FAISS Vector Store Retriever

[github-actions]

Description

Add a FAISSRetriever backed by Facebook AI Similarity Search for fast approximate nearest-neighbour search.

Motivation

InMemoryRetriever is O(N) at query time and unsuitable for large corpora. FAISS scales to millions of vectors with sub-millisecond query latency via efficient indexing structures.

Acceptance criteria

• Class FAISSRetriever in ragframework/retriever/faiss.py
• Subclasses Retriever from ragframework/base.py
• Uses faiss-cpu (already listed in [faiss] optional extra in pyproject.toml)
• Import guarded with helpful message pointing to pip install ragframework[faiss]
• Raises RetrieverError on failure
• Unit tests in tests/test_retriever/test_faiss.py
• Exported from ragframework/retriever/__init__.py
• CHANGELOG.md updated under [Unreleased]

Files to touch

• ragframework/retriever/faiss.py — new file
• ragframework/retriever/__init__.py — export it
• tests/test_retriever/test_faiss.py — new test file

Resources

• faiss-cpu on PyPI
• FAISS wiki
• InMemoryRetriever in ragframework/retriever/in_memory.py as reference