app.py

import gradio as gr
from smolagents import CodeAgent, HfApiModel  # adjust the import to your actual smolagents module

# Step 1: Set up your smolagents agent.
def create_agent():
    """
    Initialize and return the agent.
    Adjust parameters like model type or configuration as needed.
    """
    # For example, we initialize a CodeAgent with a sample model.
    agent = CodeAgent(
        tools=[], 
        model=HfApiModel(model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud/')
    )
    return agent

# Create the agent instance once so that it persists across user interactions.
agent = create_agent()

def combine_messages(messages: list[dict]) -> str:
    """
    Helper function to combine a list of message dictionaries into a single string.
    Each message is prefixed with its role.
    """
    conversation = ""
    for msg in messages:
        # Capitalize the role (e.g., 'User' instead of 'user') for clarity.
        conversation += f"{msg['role'].capitalize()}: {msg['content']}\n"
    return conversation.strip()

def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p):
    """
    Build the conversation history, combine messages into a single string prompt,
    call the smolagents agent, and stream 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})
    
    # Combine the list of messages into a single string prompt.
    prompt = combine_messages(messages)
    
    # Now call the agent with the prompt.
    complete_response = agent.run(prompt)
    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()