Solution published: update vectorstore.py

vectorstore.py

@@ -1,30 +1,30 @@
 from pathlib import Path
 from uuid import uuid4
 
-from langchain_chroma import Chroma
+from langchain_qdrant import Qdrant
 from langchain_core.documents import Document
 from langchain_ollama import OllamaEmbeddings
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 
-CHROMA_DIR = "./chroma_db"
+QDRANT_DIR = "./qdrant_db"
 COLLECTION_NAME = "local_kb"
 EMBED_MODEL = "nomic-embed-text"
 OLLAMA_BASE_URL = "http://127.0.0.1:11434"
 
 
-def create_vectorstore(persist_directory: str = CHROMA_DIR) -> Chroma:
+def create_vectorstore(persist_directory: str = QDRANT_DIR) -> Qdrant:
     embeddings = OllamaEmbeddings(
         model=EMBED_MODEL,
         base_url=OLLAMA_BASE_URL,
     )
-    return Chroma(
+    return Qdrant(
         collection_name=COLLECTION_NAME,
         embedding_function=embeddings,
         persist_directory=persist_directory,
     )
 
 
-def load_documents(directory: str, vectorstore: Chroma) -> int:
+def load_documents(directory: str, vectorstore: Qdrant) -> int:
     splitter = RecursiveCharacterTextSplitter(
         chunk_size=1000,
         chunk_overlap=200,