Core retrieval features#2
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- Updated `.env.example` to include new environment variables for embedding backends (OpenAI and local options). - Modified `pyproject.toml` description to reflect optional OpenAI/local embeddings. - Expanded `README.md` to clarify the architecture and embedding backend options. - Introduced `metadata` field in the `chunks` table for enhanced filtering capabilities. - Added `eval_recall.py` script for testing retrieval accuracy with metadata filters. - Implemented pluggable embedding backends in `embedding_backend.py` to support demo, OpenAI, and local embeddings. - Enhanced API to accept `metadata_filter` in retrieval requests and updated related tests. This commit improves the overall flexibility and usability of the RAG retrieval system, allowing for more robust embedding options and metadata handling.
- Updated project version in `pyproject.toml` to 1.2.0. - Updated `openapi.json` to reflect the new version. - Bumped versions of several dependencies in `uv.lock`, including `markdown-it-py`, `pip`, `pydantic`, and `pydantic-core` to their latest releases. This commit prepares the project for the next release and ensures compatibility with updated dependencies.
Co-authored-by: Cursor <cursoragent@cursor.com>
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Draft pull request: merge
feature/core-retrieval-featuresintomain.Made with Cursor