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import gradio as gr
import os
from smolagents import InferenceClientModel, CodeAgent, ToolCollection, MCPClient
# Function to initialize MCP client and agent
def initialize_agent(api_key, model_name):
try:
# Initialize MCP client with explicit transport key
mcp_client = MCPClient(
{
"url": "https://wd101-oneservertorulethemall.hf.space/gradio_api/mcp/sse",
"transport": "sse" # Explicitly specify transport to avoid FutureWarning
}
)
tools = mcp_client.get_tools()
# Initialize model with API key
if not api_key:
return None, None, "Please provide a valid API key."
# Map model names to InferenceClientModel configurations
model_configs = {
"Qwen": "Qwen/Qwen2-72B-Instruct", # Example model ID
"Gemma": "google/gemma-2-27b-it", # Example model ID
"Llama": "meta-llama/Llama-3-8b" # Example model ID
}
model = InferenceClientModel(
provider='nebius',
token=api_key,
model=model_configs.get(model_name, "google/gemma-2-27b-it") # Default to Qwen
)
agent = CodeAgent(tools=[*tools], model=model)
return mcp_client, agent, None
except Exception as e:
return None, None, f"Failed to initialize agent: {str(e)}"
# Function to handle chatbot interaction
def chatbot_function(user_message, chat_history, api_key, model_name):
# Initialize MCP client and agent
mcp_client, agent, error = initialize_agent(api_key, model_name)
if error:
chat_history.append((user_message, error))
if mcp_client:
mcp_client.disconnect()
return chat_history, ""
try:
# Process user message with the agent
if not user_message:
response = "Please enter a message."
else:
response = str(agent.run(user_message))
chat_history.append((user_message, response))
except Exception as e:
chat_history.append((user_message, f"Error processing message: {str(e)}"))
finally:
if mcp_client:
mcp_client.disconnect()
return chat_history, ""
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Hackathon Chatbot with MCP Tools")
gr.Markdown("Enter your API key (e.g., Hugging Face token), select a model, and start chatting!")
# API key input and model selection
with gr.Row():
api_key_input = gr.Textbox(label="API Key", type="password", placeholder="Enter your API key here")
model_dropdown = gr.Dropdown(
choices=["Qwen", "Gemma", "Llama"],
label="Select Model",
value="Gemma"
)
# Chatbot interface
chatbot = gr.Chatbot(label="Chat History")
user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...")
submit_button = gr.Button("Send")
# State to store chat history
chat_history = gr.State([])
# Connect the submit button to the chatbot function
submit_button.click(
fn=chatbot_function,
inputs=[user_input, chat_history, api_key_input, model_dropdown],
outputs=[chatbot, user_input]
)
# Launch the Gradio app
demo.launch() |