This pull request refactors the get_brains_usages method in the
Analytics class. The changes include improving code readability,
optimizing database queries, and fixing potential bugs.
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description was created by [Ellipsis](https://www.ellipsis.dev) for
commit f0ad664673. |
|--------|--------|
### Summary:
This PR optimizes the `get_brains_usages` method in the `Analytics`
class by reducing database calls and improving code readability.
**Key points**:
- Refactored `get_brains_usages` method in `Analytics` class.
- Optimized database query to fetch chat history in one go.
- Improved code readability and formatting.
----
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This pull request adds PDF generation functionality and improves the
formatting of emails. It includes a new module for generating PDFs using
the fpdf2 library and updates the email templates to use markdown
formatting for better readability.
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description was created by [Ellipsis](https://www.ellipsis.dev) for
commit ccecff77a5. |
|--------|--------|
### Summary:
This PR introduces PDF generation functionality, improves email
formatting, sanitizes filenames, updates various files and dependencies,
and updates `docker-compose.dev.yml`.
**Key points**:
- Added PDF generation functionality using the `fpdf2` library
- Improved email formatting
- Sanitized filenames using the `unidecode` library
- Updated `backend/modules/assistant/ito/ito.py` to generate PDFs and
sanitize filenames
- Added `pdf_generator.py` in `backend/modules/assistant/ito/utils/` for
PDF generation
- Updated `Pipfile` and `Pipfile.lock` in
`backend/modules/assistant/ito/utils/` to include `unidecode`
- Updated `requirements.txt` with new dependencies
- Updated `docker-compose.dev.yml`
----
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This pull request improves the prompt summary in the assistant code. It
updates the map_template and reduce_template to provide clearer
instructions for identifying main themes, key points, and important
information in each section of a document. The reduce_template also
specifies that the final summary should include the main themes, key
points, and important information of the entire document.
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----
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alt="Ellipsis" width="30px" height="30px"/></a> | 🚀 This PR
description was created by [Ellipsis](https://www.ellipsis.dev) for
commit 456736a41d. |
|--------|--------|
### Summary:
This PR enhances the document summarization process in the
`SummaryAssistant` class by providing clearer instructions for
identifying main themes, key points, and important information in each
section of a document.
**Key points**:
- Updated `map_template` and `reduce_template` in `process_assistant`
function of `SummaryAssistant` class.
- Changes provide clearer instructions for summarizing documents.
- Final summary should include main themes, key points, and important
information of the entire document.
----
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This pull request adds functionality to update user usage and calculate
pricing in the ITO assistant. It includes a new method
`increase_usage_user()` that raises an error if the user has consumed
all of their credits, and a new method `calculate_pricing()` that
returns a fixed pricing value of 20.
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alt="Ellipsis" width="30px" height="30px"/></a> | 🚀 This PR
description was created by [Ellipsis](https://www.ellipsis.dev) for
commit ee5fdf70f6. |
|--------|--------|
### Summary:
This PR adds functionality to update user usage and calculate pricing in
the ITO assistant, with new methods in the `ITO` class and an update to
where the `increase_usage_user()` method is called.
**Key points**:
- Added `increase_usage_user()` and `calculate_pricing()` methods to
`ITO` class in `/backend/modules/assistant/ito/ito.py`
- `increase_usage_user()` updates user usage and raises an error if all
credits are consumed
- `calculate_pricing()` returns a fixed pricing value of 20
- `increase_usage_user()` is now called in the `ITO` class constructor
----
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This pull request adds new input models for boolean, number, select
text, and select number. These models will allow for more flexible and
dynamic input options in the software. The changes include the addition
of the `InputBoolean`, `InputNumber`, `InputSelectText`, and
`InputSelectNumber` classes to the `Inputs` model. These classes provide
properties for key, required, description, and additional options
specific to each input type. This enhancement will improve the overall
functionality and user experience of the software.
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alt="Ellipsis" width="30px" height="30px"/></a> | 🚀 This PR
description was created by [Ellipsis](https://www.ellipsis.dev) for
commit 6fa583b6a8. |
|--------|--------|
### Summary:
This PR enhances the `Inputs` model by adding new input models for
boolean, number, select text, and select number, improving the
software's functionality and user experience.
**Key points**:
- Added `InputBoolean`, `InputNumber`, `InputSelectText`, and
`InputSelectNumber` classes to `Inputs` model in `inputs.py` and
`outputs.py`.
- Each new class provides properties for key, required, description, and
additional options specific to each input type.
----
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# 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):
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alt="Ellipsis" width="30px" height="30px"/></a> | 🚀 This PR
description was created by [Ellipsis](https://www.ellipsis.dev) for
commit 5350e0a071. |
|--------|--------|
### Summary:
This PR adds a new script for evaluating the RAG model using the Ragas
library, with results saved as a JSON file and printed to the console.
**Key points**:
- New script `run_evaluation.py` added to
`backend/tests/ragas_evaluation/`.
- The script processes documents, generates replies using a QuivrRAG
chain, and evaluates the replies using specified metrics.
- Results are saved as a JSON file and printed to the console.
- The script can be run from the command line with various options.
----
Generated with ❤️ by [ellipsis.dev](https://www.ellipsis.dev)
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---------
Co-authored-by: Damien Mourot <damien.mourot@gmail.com>
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
This pull request adds an icon and description to the assistant. The
icon is displayed in the user interface and the description provides
additional information about the assistant.
This pull request adds a new optional field "tags" to the
AssistantOutput classes. The "tags" field allows for categorizing the
outputs and can be used for filtering or organizing purposes.
…dio_transcript and crawler assistants
# Description
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## Screenshots (if appropriate):
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Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
# Description
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# Description
Added ability to upload .bib files to brain using langchain bibtex
document loader. Also changed frontend to allow the choosing of said
file.
Looking for guidance on how to run unit tests locally!
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my feature works
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This pull request adds a new field, `url_required`, to the
`IngestionEntity` class. This field is required for the ingestion
process and will be used to store the URL of the entity.
# Description
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also include relevant motivation and context.
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my feature works
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## Screenshots (if appropriate):
This pull request adds the ingestion module and routes to the project.
It includes the necessary files and code changes to implement the
ingestion functionality.
# Description
Readme has a typo in step 1 for the directory name to `cd` into
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## Screenshots (if appropriate):
# Description
Two small comment changes in the .env file. One to reposition the main
file comment to the top of the file and the other to add a comment to
the OpenAI config line per https://github.com/QuivrHQ/quivr/issues/2384
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## Screenshots (if appropriate):
# Description
TODO BEFORE RELEASE
- [ ] Onboarded true for all existing users
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Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
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Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
# Description
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# Description
Optimize the docker image for cpu-only environment. (PyTorch in cpu
mode, cuda not installed etc) This should reduce the backend docker
image size by ~2
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# Description
Fix match_vectors function that rank chunks in the wrong order
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## Screenshots (if appropriate):
