# qdrant_functions.py
import logging
from qdrant_client import QdrantClient
from sentence_transformers import SentenceTransformer
import uuid
import os

QDRANT_HOST = os.getenv("QDRANT_HOST", "localhost")
QDRANT_PORT = int(os.getenv("QDRANT_PORT", 6333))
QDRANT_COLLECTION = os.getenv("QDRANT_COLLECTION", "abot-slack")

client = QdrantClient(host=QDRANT_HOST, port=QDRANT_PORT)

embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
VECTOR_SIZE = 384

def ensure_collection():
    collections = [c.name for c in client.get_collections().collections]
    if QDRANT_COLLECTION not in collections:
        client.create_collection(
            collection_name=QDRANT_COLLECTION,
            vectors_config={
                "size": VECTOR_SIZE,
                "distance": "Cosine"
            }
        )
        logging.info(f"Created Qdrant collection {QDRANT_COLLECTION}")

ensure_collection()