app.py

import gradio as gr
from smolagents import Agent  # adjust the import to your actual smolagents module

# Step 1: Initialize your smolagents agent.
# Replace "zephyr-7b-beta" with your desired model name/configuration.
agent = Agent(model="zephyr-7b-beta")  

def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p):
    """
    This function builds the conversation history, calls the smolagents agent,
    and streams the response back to Gradio.
    """
    # Build the conversation messages list, starting with the system prompt.
    messages = [{"role": "system", "content": system_message}]
    for user_msg, assistant_msg in history:
        if user_msg:
            messages.append({"role": "user", "content": user_msg})
        if assistant_msg:
            messages.append({"role": "assistant", "content": assistant_msg})
    # Add the latest user input.
    messages.append({"role": "user", "content": message})
    
    # Initialize an empty response.
    complete_response = ""
    
    # Step 2: Call the agent's chat_completion method.
    # If your smolagents agent supports streaming (i.e. yielding tokens as they are generated),
    # this loop will yield partial responses to update the UI.
    # If streaming is not supported, you can simply do:
    #   complete_response = agent.chat_completion(messages, max_tokens, temperature, top_p)
    #   yield complete_response
    for token in agent.chat_completion(
        messages,
        max_tokens=max_tokens,
        temperature=temperature,
        top_p=top_p,
        stream=True  # set to False if your agent does not support streaming
    ):
        complete_response += token
        yield complete_response

# Step 3: Create the Gradio ChatInterface.
demo = gr.ChatInterface(
    fn=respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)"
        ),
    ],
)

# Step 4: Launch the Gradio app.
if __name__ == "__main__":
    demo.launch()