phoenix/litellm-mirror
0
0
Fork 1
mirror of https://github.com/BerriAI/litellm.git synced 2025-04-27 03:34:10 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

call_openai_tool on MCP client

Browse source
This commit is contained in:
Ishaan Jaff 2025-03-21 14:36:32 -07:00
parent 1f3aa82095
commit 147787b9e0
2 changed files with 90 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

41
tests/mcp_tests/test_mcp_litellm_client.py
View file

@ -10,7 +10,11 @@ sys.path.insert(
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
import os
from litellm.mcp_client.tools import load_mcp_tools
from litellm.mcp_client.tools import (
load_mcp_tools,
transform_openai_tool_to_mcp_tool,
call_openai_tool,
)
import litellm
import pytest
import json
@ -34,11 +38,12 @@ async def test_mcp_agent():
print("MCP TOOLS: ", tools)
# Create and run the agent
messages = [{"role": "user", "content": "what's (3 + 5)"}]
print(os.getenv("OPENAI_API_KEY"))
llm_response = await litellm.acompletion(
model="gpt-4o",
api_key=os.getenv("OPENAI_API_KEY"),
messages=[{"role": "user", "content": "what's (3 + 5) x 12?"}],
messages=messages,
tools=tools,
)
print("LLM RESPONSE: ", json.dumps(llm_response, indent=4, default=str))
@ -51,3 +56,35 @@ async def test_mcp_agent():
]
== "add"
)
openai_tool = llm_response["choices"][0]["message"]["tool_calls"][0]
# Convert the OpenAI tool to an MCP tool
mcp_tool = transform_openai_tool_to_mcp_tool(openai_tool)
print("MCP TOOL: ", mcp_tool)
# Call the tool using MCP client
call_result = await call_openai_tool(
session=session,
openai_tool=openai_tool,
)
print("CALL RESULT: ", call_result)
# send the tool result to the LLM
messages.append(llm_response["choices"][0]["message"])
messages.append(
{
"role": "tool",
"content": str(call_result.content[0].text),
"tool_call_id": openai_tool["id"],
}
)
print("final messages: ", messages)
llm_response = await litellm.acompletion(
model="gpt-4o",
api_key=os.getenv("OPENAI_API_KEY"),
messages=messages,
tools=tools,
)
print(
"FINAL LLM RESPONSE: ", json.dumps(llm_response, indent=4, default=str)
)