Use real Qdrant client integration for RAG memory: update main.py

2026-06-16 11:01:05 +00:00
parent 9ba475d433
commit bca976448e
1 changed files with 2 additions and 1 deletions
@@ -11,7 +11,8 @@ from langchain_core.tools import tool
 from langchain_ollama import ChatOllama, OllamaEmbeddings
 from langchain_qdrant import QdrantVectorStore
 from langchain_text_splitters import RecursiveCharacterTextSplitter
-from qdrant_client import QdrantClient, Distance, VectorParams
+from qdrant_client import QdrantClient
+from qdrant_client.models import Distance, VectorParams

 QDRANT_URL = os.getenv("QDRANT_URL", "http://localhost:6333")
 QDRANT_COLLECTION = os.getenv("QDRANT_COLLECTION", "rag_memory")