This pull request adds the flashrank and contextual compression
retriever to the codebase. The flashrank reranker model is used for
compression, and the contextual compression retriever combines the base
compressor and base retriever to improve document retrieval.
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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### 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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# 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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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>
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
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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 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
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also include relevant motivation and context.
## Checklist before requesting a review
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my feature works
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- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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my feature works
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## Screenshots (if appropriate):
# 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):
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Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com>
added ocr
# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
moved to brains
# Description
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## Checklist before requesting a review
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## Screenshots (if appropriate):
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Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com>
# Description
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also include relevant motivation and context.
## Checklist before requesting a review
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- [ ] My code follows the style guidelines of this project
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my feature works
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## Screenshots (if appropriate):
backend test fixed
# 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):
