Update app.py

app.py

@@ -1,5 +1,8 @@
 from llama_index.core import SimpleDirectoryReader, GPTListIndex, GPTVectorStoreIndex, PromptHelper
-from llama_index.core import StorageContext, load_index_from_storage
+from llama_index.core import StorageContext, load_index_from_storage, get_response_synthesizer
+from llama_index.core.retrievers import VectorIndexRetriever
+from llama_index.core.query_engine import RetrieverQueryEngine
+from llama_index.core.postprocessor import SimilarityPostprocessor
 #from llama_index import LLMPredictor, PromptHelper
 #from langchain.chat_models import ChatOpenAI
 from langchain_community.embeddings import OpenAIEmbeddings
@@ -63,9 +66,26 @@ def construct_index(directory_path):
 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, similarity_top_k=5, response_mode="tree_summarize")
-#    response = index.query(input, similarity_top_k=5, response_mode="tree_summarize")
+#    query_engine = index.as_query_engine()
+#    response = query_engine.query(input, similarity_top_k=5, response_mode="tree_summarize")
+##    response = index.query(input, similarity_top_k=5, response_mode="tree_summarize")
+# configure retriever
+    retriever = VectorIndexRetriever(
+        index=index,
+        similarity_top_k=10,
+    )
+
+# configure response synthesizer
+    response_synthesizer = get_response_synthesizer()
+
+# assemble query engine
+    query_engine = RetrieverQueryEngine(
+        retriever=retriever,
+        response_synthesizer=response_synthesizer,
+        node_postprocessors=[SimilarityPostprocessor(similarity_cutoff=0.7)],
+    )
+
+    response = query_engine.query(input, response_mode="tree_summarize")        
     return response.response
 
 #def chatbotGPT(input):