Update app.py

app.py

@@ -11,7 +11,6 @@ client = OpenAI(
 )
 print("OpenAI client initialized.")
 
-
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -23,44 +22,27 @@ def respond(
     seed,
     custom_model
 ):
-
     print(f"Received message: {message}")
     print(f"History: {history}")
     print(f"System message: {system_message}")
-    print(f"Max tokens: {max_tokens}, Temperature: {temperature}, Top-P: {top_p}")
-    print(f"Frequency Penalty: {frequency_penalty}, Seed: {seed}")
-    print(f"Selected model (custom_model): {custom_model}")
-
-    # Convert seed to None if -1 (meaning random)
+    
     if seed == -1:
         seed = None
-
+    
     messages = [{"role": "system", "content": system_message}]
-    print("Initial messages array constructed.")
-
-    # Add conversation history to the context
+    
     for val in history:
-        user_part = val[0]
-        assistant_part = val[1]
-        if user_part:
-            messages.append({"role": "user", "content": user_part})
-            print(f"Added user message to context: {user_part}")
-        if assistant_part:
-            messages.append({"role": "assistant", "content": assistant_part})
-            print(f"Added assistant message to context: {assistant_part}")
-
-    # Append the latest user message
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+    
     messages.append({"role": "user", "content": message})
-    print("Latest user message appended.")
-
-    # If user provided a model, use that; otherwise, fall back to a default model
+    
     model_to_use = custom_model.strip() if custom_model.strip() != "" else "meta-llama/Llama-3.1-8B-Instruct"
-    print(f"Model selected for inference: {model_to_use}")
-
-    # Start with an empty string to build the response as tokens stream in
+    
     response = ""
-    print("Sending request to OpenAI API.")
-
+    
     for message_chunk in client.chat.completions.create(
         model=model_to_use,
         max_tokens=max_tokens,
@@ -72,75 +54,24 @@ def respond(
         messages=messages,
     ):
         token_text = message_chunk.choices[0].delta.content
-        print(f"Received token: {token_text}")
         response += token_text
         yield response
 
-    print("Completed response generation.")
-
-# GRADIO UI
-
 chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="ChatGPT is initializing...", likeable=True, layout="panel")
-print("Chatbot interface created.")
 
 system_message_box = gr.Label(value="You can select Max Tokens, Temperature, Top-P, Seed")
 
-max_tokens_slider = gr.Slider(
-    minimum=1024,
-    maximum=2048,
-    value=1024,
-    step=100,
-    label="Max new tokens"
-)
-temperature_slider = gr.Slider(
-    minimum=0.1,
-    maximum=1.0,
-    value=0.7,
-    step=0.1,
-    label="Temperature"
-)
-top_p_slider = gr.Slider(
-    minimum=0.1,
-    maximum=1.0,
-    value=0.95,
-    step=0.05,
-    label="Top-P"
-)
-frequency_penalty_slider = gr.Slider(
-    minimum=-2.0,
-    maximum=2.0,
-    value=0.0,
-    step=0.1,
-    label="Frequency Penalty"
-)
-seed_slider = gr.Slider(
-    minimum=-1,
-    maximum=65535,
-    value=-1,
-    step=1,
-    label="Seed (-1 for random)"
-)
+max_tokens_slider = gr.Slider(1024, 2048, value=1024, step=100, label="Max new tokens")
+temperature_slider = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Temperature")
+top_p_slider = gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-P")
+frequency_penalty_slider = gr.Slider(-2.0, 2.0, value=0.0, step=0.1, label="Frequency Penalty")
+seed_slider = gr.Slider(-1, 65535, value=-1, step=1, label="Seed (-1 for random)")
 
-# The custom_model_box is what the respond function sees as "custom_model"
-custom_model_box = gr.Textbox(
-     value="meta-llama/Llama-3.2-3B-Instruct",
-     label="AI Mode is ",
-    # info="(Optional) Provide a custom Hugging Face model path. Overrides any selected featured model.",
-    # info="meta-llama/Llama-3.2-3B-Instruct"
-)
-
-def set_custom_model_from_radio(selected):
-    """
-    This function will get triggered whenever someone picks a model from the 'Featured Models' radio.
-    We will update the Custom Model text box with that selection automatically.
-    """
-    print(f"Featured model selected: {selected}")
-    return selected
+custom_model_box = gr.Textbox(value="meta-llama/Llama-3.2-3B-Instruct", label="AI Mode is ")
 
 demo = gr.ChatInterface(
     fn=respond,
     additional_inputs=[
-        
         system_message_box,
         max_tokens_slider,
         temperature_slider,
@@ -148,49 +79,13 @@ demo = gr.ChatInterface(
         frequency_penalty_slider,
         seed_slider,
         custom_model_box,
-       
     ],
     fill_height=True,
     chatbot=chatbot,
     theme="Nymbo/Nymbo_Theme",
 )
-print("Chat Interface object created.")
-
-with demo:
-    with gr.Accordion("", open=False):
-        
-        print("")
-
-        models_list = [
-                  
-           
-        ]
-#     print("")
-        featured_model_radio = gr.Radio(
-            value="meta-llama/Llama-3.2-3B-Instruct",
-            interactive=True
-        )
-        
-#        print("Featured models radio button created.")
-
-        def filter_models(search_term):
-            print(f"Filtering models with search term: {search_term}")
-            filtered = [m for m in models_list if search_term.lower() in m.lower()]
-            print(f"Filtered models: {filtered}")
-            return gr.update(choices=filtered)
-
-       
-#        print("Model search box change event linked.")
-
-        featured_model_radio.change(
-            fn=set_custom_model_from_radio,
-            inputs=featured_model_radio,
-            outputs=custom_model_box
-        )
-#       print("Featured model radio button change event linked.")
-
-#        print("Gradio interface initialized.")
 
 if __name__ == "__main__":
-    print("Launching the ChatGPT-Llama.....")
+    print("Launching the ChatGPT-Llama...")
     demo.launch()
+