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quivr/backend/requirements.lock

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feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# generated by rye
# use `rye lock` or `rye sync` to update this lockfile
#
# last locked with the following flags:
# pre: false
# features: ["quivr-core/all"]
# all-features: false
# with-sources: true
# generate-hashes: false
# universal: true
--index-url https://pypi.org/simple/
--extra-index-url https://download.pytorch.org/whl/cpu
-e file:.
-e file:api
# via quivr-worker
-e file:core
# via quivr-api
# via quivr-worker
-e file:worker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
aiofiles==24.1.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
aiohappyeyeballs==2.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via aiohttp
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
aiohttp==3.10.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain
# via langchain-community
# via litellm
# via llama-index-core
# via llama-index-legacy
# via realtime
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
aiosignal==1.3.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via aiohttp
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
amqp==5.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via kombu
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
annotated-types==0.7.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pydantic
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
anthropic==0.34.1
# via langchain-anthropic
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
antlr4-python3-runtime==4.9.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via omegaconf
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
anyio==4.4.0
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via httpx
# via openai
# via starlette
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
async-timeout==4.0.3 ; python_full_version < '3.12'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via asyncpg
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
asyncpg==0.29.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
attrs==24.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via aiohttp
# via jsonschema
# via referencing
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
backoff==2.2.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via posthog
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
beautifulsoup4==4.12.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-readers-file
# via markdownify
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
billiard==4.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
boto3==1.35.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
botocore==1.35.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via boto3
# via s3transfer
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
cachetools==5.5.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-auth
celery==5.4.0
# via flower
# via quivr-api
# via quivr-worker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
certifi==2022.12.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via httpcore
# via httpx
# via requests
# via sentry-sdk
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
cffi==1.17.0 ; platform_python_implementation != 'PyPy'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cryptography
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
chardet==5.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
charset-normalizer==2.1.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pdfminer-six
# via requests
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
click==8.1.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
# via click-didyoumean
# via click-plugins
# via click-repl
# via litellm
# via nltk
# via uvicorn
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
click-didyoumean==0.3.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
click-plugins==1.1.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
click-repl==0.3.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
cobble==0.1.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via mammoth
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
cohere==5.8.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
colorama==0.4.6 ; sys_platform == 'win32' or platform_system == 'Windows'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via click
# via colorlog
# via tqdm
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
coloredlogs==15.0.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via onnxruntime
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
colorlog==6.8.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
contourpy==1.2.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via matplotlib
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
cryptography==43.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via msal
# via pdfminer-six
# via pyjwt
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
cycler==0.12.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via matplotlib
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
dataclasses-json==0.6.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-community
# via llama-index-core
# via llama-index-legacy
# via unstructured
# via unstructured-client
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
defusedxml==0.7.1
# via langchain-anthropic
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
deprecated==1.2.14
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-core
# via llama-index-legacy
# via pikepdf
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
deprecation==2.1.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via postgrest
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
dirtyjson==1.0.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-core
# via llama-index-legacy
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
distro==1.9.0
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via openai
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
docx2txt==0.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
dropbox==12.0.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
ecdsa==0.19.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via python-jose
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
effdet==0.4.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
emoji==2.12.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
et-xmlfile==1.1.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via openpyxl
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
faiss-cpu==1.8.0.post1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
fastapi==0.112.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
# via sentry-sdk
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
fastavro==1.9.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
filelock==3.13.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via huggingface-hub
# via torch
# via transformers
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
filetype==1.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
fire==0.6.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pdf2docx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
flatbuffers==24.3.25
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via onnxruntime
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
flower==2.0.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-worker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
fonttools==4.53.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via matplotlib
# via pdf2docx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
fpdf==1.7.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
frozenlist==1.4.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via aiohttp
