Update app.py

app.py

@@ -7,13 +7,14 @@ from llama_index import ServiceContext, LLMPredictor, PromptHelper
 from llama_index.text_splitter import TokenTextSplitter
 from llama_index.node_parser import SimpleNodeParser
 from langchain.embeddings import HuggingFaceEmbeddings
-from llama_index import SimpleDirectoryReader, GPTVectorStoreIndex
+from llama_index import SimpleDirectoryReader, VectorStoreIndex
 from gradio import Interface
 nest_asyncio.apply()
 
 embed_model = HuggingFaceEmbeddings(
     model_name="sentence-transformers/all-mpnet-base-v2"
 )
+"""
 node_parser = SimpleNodeParser.from_defaults(text_splitter=TokenTextSplitter(chunk_size=1024, chunk_overlap=20))
 prompt_helper = PromptHelper(
   context_window=4096,
@@ -21,7 +22,7 @@ prompt_helper = PromptHelper(
   chunk_overlap_ratio=0.1,
   chunk_size_limit=None
 )
-
+"""
 from langchain_g4f import G4FLLM
 
 async def main(question):
@@ -34,12 +35,10 @@ async def main(question):
     llm = LangChainLLM(llm=llm)
     
     service_context = ServiceContext.from_defaults(llm=llm,
-  embed_model=embed_model,
-  node_parser=node_parser,
-  prompt_helper=prompt_helper)
+  embed_model=embed_model)
 
     documents = SimpleDirectoryReader("data/").load_data()
-    index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
+    index = VectorStoreIndex.from_documents(documents, service_context=service_context)
     query_engine = index.as_query_engine(service_context=service_context)
     response = query_engine.query(question)
     print(response)