Update app.py

app.py

@@ -62,6 +62,8 @@ async def on_chat_start():
     sentence_blueprint = metadata_generator(ai_blueprint_document, "AI Blueprint", sentence_text_splitter)
 
     sentence_combined_documents = sentence_framework + sentence_blueprint
+    from langchain_community.embeddings import HuggingFaceEmbeddings  # Use HuggingFaceEmbeddings if needed
+
 
     # Initialize the custom embedding class
     embedding_model = SentenceTransformerEmbedding('Cheselle/finetuned-arctic-sentence')
@@ -69,7 +71,7 @@ async def on_chat_start():
     # Create the Qdrant vector store using the custom embedding model
     sentence_vectorstore = Qdrant.from_documents(
         documents=sentence_combined_documents,
-        embedding=embedding_model,  # Ensure this is an instance
+        embedding_function=embedding_model,  # Ensure this is an instance
         location=":memory:",
         collection_name="AI Policy"
     )