# via aiosignal
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
fsspec==2024.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via huggingface-hub
# via llama-index-core
# via llama-index-legacy
# via torch
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
google-api-core==2.19.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-python-client
# via google-cloud-vision
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
google-api-python-client==2.142.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
google-auth==2.34.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-core
# via google-api-python-client
# via google-auth-httplib2
# via google-auth-oauthlib
# via google-cloud-vision
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
google-auth-httplib2==0.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-python-client
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
google-auth-oauthlib==1.2.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
google-cloud-vision==3.7.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
googleapis-common-protos==1.63.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-core
# via grpcio-status
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
gotrue==2.7.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via supabase
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
greenlet==3.0.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via playwright
# via sqlalchemy
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
grpcio==1.65.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-core
# via grpcio-status
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
grpcio-status==1.65.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
h11==0.14.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via httpcore
# via uvicorn
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
h2==4.1.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via httpx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
hpack==4.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via h2
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
httpcore==1.0.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via httpx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
httplib2==0.22.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-python-client
# via google-auth-httplib2
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
httpx==0.27.0
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
# via gotrue
# via langsmith
# via llama-cloud
# via llama-index-core
# via llama-index-legacy
# via notion-client
# via openai
# via postgrest
# via quivr-core
# via storage3
# via supabase
# via supafunc
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
httpx-sse==0.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
huggingface-hub==0.24.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via timm
# via tokenizers
# via transformers
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
humanfriendly==10.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via coloredlogs
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
humanize==4.10.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via flower
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
hyperframe==6.0.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via h2
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
idna==3.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via anyio
# via httpx
# via requests
# via unstructured-client
# via yarl
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
importlib-metadata==8.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via litellm
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
iopath==0.1.10
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via layoutparser
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jinja2==3.1.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via litellm
# via torch
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jiter==0.5.0
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via openai
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jmespath==1.0.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via boto3
# via botocore
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
joblib==1.4.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via nltk
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jsonpatch==1.33
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jsonpath-python==1.0.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jsonpointer==3.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via jsonpatch
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jsonschema==4.23.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via litellm
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
jsonschema-specifications==2023.12.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via jsonschema
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
kiwisolver==1.4.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via matplotlib
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
kombu==5.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langchain==0.2.14
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-community
# via megaparse
# via quivr-api
# via quivr-core
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
langchain-anthropic==0.1.23
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langchain-cohere==0.2.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langchain-community==0.2.12
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-experimental
# via megaparse
# via quivr-api
# via quivr-core
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
langchain-core==0.2.38
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via langchain-anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-cohere
# via langchain-community
# via langchain-experimental
# via langchain-openai
# via langchain-text-splitters
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
# via langgraph
# via langgraph-checkpoint
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langchain-experimental==0.0.64
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langchain-openai==0.1.22
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langchain-text-splitters==0.2.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langdetect==1.0.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
langgraph==0.2.14
# via quivr-core
langgraph-checkpoint==1.0.6
# via langgraph
langsmith==0.1.100
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain
# via langchain-community
# via langchain-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
layoutparser==0.3.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
litellm==1.43.19
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-cloud==0.0.13
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-indices-managed-llama-cloud
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index==0.10.67.post1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-agent-openai==0.2.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
# via llama-index-program-openai
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-cli==0.1.13
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-core==0.10.67
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
# via llama-index-agent-openai
# via llama-index-cli
# via llama-index-embeddings-openai
# via llama-index-indices-managed-llama-cloud
# via llama-index-llms-openai
# via llama-index-multi-modal-llms-openai
# via llama-index-program-openai
# via llama-index-question-gen-openai
# via llama-index-readers-file
# via llama-index-readers-llama-parse
# via llama-parse
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-embeddings-openai==0.1.11
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
