vector_db.py

from qdrant_client import QdrantClient
from qdrant_client.models import VectorParams, Distance, PointStruct


class QdrantStorage:
    def __init__(self, path="./qdrant_storage", collection="docs", dim=3072):
        # Use local mode - this will use your existing data
        self.client = QdrantClient(path=path)
        self.collection = collection
        if not self.client.collection_exists(self.collection):
            self.client.create_collection(
                collection_name=self.collection,
                vectors_config=VectorParams(size=dim, distance=Distance.COSINE),
            )

    def upsert(self, ids, vectors, payloads):
        points = [PointStruct(id=ids[i], vector=vectors[i], payload=payloads[i]) for i in range(len(ids))]
        self.client.upsert(self.collection, points=points)

    def search(self, query_vector, top_k: int = 5, source_filter: str = None):
        from qdrant_client.models import Filter, FieldCondition, MatchValue
        
        # If source_filter is provided, only search within that source
        if source_filter:
            results = self.client.search(
                collection_name=self.collection,
                query_vector=query_vector,
                query_filter=Filter(
                    must=[
                        FieldCondition(
                            key="source",
                            match=MatchValue(value=source_filter)
                        )
                    ]
                ),
                with_payload=True,
                limit=top_k
            )
        else:
            # Search across all sources
            results = self.client.search(
                collection_name=self.collection,
                query_vector=query_vector,
                with_payload=True,
                limit=top_k
            )
        
        contexts = []
        sources = set()

        for r in results:
            payload = getattr(r, "payload", None) or {}
            text = payload.get("text", "")
            source = payload.get("source", "")
            if text:
                contexts.append(text)
                sources.add(source)

        return {"contexts": contexts, "sources": list(sources)}