Create app.py

app.py

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+import gradio as gr
+from smolagents import CodeAgent, HfApiModel, Tool
+
+# Define a simple tool (e.g., a text generator from a Hugging Face Space)
+image_generation_tool = Tool.from_space(
+    "black-forest-labs/FLUX.1-schnell",  # Example Space ID
+    name="image_generator",
+    description="Generate an image from a text prompt."
+)
+
+# Initialize the model (using a Hugging Face API model as an example)
+model = HfApiModel("Qwen/Qwen2.5-Coder-32B-Instruct")  # Replace with your preferred model
+
+# Create the Smol Agent with the tool
+agent = CodeAgent(tools=[image_generation_tool], model=model)
+
+# Define the chatbot function
+def chat_with_agent(user_input, history):
+    # History is a list of [user, assistant] pairs; we'll append to it
+    if history is None:
+        history = []
+    
+    # Run the agent with the user's input
+    response = agent.run(user_input)
+    
+    # Append the new interaction to the history
+    history.append([user_input, response])
+    return history, ""  # Return updated history and clear input box
+
+# Create the Gradio interface
+with gr.Blocks(title="Smol Agent Chatbot") as demo:
+    gr.Markdown("# Chat with a Smol Agent")
+    gr.Markdown("Ask anything, and the agent will respond—maybe even generate an image!")
+    
+    # Chatbot component to display conversation
+    chatbot = gr.Chatbot()
+    
+    # Textbox for user input
+    user_input = gr.Textbox(placeholder="Type your message here...", label="Your Message")
+    
+    # Submit button
+    submit_btn = gr.Button("Send")
+    
+    # Connect the components: when the button is clicked, run the chat function
+    submit_btn.click(
+        fn=chat_with_agent,
+        inputs=[user_input, chatbot],
+        outputs=[chatbot, user_input]
+    )
+
+# Launch the app
+demo.launch()