import os
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
from dotenv import load_dotenv
load_dotenv()
def get_chat_model() -> ChatOpenAI:
"""Initialize and return a ChatOpenAI model from environment settings."""
return ChatOpenAI(
model=os.environ.get("MODEL_NAME"),
base_url=os.environ["BASE_URL"],
api_key=os.environ["OPENAI_API_KEY"],
temperature=0.7,
)
async def run_e2e_test_with_client(client: MultiServerMCPClient, expected_tools: list[str], test_prompts: list[tuple[str, str]]) -> None:
"""Run an end-to-end test using a connected MCP client and validate tool behavior."""
tools = client.get_tools()
tool_names = [tool.name for tool in tools]
print(f"🔧 Tools list: {tool_names}")
for tool in expected_tools:
assert tool in tool_names, f"Expected '{tool}' tool to be available"
agent = create_react_agent(get_chat_model(), tools)
for question, expected_answer in test_prompts:
response = await agent.ainvoke({"messages": question})
for m in response['messages']:
m.pretty_print()
assert any(expected_answer.lower() in m.content.lower() for m in response["messages"]), \
f"Expected answer to include '{expected_answer}'"
