Update app.py

app.py

@@ -24,6 +24,15 @@ backend = Backend()
 
 cv2.setNumThreads(1)
 
+def load_topic_data(topic):
+    if topic:
+        query_engine = backend.create_index_for_query_engine(documents_paths[topic])
+        gr.Info(f"Data loaded for {topic} topic")
+        return query_engine
+    else:
+        gr.Warning("No topic selected. Please select a topic first.")
+        return None
+
 @spaces.GPU(duration=20)
 def respond(
     message,
@@ -35,28 +44,21 @@ def respond(
     top_p,
     top_k,
     repeat_penalty,
-    selected_topic
+    query_engine
 ):
     chat_template = MessagesFormatterType.GEMMA_2
 
-    print("HISTORY SO FAR ", history)
-    print("Selected topic:", selected_topic)
+    if query_engine is None:
+        return history + [[message, "Please select a topic before asking questions."]]
 
-    if selected_topic:
-        query_engine = backend.create_index_for_query_engine(documents_paths[selected_topic])
-        message = backend.generate_prompt(query_engine, message)
-        gr.Info(f"Relevant context indexed from {selected_topic} docs...")
-    else:
-        query_engine = backend.load_index_for_query_engine()
-        message = backend.generate_prompt(query_engine, message)
-        gr.Info("Relevant context extracted from db...")
+    full_prompt = backend.generate_prompt(query_engine, message)
 
     # Load model only if it's not already loaded or if a new model is selected
     if backend.llm is None or backend.llm_model != model:
         try:
             backend.load_model(model)
         except Exception as e:
-            return f"Error loading model: {str(e)}"
+            return history + [[message, f"Error loading model: {str(e)}"]]
 
     provider = LlamaCppPythonProvider(backend.llm)
 
@@ -84,7 +86,7 @@ def respond(
 
     try:
         stream = agent.get_chat_response(
-            message, 
+            full_prompt, 
             llm_sampling_settings=settings,
             chat_history=messages,
             returns_streaming_generator=True,
@@ -99,7 +101,16 @@ def respond(
         yield history + [[message, f"Error during response generation: {str(e)}"]]
 
 def select_topic(topic):
-    return gr.update(visible=True), topic, gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False)
+    query_engine = load_topic_data(topic)
+    return (
+        gr.update(interactive=True),  # Enable the chat input
+        gr.update(interactive=True),  # Enable the submit button
+        gr.update(visible=True),      # Make the chatbot visible
+        gr.update(interactive=False), # Disable blockchain button
+        gr.update(interactive=False), # Disable metaverse button
+        gr.update(interactive=False), # Disable payment button
+        query_engine                  # Return the loaded query engine
+    )
 
 with gr.Blocks(css="""
     .gradio-container {
@@ -114,7 +125,7 @@ with gr.Blocks(css="""
         metaverse_btn = gr.Button("🌐 Metaverse", scale=1)
         payment_btn = gr.Button("💳 Payment", scale=1)
 
-    selected_topic = gr.State(value="")
+    query_engine = gr.State(None)
 
     chatbot = gr.Chatbot(
         scale=1,
@@ -129,8 +140,9 @@ with gr.Blocks(css="""
             show_label=False,
             placeholder="Inserisci il tuo messaggio...",
             container=False,
+            interactive=False
         )
-        submit_btn = gr.Button("Invia", scale=1)
+        submit_btn = gr.Button("Invia", scale=1, interactive=False)
 
     with gr.Accordion("Advanced Options", open=False):
         model = gr.Dropdown([
@@ -156,19 +168,19 @@ with gr.Blocks(css="""
         top_k = gr.Slider(minimum=0, maximum=100, value=30, step=1, label="Top-k")
         repeat_penalty = gr.Slider(minimum=0.0, maximum=2.0, value=1.1, step=0.1, label="Repetition penalty")
 
-    blockchain_btn.click(lambda: select_topic("blockchain"), inputs=None, outputs=[chatbot, selected_topic, blockchain_btn, metaverse_btn, payment_btn])
-    metaverse_btn.click(lambda: select_topic("metaverse"), inputs=None, outputs=[chatbot, selected_topic, blockchain_btn, metaverse_btn, payment_btn])
-    payment_btn.click(lambda: select_topic("payment"), inputs=None, outputs=[chatbot, selected_topic, blockchain_btn, metaverse_btn, payment_btn])
+    blockchain_btn.click(lambda: select_topic("blockchain"), inputs=None, outputs=[msg, submit_btn, chatbot, blockchain_btn, metaverse_btn, payment_btn, query_engine])
+    metaverse_btn.click(lambda: select_topic("metaverse"), inputs=None, outputs=[msg, submit_btn, chatbot, blockchain_btn, metaverse_btn, payment_btn, query_engine])
+    payment_btn.click(lambda: select_topic("payment"), inputs=None, outputs=[msg, submit_btn, chatbot, blockchain_btn, metaverse_btn, payment_btn, query_engine])
 
     submit_btn.click(
         respond,
-        inputs=[msg, chatbot, model, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty, selected_topic],
+        inputs=[msg, chatbot, model, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty, query_engine],
         outputs=chatbot
     )
 
     msg.submit(
         respond,
-        inputs=[msg, chatbot, model, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty, selected_topic],
+        inputs=[msg, chatbot, model, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty, query_engine],
         outputs=chatbot
     )