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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()
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