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import gradio as gr
from typing import Optional
from smolagents.agent_types import AgentAudio, AgentImage, AgentText, handle_agent_output_types
from smolagents.agents import ActionStep, MultiStepAgent
from smolagents.memory import MemoryStep
class GradioUI:
"""Simplified Gradio interface for Hugging Face Spaces"""
def __init__(self, agent: MultiStepAgent):
self.agent = agent
def launch(self):
with gr.Blocks(title="AI Assistant", theme=gr.themes.Soft()) as demo:
gr.Markdown("""
# 🤖 AI Assistant
**Capabilities:**
- Time zone conversions
- Weather lookups
- Unit conversions
- Web search
- Image generation
- Code execution
""")
chatbot = gr.Chatbot(
height=500,
avatar_images=(
None,
"https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/communication/Alfred.png",
)
)
with gr.Row():
msg = gr.Textbox(
placeholder="Ask me anything...",
container=False,
scale=7
)
submit = gr.Button("Send", scale=1)
def respond(message, chat_history):
chat_history.append((message, ""))
full_response = ""
for step_log in self.agent.run(message, stream=True):
if isinstance(step_log, ActionStep):
if hasattr(step_log, 'model_output') and step_log.model_output:
full_response += step_log.model_output + "\n"
if hasattr(step_log, 'observations') and step_log.observations:
full_response += step_log.observations + "\n"
chat_history[-1] = (message, full_response)
return "", chat_history
msg.submit(respond, [msg, chatbot], [msg, chatbot])
submit.click(respond, [msg, chatbot], [msg, chatbot])
demo.launch() |