Update app.py

app.py

@@ -45,7 +45,8 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
     qa_chain = RetrievalQA.from_chain_type(llm, retriever = vector_db.as_retriever(search_kwargs = {"k": 3}), return_source_documents = True, chain_type_kwargs = {"prompt": QA_CHAIN_PROMPT})
     result = qa_chain({"query": prompt})
     #print(result)
-    openai.api_key = ""
+    openai.api_key = None
+    llm = None
     return result["result"]
 
 description = """<strong>Overview:</strong> The app demonstrates how to use a Large Language Model (LLM) with Retrieval Augmented Generation (RAG) on external data