Update app.py

app.py

@@ -311,105 +311,6 @@ chain_neo4j = (
 
 
 
-# # Define the custom template for Phi-3.5
-# phi_custom_template = """
-# <|system|>
-# You are a helpful assistant.<|end|>
-# <|user|>
-# {context}
-# {question}<|end|>
-# <|assistant|>
-# """
-# import traceback
-
-# def generate_answer(message, choice, retrieval_mode, selected_model):
-#     logging.debug(f"generate_answer called with choice: {choice}, retrieval_mode: {retrieval_mode}, and selected_model: {selected_model}")
-
-#     try:
-#         # Handle hotel-related queries
-#         if "hotel" in message.lower() or "hotels" in message.lower() and "birmingham" in message.lower():
-#             logging.debug("Handling hotel-related query")
-#             response = fetch_google_hotels()
-#             logging.debug(f"Hotel response: {response}")
-#             return response, extract_addresses(response)
-        
-#         # Handle restaurant-related queries
-#         if "restaurant" in message.lower() or "restaurants" in message.lower() and "birmingham" in message.lower():
-#             logging.debug("Handling restaurant-related query")
-#             response = fetch_yelp_restaurants()
-#             logging.debug(f"Restaurant response: {response}")
-#             return response, extract_addresses(response)
-
-#         # Handle flight-related queries
-#         if "flight" in message.lower() or "flights" in message.lower() and "birmingham" in message.lower():
-#             logging.debug("Handling flight-related query")
-#             response = fetch_google_flights()
-#             logging.debug(f"Flight response: {response}")
-#             return response, extract_addresses(response)
-
-#         # Retrieval-based response
-#         if retrieval_mode == "VDB":
-#             logging.debug("Using VDB retrieval mode")
-#             if selected_model == chat_model:
-#                 logging.debug("Selected model: GPT-4o")
-#                 retriever = gpt_retriever
-#                 prompt_template = QA_CHAIN_PROMPT_1 if choice == "Details" else QA_CHAIN_PROMPT_2
-#                 context = retriever.get_relevant_documents(message)
-#                 logging.debug(f"Retrieved context: {context}")
-
-#                 prompt = prompt_template.format(context=context, question=message)
-#                 logging.debug(f"Generated prompt: {prompt}")
-
-#                 qa_chain = RetrievalQA.from_chain_type(
-#                     llm=chat_model,
-#                     chain_type="stuff",
-#                     retriever=retriever,
-#                     chain_type_kwargs={"prompt": prompt_template}
-#                 )
-#                 response = qa_chain({"query": message})
-#                 logging.debug(f"GPT-4o response: {response}")
-#                 return response['result'], extract_addresses(response['result'])
-
-#             elif selected_model == phi_pipe:
-#                 logging.debug("Selected model: Phi-3.5")
-#                 retriever = phi_retriever
-#                 context_documents = retriever.get_relevant_documents(message)
-#                 context = "\n".join([doc.page_content for doc in context_documents])
-#                 logging.debug(f"Retrieved context for Phi-3.5: {context}")
-
-#                 # Use the correct template variable
-#                 prompt = phi_custom_template.format(context=context, question=message)
-#                 logging.debug(f"Generated Phi-3.5 prompt: {prompt}")
-
-#                 response = selected_model(prompt, **{
-#                     "max_new_tokens": 160,  # Increased to handle longer responses
-#                     "return_full_text": True,
-#                     "temperature": 0.7,  # Adjusted to avoid cutting off
-#                     "do_sample": True,   # Allow sampling to increase response diversity
-#                 })
-
-#                 if response:
-#                     generated_text = response[0]['generated_text']
-#                     logging.debug(f"Phi-3.5 Response: {generated_text}")
-#                     cleaned_response = clean_response(generated_text)
-#                     return cleaned_response, extract_addresses(cleaned_response)
-#                 else:
-#                     logging.error("Phi-3.5 did not return any response.")
-#                     return "No response generated.", []
-
-#         elif retrieval_mode == "KGF":
-#             logging.debug("Using KGF retrieval mode")
-#             response = chain_neo4j.invoke({"question": message})
-#             logging.debug(f"KGF response: {response}")
-#             return response, extract_addresses(response)
-#         else:
-#             logging.error("Invalid retrieval mode selected.")
-#             return "Invalid retrieval mode selected.", []
-
-#     except Exception as e:
-#         logging.error(f"Error in generate_answer: {str(e)}")
-#         logging.error(traceback.format_exc())
-#         return "Sorry, I encountered an error while processing your request.", []
 
 
 
@@ -481,6 +382,11 @@ import traceback
 def generate_answer(message, choice, retrieval_mode, selected_model):
     logging.debug(f"generate_answer called with choice: {choice}, retrieval_mode: {retrieval_mode}, and selected_model: {selected_model}")
 
+    # Logic for disabling options for Phi-3.5
+    if selected_model == "Phi-3.5":
+        choice = None
+        retrieval_mode = None
+
     try:
         # Handle hotel-related queries
         if "hotel" in message.lower() or "hotels" in message.lower() and "birmingham" in message.lower():
@@ -567,6 +473,13 @@ def generate_answer(message, choice, retrieval_mode, selected_model):
         logging.error(traceback.format_exc())
         return "Sorry, I encountered an error while processing your request.", []
 
+def handle_retrieval_mode_change(selected_model):
+    if selected_model == "Phi-3.5":
+        # Disable retrieval mode and select style when Phi-3.5 is selected
+        return gr.update(interactive=False), gr.update(interactive=False)
+    else:
+        # Enable retrieval mode and select style for other models
+        return gr.update(interactive=True), gr.update(interactive=True)
 
 
 
@@ -1222,6 +1135,11 @@ with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
             choice = gr.Radio(label="Select Style", choices=["Details", "Conversational"], value="Conversational")
             retrieval_mode = gr.Radio(label="Retrieval Mode", choices=["VDB", "KGF"], value="VDB")
             model_choice = gr.Dropdown(label="Choose Model", choices=["GPT-4o", "Phi-3.5"], value="GPT-4o")
+            
+            
+            # Link the dropdown change to handle_retrieval_mode_change
+            model_choice.change(fn=handle_retrieval_mode_change, inputs=model_choice, outputs=[retrieval_mode, choice])
+
 
             gr.Markdown("<h1 style='color: red;'>Talk to RADAR</h1>", elem_id="voice-markdown")
 
@@ -1260,7 +1178,9 @@ with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
             audio_input = gr.Audio(sources=["microphone"], streaming=True, type='numpy', every=0.1)
             audio_input.stream(transcribe_function, inputs=[state, audio_input], outputs=[state, chat_input], api_name="voice_query_to_text")
 
-            retrieval_mode.change(fn=handle_retrieval_mode_change, inputs=retrieval_mode, outputs=[choice, choice])
+            # retrieval_mode.change(fn=handle_retrieval_mode_change, inputs=retrieval_mode, outputs=[choice, choice])
+             model_choice.change(fn=handle_retrieval_mode_change, inputs=model_choice, outputs=[choice, retrieval_mode])
+
 
         # with gr.Column():
         #     weather_output = gr.HTML(value=fetch_local_weather())