same Embedded update as before in diff location

app.py

@@ -277,7 +277,7 @@ def ask_question(question: str, openai_apikey: str, curation_names: List[str]):
   openai.api_key = openai_apikey
   # query vector db for topk chunks
   # can't use langchain bc we are using pinecone metadata filtering
-  q_embedding = Embedder(question).tolist()
+  q_embedding = Embedder(question)#.tolist()
   curations_dict = curation_name2id()
   curation_ids = [curations_dict[name] for name in curation_names]
   results = Pinecone_index.query(vector=q_embedding, filter={'curation_ids': {"$in": curation_ids}}, top_k=5, include_metadata=True)