agent-dev

[project]
name = "agent-dev"
version = "0.1.0"
description = "AI agent development environment"
requires-python = "==3.12.*"
dependencies = [
  "langchain==1.2.10",
  "langgraph==1.0.9",
  "langsmith==0.7.6",
  "pydantic==2.12.5",
  "fastapi==0.130.0",
  "uvicorn==0.41.0",
  "httpx==0.28.1",
  "openai==2.21.0",
  "tiktoken==0.12.0",
  "ipykernel==7.2.0",
  "pytest==9.0.2",
  "ruff==0.15.2",
]

[tool.uv]
package = false

uv run python -c "import langchain, langgraph, langsmith, fastapi, httpx, openai; print('langgraph', langgraph.__version__); print('fastapi', fastapi.__version__); print('openai', openai.__version__)"

from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
from langgraph.prebuilt import create_react_agent

# 1) Tool 정의
@tool
def get_weather(city: str) -> str:
    """도시의 현재 날씨를 반환합니다."""
    return f"{city}의 현재 날씨: 맑음, 22도"

@tool
def search_docs(query: str) -> str:
    """내부 문서를 검색합니다."""
    return f"'{query}'에 대한 검색 결과: 관련 문서 3건 발견"

# 2) Agent 생성
llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
agent = create_react_agent(llm, tools=[get_weather, search_docs])

# 3) Agent 실행
result = agent.invoke({"messages": [("user", "서울 날씨 알려줘")]})
print(result["messages"][-1].content)

import httpx

async def call_mcp_tool(server_url: str, tool_name: str, arguments: dict):
    async with httpx.AsyncClient() as client:
        response = await client.post(
            f"{server_url}/tools/{tool_name}",
            json={"arguments": arguments},
            timeout=30.0
        )
        return response.json()