| # import gradio as gr | |
| # from mcp.client.stdio import StdioServerParameters | |
| # from smolagents import InferenceClientModel, CodeAgent | |
| # from smolagents.mcp_client import MCPClient | |
| # from transformers import pipeline | |
| # from transformers import AutoModelForCausalLM, AutoTokenizer | |
| # import torch | |
| # # Initialize the MCP client correctly | |
| # try: | |
| # mcp_client = MCPClient( | |
| # ## Try this working example on the hub: | |
| # # {"url": "https://abidlabs-mcp-tools.hf.space/gradio_api/mcp/sse"} | |
| # {"url": "https://captain-awesome-alquranchapters.hf.space/gradio_api/mcp/sse"} | |
| # ) | |
| # tools = mcp_client.get_tools() | |
| # # model = InferenceClientModel() | |
| # # model = TransformersModel( | |
| # # model_id="Qwen/Qwen2.5-Coder-32B-Instruct", | |
| # # device="cuda", | |
| # # max_new_tokens=5000, | |
| # # ) | |
| # model_id = "unsloth/Llama-3.2-1B" | |
| # model = AutoModelForCausalLM.from_pretrained( | |
| # model_id, | |
| # torch_dtype=torch.bfloat16, | |
| # device_map="auto" | |
| # ) | |
| # agent = CodeAgent(tools=[*tools], model=model) | |
| # # Define Gradio ChatInterface | |
| # demo = gr.ChatInterface( | |
| # fn=lambda message, history: str(agent.run(message)), | |
| # type="messages", | |
| # title="Agent with MCP Tools", | |
| # description="This is a simple agent that uses MCP tools to get chapters of the Quran.", | |
| # ) | |
| # demo.launch(share=True) | |
| # finally: | |
| # # Properly close the MCP client connection | |
| # # if 'mcp_client' in locals(): | |
| # # mcp_client.disconnect() | |
| # mcp_client.disconnect() | |
| import gradio as gr | |
| import asyncio | |
| from smolagents.mcp_client import MCPClient | |
| from transformers import AutoModelForCausalLM | |
| import torch | |
| async def main(): | |
| mcp_client = MCPClient({"url": "https://captain-awesome-alquranchapters.hf.space/gradio_api/mcp/sse"}) | |
| await mcp_client.connect() # or use async context manager if supported | |
| tools = await mcp_client.get_tools() | |
| model_id = "unsloth/Llama-3.2-1B" | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_id, | |
| torch_dtype=torch.bfloat16, | |
| device_map="auto" | |
| ) | |
| agent = CodeAgent(tools=tools, model=model) | |
| async def gradio_fn(message, history): | |
| response = await agent.run(message) # assuming run is async | |
| return str(response) | |
| demo = gr.ChatInterface( | |
| fn=gradio_fn, | |
| type="messages", | |
| title="Agent with MCP Tools", | |
| description="This is a simple agent that uses MCP tools to get chapters of the Quran.", | |
| ) | |
| demo.launch(share=True) | |
| await mcp_client.disconnect() | |
| if __name__ == "__main__": | |
| asyncio.run(main()) |