# app/store.py
import chromadb
from chromadb.config import Settings

class VectorStore:
    def __init__(self, path="../data/vector_store"):
        self.client = chromadb.PersistentClient(path=path, settings=Settings(anonymized_telemetry=False))
        self.collection = self.client.get_or_create_collection(name="ece_concepts")
        print(f"✅ Vector store initialized at {path}")

    def add_documents(self, docs, embeddings):
        ids = [str(i) for i in range(len(docs))]
        # embeddings is a numpy array; convert to list for Chroma
        self.collection.add(documents=docs, embeddings=embeddings.tolist(), ids=ids)
        print(f"🧠 Stored {len(docs)} chunks in vector DB.")

    def retrieve_similar_docs(self, query_embedding, top_k=3):
        results = self.collection.query(
            query_embeddings=[query_embedding.tolist()],
            n_results=top_k
        )
        docs = results.get("documents", [])[0]  # list of docs
        return docs