# Description
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## Screenshots (if appropriate):
---------
Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
# 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
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
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# Description
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## Checklist before requesting a review
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This pull request adds optional fields to the UserIdentity and
UserUpdatableProperties classes in order to allow for more flexibility
when updating user properties. The new fields include username, company,
and onboarded. Additionally, the database schema has been updated to
reflect these changes.
# Description
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also include relevant motivation and context.
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This pull request updates the langchain.prompts and
langchain_core.messages modules. It includes changes to the code that
improve functionality and fix any existing issues.
# Description
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also include relevant motivation and context.
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# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
This pull request includes a feature update to the newest version of
litellm. This update brings in the latest enhancements and bug fixes to
improve the functionality and performance of the software.
# Description
With this pull request, I add a fix that **enables Ollama**.
Running quivr in a Docker container, Ollama needs to be accessed via
http://host.docker.internal:11434.
This URL is defined as `api_base` of the `ChatLiteLLM` constructor. But
there are calls that are missing `api_base`. This leads to fallback URLs
being used. This is now fixed.
Fixes#2270#2267#2217#2204
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## Screenshots (if appropriate):
None
Co-authored-by: Niels Garve <niels.garve@experienceone.com>
This pull request updates the integration types and classes in the
codebase. It includes the following commits:
- Update logo_url field in brain entity and integration_brain entity
- Update integration references in BrainsUsers and IntegrationBrain
classes
- Revert "Update integration references in BrainsUsers and
IntegrationBrain classes"
- Revert "Update logo_url field in brain entity and integration_brain
entity"
- Add 'doc' integration type and KnowledgeBrainQA class
Please review and merge these changes.
This pull request adds a custom integration feature and sync
functionality to the application. It includes the following changes:
- Added a new integration entity for custom integrations.
- Implemented the ability to load and poll the custom integration.
- Added a task to sync the custom integration with the user's brain.
- Updated the celery beat schedule to include the new task.
Please review and merge this pull request.
This pull request updates the origins in cors.py, origin in
resend_invitation_email.py, and referring_site in
add-new-email/index.ts. It also refactors the code in home/page.tsx and
next.config.js.
This pull request removes the healthz endpoint from the Sentry
integration. The `before_send` function has been updated to drop
transaction events that contain 'healthz' in the transaction name. This
change ensures that healthz transactions are not sent to Sentry.
This pull request adds the `max_input` and `max_tokens` parameters to
the `KnowledgeBrainQA` constructor. These parameters allow for setting
the maximum input length and maximum number of tokens for the
KnowledgeBrainQA model. This provides more flexibility and control over
the input size and tokenization process.
This pull request reduces the sampling rate for Sentry traces to 0.1.
This change ensures that only a small percentage of traces are captured,
which helps to reduce the impact on performance and storage.
This pull request fixes the `get_brain_details` API by adding a
`user_id` parameter. Previously, the API did not include the `user_id`
parameter, which caused issues when retrieving brain details. This fix
ensures that the `user_id` is passed correctly to the API, allowing for
accurate retrieval of brain details.
# Description
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## Checklist before requesting a review
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my feature works
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# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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## Screenshots (if appropriate):
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
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my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
This pull request adds a new attribute, max_files, to the
MinimalUserBrainEntity class in the BrainsUsers repository. The
max_files attribute represents the maximum number of files allowed for a
brain integration.
This pull request adds Redis configuration to the `celery_config.py`
file. The `CELERY_BROKER_URL` has been replaced with `REDIS_HOST`,
`REDIS_PORT`, and `REDIS_PASS` environment variables to configure the
Redis broker and backend. This change allows for better integration with
Redis in the application.
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
This pull request updates the brain authorization and integration
entities. It includes changes to the `retrieve_brain_by_id`,
`update_existing_brain`, `update_existing_brain_secrets`,
`CreateApiBrainDefinition`, `CreateIntegrationBrain`,
`BrainIntegrationSettings`, `BrainIntegrationUpdateSettings`,
`CreateBrainProperties`, and `BrainUpdatableProperties` classes.
This pull request adds a new method called `calculate_pricing` to the
`GPT4Brain` class in the codebase. This method calculates the pricing
for the GPT4Brain model. Additionally, the user usage in the chat
controller has been updated to include the new pricing calculation
method.
This pull request updates the system templates to include support for
custom personality. It adds a new parameter called "custom_personality"
to the generate_stream function, which allows users to provide a custom
personality for the AI assistant. This feature enhances the user
experience by allowing them to personalize the assistant's responses.
# Description
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# Description
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# Description
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# Description
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# Description
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Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com>
added ocr
# Description
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# Description
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# Description
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## Screenshots (if appropriate):
