Update app.py

app.py

@@ -65,14 +65,15 @@ Settings.llm = HuggingFaceInferenceAPI(model_name="mistralai/Mistral-Nemo-Instru
                              )
 
 Settings.embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-m3")
-documents = [Document(text="Indian parliament elections happened in April-May 2024. BJP Party won."),
-             Document(text="Indian parliament elections happened in April-May 2021. XYZ Party won."),
-             Document(text="Indian parliament elections happened in 2020. ABC Party won."),
-            ]
-index = VectorStoreIndex.from_documents(
-    documents,
-)
-
+#documents = [Document(text="Indian parliament elections happened in April-May 2024. BJP Party won."),
+#             Document(text="Indian parliament elections happened in April-May 2021. XYZ Party won."),
+#             Document(text="Indian parliament elections happened in 2020. ABC Party won."),
+#            ]
+#index = VectorStoreIndex.from_documents(
+#    documents,
+#)
+vector_store = ChromaVectorStore(chroma_collection=collection)
+index = VectorStoreIndex.from_vector_store(vector_store, embed_model=Settings.embed_model)
 query_engine = index.as_query_engine()
 def rag(input_text, file):
     return query_engine.query(