# via llama-index-cli
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-indices-managed-llama-cloud==0.2.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-legacy==0.9.48.post3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-llms-openai==0.1.30
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
# via llama-index-agent-openai
# via llama-index-cli
# via llama-index-multi-modal-llms-openai
# via llama-index-program-openai
# via llama-index-question-gen-openai
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-multi-modal-llms-openai==0.1.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-program-openai==0.1.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
# via llama-index-question-gen-openai
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-question-gen-openai==0.1.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-readers-file==0.1.33
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-index-readers-llama-parse==0.1.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
llama-parse==0.4.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-readers-llama-parse
# via megaparse
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
lxml==5.3.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pikepdf
# via python-docx
# via python-pptx
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
mammoth==1.8.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
markdown==3.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
markdown-it-py==3.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via rich
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
markdownify==0.13.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
markupsafe==2.1.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via jinja2
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
marshmallow==3.22.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via dataclasses-json
# via marshmallow-enum
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
marshmallow-enum==1.5.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
matplotlib==3.9.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pycocotools
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
mdurl==0.1.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via markdown-it-py
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
megaparse==0.0.31
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
monotonic==1.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via posthog
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
mpmath==1.3.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via sympy
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
msal==1.30.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
multidict==6.0.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via aiohttp
# via yarl
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
mypy-extensions==1.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via typing-inspect
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
nest-asyncio==1.6.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-core
# via llama-index-legacy
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
networkx==3.2.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-core
# via llama-index-legacy
# via torch
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
nltk==3.9.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-core
# via llama-index-legacy
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
notion-client==2.2.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
numpy==1.26.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via contourpy
# via faiss-cpu
# via langchain
# via langchain-community
# via layoutparser
# via llama-index-core
# via llama-index-legacy
# via matplotlib
# via onnx
# via onnxruntime
# via opencv-python
# via opencv-python-headless
# via pandas
# via pdf2docx
# via pgvector
# via pycocotools
# via scipy
# via torchvision
# via transformers
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
oauthlib==3.2.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via requests-oauthlib
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
omegaconf==2.3.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
onnx==1.16.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
onnxruntime==1.19.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
openai==1.42.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-openai
# via litellm
# via llama-index-agent-openai
# via llama-index-core
# via llama-index-legacy
# via llama-index-llms-openai
# via quivr-api
# via quivr-worker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
opencv-python==4.10.0.84
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via layoutparser
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
opencv-python-headless==4.10.0.84
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pdf2docx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
openpyxl==3.1.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
orjson==3.10.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langsmith
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
packaging==24.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via deprecation
# via faiss-cpu
# via huggingface-hub
# via langchain-core
# via marshmallow
# via matplotlib
# via onnxruntime
# via pikepdf
# via quivr-monorepo
# via transformers
# via unstructured-client
# via unstructured-pytesseract
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pandas==2.2.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-cohere
# via layoutparser
# via llama-index-core
# via llama-index-legacy
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
parameterized==0.9.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pdf2docx==0.5.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pdf2image==1.17.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via layoutparser
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pdfminer-six==20231228
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pdfplumber
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pdfplumber==0.11.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via layoutparser
# via megaparse
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pgvector==0.3.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pikepdf==9.1.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pillow==10.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via layoutparser
# via llama-index-core
# via matplotlib
# via pdf2image
# via pdfplumber
# via pikepdf
# via pillow-heif
# via python-pptx
# via torchvision
# via unstructured-pytesseract
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pillow-heif==0.18.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
playwright==1.46.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-worker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
ply==3.11
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via stone
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
portalocker==2.10.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via iopath
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
postgrest==0.16.10
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via supabase
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
posthog==3.5.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
prometheus-client==0.20.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via flower
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
prompt-toolkit==3.0.47
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via click-repl
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
proto-plus==1.24.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-core
# via google-cloud-vision
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
protobuf==5.27.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-core
