Update app.py

app.py

@@ -24,7 +24,7 @@ def construct_index(directory_path):
     temperature = 0.1
 
     prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
-    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=temperature, model_name="text-embedding-ada-002", max_tokens=num_outputs))
+    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=temperature, model_name="text-embedding-3-large", max_tokens=num_outputs))
     documents = SimpleDirectoryReader(directory_path).load_data()
     #index = GPTVectorStoreIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
     index = GPTVectorStoreIndex.from_documents(documents, urls=[
@@ -57,13 +57,13 @@ def construct_index(directory_path):
 
     return index
 
-def chatbotCustom(input):
-    storage_context = StorageContext.from_defaults(persist_dir="index.json")
-    index = load_index_from_storage(storage_context)
-    query_engine = index.as_query_engine()
-    response = query_engine.query(input)
+#def chatbotCustom(input):
+#    storage_context = StorageContext.from_defaults(persist_dir="index.json")
+#    index = load_index_from_storage(storage_context)
+#    query_engine = index.as_query_engine()
+#    response = query_engine.query(input)
 #    response = index.query(input, similarity_top_k=5, response_mode="tree_summarize")
-    return response.response
+#    return response.response
 
 def chatbotGPT(input):
     if input: