Spaces:
Sleeping
Sleeping
File size: 1,974 Bytes
7da81aa 9fc0224 7da81aa |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
from smolagents import CodeAgent, InferenceClientModel, MCPClient
from mcp import StdioServerParameters
import os
def create_agent_with_mcp():
# Path to server
server_path = os.path.join(os.path.dirname(__file__), "mcp_server.py")
# Parameters
params = StdioServerParameters(
command="python",
args=[server_path],
env=os.environ.copy()
)
# Initialize Client
# We create the client but need to manage its lifecycle.
# For a simple demo script or Gradio app, we can keep the client content_manager logic in the caller
# OR just instantiate it and manualy disconnect later.
client = MCPClient(params, structured_output=True)
# The tools are now available in client.get_tools()
# Note: connect() is called inside __init__ of MCPClient
mcp_tools = client.get_tools()
print(f"Debug: mcp_tools type: {type(mcp_tools)}")
if mcp_tools:
print(f"Debug: first tool type: {type(mcp_tools[0])}")
print(f"Debug: mcp_tools: {mcp_tools}")
# Using InferenceClientModel with Llama 4 Scout
model = InferenceClientModel(
model_id="meta-llama/Llama-4-Scout-17B-16E-Instruct",
)
agent = CodeAgent(
tools=mcp_tools,
model=model,
max_steps=5, # Limit steps to avoid excessive token usage
)
return agent, client
if __name__ == "__main__":
try:
agent, client = create_agent_with_mcp()
tools_list = agent.tools.values() if isinstance(agent.tools, dict) else agent.tools
print("Agent created with tools:", [t.name for t in tools_list])
# Test run
print("Running agent test...")
response = agent.run("Please authenticate with 'open sesame' and then read the treasure.")
print("Agent Response:", response)
except Exception as e:
print(f"An error occurred: {e}")
finally:
if 'client' in locals():
client.disconnect()
|