# via google-cloud-vision
# via googleapis-common-protos
# via grpcio-status
# via onnx
# via onnxruntime
# via proto-plus
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
psutil==6.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
psycopg2-binary==2.9.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyasn1==0.6.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pyasn1-modules
# via python-jose
# via rsa
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyasn1-modules==0.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-auth
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pycocotools==2.0.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pycparser==2.22 ; platform_python_implementation != 'PyPy'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cffi
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pycryptodome==3.20.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pydantic==2.8.2
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
# via fastapi
# via gotrue
# via langchain
# via langchain-core
# via langsmith
# via litellm
# via llama-cloud
# via openai
# via postgrest
# via pydantic-settings
# via quivr-core
# via sqlmodel
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pydantic-core==2.20.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
# via pydantic
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pydantic-settings==2.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyee==11.1.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via playwright
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pygments==2.18.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via rich
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyinstrument==4.7.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyjwt==2.9.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via msal
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pymupdf==1.24.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pdf2docx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pymupdfb==1.24.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pymupdf
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pypandoc==1.13
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyparsing==3.1.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via httplib2
# via matplotlib
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pypdf==4.3.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-readers-file
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pypdfium2==4.30.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via pdfplumber
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyreadline3==3.4.1 ; sys_platform == 'win32'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via humanfriendly
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-dateutil==2.9.0.post0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via botocore
# via celery
# via matplotlib
# via pandas
# via posthog
# via realtime
# via storage3
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-docx==1.1.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
# via pdf2docx
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-dotenv==1.0.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via litellm
# via megaparse
# via pydantic-settings
# via quivr-api
# via quivr-worker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-iso639==2024.4.27
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-jose==3.3.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-magic==0.4.27
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-multipart==0.0.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
python-pptx==1.0.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pytz==2024.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via flower
# via pandas
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pywin32==306 ; platform_system == 'Windows'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via portalocker
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
pyyaml==6.0.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via huggingface-hub
# via langchain
# via langchain-community
# via langchain-core
# via layoutparser
# via llama-index-core
# via omegaconf
# via timm
# via transformers
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
rapidfuzz==3.9.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
realtime==2.0.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via supabase
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
redis==5.0.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
referencing==0.35.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via jsonschema
# via jsonschema-specifications
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
regex==2024.7.24
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via nltk
# via tiktoken
# via transformers
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
requests==2.32.3
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
# via dropbox
# via google-api-core
# via huggingface-hub
# via langchain
# via langchain-community
# via langsmith
# via litellm
# via llama-index-core
# via llama-index-legacy
# via msal
# via posthog
# via requests-oauthlib
# via resend
# via tiktoken
# via transformers
# via unstructured
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
requests-oauthlib==2.0.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-auth-oauthlib
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
resend==2.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
rich==13.7.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
rpds-py==0.20.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via jsonschema
# via referencing
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
rsa==4.9
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-auth
# via python-jose
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
s3transfer==0.10.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via boto3
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
safetensors==0.4.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via timm
# via transformers
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
scipy==1.14.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via layoutparser
sentry-sdk==2.13.0
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
six==1.16.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via dropbox
# via ecdsa
# via fire
# via langdetect
# via markdownify
# via posthog
# via python-dateutil
# via stone
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
sniffio==1.3.1
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via anyio
# via httpx
# via openai
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
soupsieve==2.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via beautifulsoup4
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
sqlalchemy==2.0.32
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain
# via langchain-community
# via llama-index-core
# via llama-index-legacy
# via sqlmodel
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
sqlmodel==0.0.21
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
starlette==0.38.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via fastapi
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
stone==3.3.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via dropbox
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
storage3==0.7.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via supabase
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
strenum==0.4.15
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via postgrest
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
striprtf==0.0.26
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via llama-index-readers-file
