rag.py #1

"""RAG knowledge base retrieval (Phase 3).

Provides domain-specific document retrieval using chromadb + sentence
transformers. Injected into ContextBuilder at context assembly time.
"""
from __future__ import annotations

import logging
from pathlib import Path

logger = logging.getLogger(__name__)


class RAGRetriever:
    """Retrieves relevant P4 domain documentation chunks for a given query.

    Uses chromadb (local, no server required) with sentence-transformer
    embeddings. At P4 documentation scale this is trivially sized.
    """

    def __init__(self, db_path: Path, top_k: int = 5) -> None:
        raise NotImplementedError

    def retrieve(self, query: str) -> list[str]:
        """Return top_k relevant document chunks for the given query."""
        raise NotImplementedError

    def ingest(self, documents: list[str], metadatas: list[dict]) -> None:
        """Add documents to the vector store."""
        raise NotImplementedError