embedding

app.py

@@ -31,10 +31,11 @@ def predict(query,history):
         template=template,
     )
 
+    embeddings = OpenAIEmbeddings(model="text-embedding-ada-002")
     my_activeloop_org_id = "utkarshtiwari"
     my_activeloop_dataset_name = "modelwise_dataset"
     dataset_path = f"hub://{my_activeloop_org_id}/{my_activeloop_dataset_name}"
-    db = DeepLake(dataset_path=dataset_path, read_only=True)
+    db = DeepLake(dataset_path=dataset_path, read_only=True, embedding_function = embeddings)
     # Retrieve relevant chunks from the Knowledge Base
     docs = db.similarity_search(query)
     retrieved_chunks = [doc.page_content for doc in docs]