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
supabase==2.7.2
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
supafunc==0.5.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via supabase
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
sympy==1.12
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via onnxruntime
# via torch
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tabulate==0.9.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-cohere
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tenacity==8.5.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain
# via langchain-community
# via langchain-core
# via llama-index-core
# via llama-index-legacy
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
termcolor==2.4.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via fire
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tiktoken==0.7.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via langchain-openai
# via litellm
# via llama-index-core
# via llama-index-legacy
# via quivr-api
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
timm==1.0.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tokenizers==0.19.1
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
# via litellm
# via transformers
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
torch==2.4.0 ; platform_machine != 'x86_64'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
# via quivr-worker
# via timm
# via torchvision
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
torch==2.4.0+cpu ; platform_machine == 'x86_64'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
# via quivr-worker
# via timm
# via torchvision
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
torchvision==0.19.0 ; platform_machine != 'x86_64'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
# via quivr-worker
# via timm
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
torchvision==0.19.0+cpu ; platform_machine == 'x86_64'
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via effdet
# via quivr-worker
# via timm
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tornado==6.4.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via flower
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tqdm==4.66.5
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via huggingface-hub
# via iopath
# via llama-index-core
# via nltk
# via openai
# via transformers
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
transformers==4.44.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured-inference
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
types-requests==2.31.0.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
types-urllib3==1.26.25.14
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via types-requests
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
typing-extensions==4.12.2
feat(anthropic): add llm (#3146) This commit adds the langchain_openai and langchain_anthropic dependencies to the `llm_endpoint.py` file. # Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
2024-09-04 16:24:21 +03:00
# via anthropic
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via cohere
# via emoji
# via fastapi
# via huggingface-hub
# via iopath
# via langchain-core
# via llama-index-core
# via llama-index-legacy
# via openai
# via pydantic
# via pydantic-core
# via pyee
# via python-docx
# via python-pptx
# via realtime
# via resend
# via sqlalchemy
# via storage3
# via torch
# via typing-inspect
# via unstructured
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
typing-inspect==0.9.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via dataclasses-json
# via llama-index-core
# via llama-index-legacy
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
tzdata==2024.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via celery
# via pandas
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
unidecode==1.3.8
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
unstructured==0.15.7
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via megaparse
# via quivr-core
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
unstructured-client==0.8.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
unstructured-inference==0.7.36
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
unstructured-pytesseract==0.3.13
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
uritemplate==4.1.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via google-api-python-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
urllib3==1.26.13
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via botocore
# via requests
# via sentry-sdk
# via unstructured-client
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
uvicorn==0.30.6
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
uvloop==0.20.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via quivr-api
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
vine==5.1.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via amqp
# via celery
# via kombu
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
wcwidth==0.2.13
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via prompt-toolkit
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
websockets==12.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via realtime
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
wrapt==1.16.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via deprecated
# via llama-index-core
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
xlrd==2.0.1
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via unstructured
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
xlsxwriter==3.2.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via python-pptx
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
yarl==1.9.4
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via aiohttp
feat: using langgraph in our RAG pipeline (#3130) # Description Using LangGraph instead of LangChain LCEL to build and run the RAG pipeline, as LangGraph enables greater flexibility and an easier maintainability of complex (agentic) pipelines Completes CORE-175 ## Checklist before requesting a review Please delete options that are not relevant. - [x] My code follows the style guidelines of this project - [x] I have performed a self-review of my code - [x] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [x] Any dependent changes have been merged ## Screenshots (if appropriate): --------- Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
2024-09-03 16:23:23 +03:00
zipp==3.20.0
feat: quivr core 0.1 (#2970) # Description # Testing backend ## Docker setup 1. Copy `.env.example` to `.env`. Some env variables were added : EMBEDDING_DIM 2. Apply supabase migratrions : ```sh supabase stop supabase db reset supabase start ``` 3. Start backend containers ``` make dev ``` ## Local setup You can also run backend without docker. 1. Install [`rye`](https://rye.astral.sh/guide/installation/). Choose the managed python version and set the version to 3.11 2. Run the following: ``` cd quivr/backend rye sync ``` 3. Source `.venv` virtual env : `source .venv/bin/activate` 4. Run the backend, make sure you are running redis and supabase API: ``` LOG_LEVEL=debug uvicorn quivr_api.main:app --log-level debug --reload --host 0.0.0.0 --port 5050 --workers 1 ``` Worker: ``` LOG_LEVEL=debug celery -A quivr_worker.celery_worker worker -l info -E --concurrency 1 ``` Notifier: ``` LOG_LEVEL=debug python worker/quivr_worker/celery_monitor.py ``` --------- Co-authored-by: chloedia <chloedaems0@gmail.com> Co-authored-by: aminediro <aminedirhoussi1@gmail.com> Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com> Co-authored-by: Chloé Daems <73901882+chloedia@users.noreply.github.com> Co-authored-by: Zewed <dewez.antoine2@gmail.com>
2024-09-02 11:20:53 +03:00
# via importlib-metadata
Reference in New Issue Copy Permalink