vector_store.py

import uuid

from config import client, COLLECTION
from embeddings import embed


def index_doc(text, payload):

    vector = embed(text)

    client.upsert(
        collection_name=COLLECTION,
        points=[{
            "id": str(uuid.uuid4()),
            "vector": vector,
            "payload": payload | {"text": text}
        }]
    )


def search(query, k=3):

    vector = embed(query)

    results = client.search(
        collection_name=COLLECTION,
        query_vector=vector,
        limit=k
    )

    return [r.payload for r in results]