added text streamer

app.py

@@ -1,16 +1,23 @@
-from backend import handle_query
+from backend import handle_query, build_index
 import gradio as gr
 
 
-iface = gr.ChatInterface(
-    fn=handle_query,
-    title="PDF Information and Inference",
-    description="Retrieval-Augmented Generation - Ask me anything about the content of the PDF.",
-    #examples=["What is the main topic of the document?", "Can you summarize the key points?"],
-    #cache_examples=True,
-)
+
+
+def setup_and_run():
+    # Call build_index() before starting the chat interface
+    build_index()  # This builds the index on app initialization
+
+    # Pass the index into handle_query (you can modify handle_query to accept it as an argument if needed)
+    iface = gr.ChatInterface(
+        fn=handle_query,  # Query handling remains here
+        title="PDF Information and Inference",
+        description="Retrieval-Augmented Generation - Ask me anything about the content of the PDF.",
+    )
+
+    iface.launch()
 
 
 if __name__ == "__main__":
     progress=gr.Progress(track_tqdm=True)
-    iface.launch()
+    setup_and_run()

backend.py

@@ -41,7 +41,9 @@ parser = SentenceSplitter.from_defaults(
                 chunk_size=256, chunk_overlap=64, paragraph_separator="\n\n"
             )
 
+index = None
 def build_index():
+    global index
     # Load documents from a file
     documents = SimpleDirectoryReader(input_files=["data/blockchainprova.txt"]).load_data()
     # Parse the documents into nodes
@@ -52,11 +54,9 @@ def build_index():
     return index
 
 
-index = build_index()
-
 @spaces.GPU(duration=20)
 def handle_query(query_str, chathistory):
-  
+    global index
   
     qa_prompt_str = (
         "Context information is below.\n"