psql -U postgres

CREATE USER toolbox_user WITH PASSWORD 'my-password';
CREATE DATABASE toolbox_db;
GRANT ALL PRIVILEGES ON DATABASE toolbox_db TO toolbox_user;
ALTER DATABASE toolbox_db OWNER TO toolbox_user;

\c toolbox_db toolbox_user

CREATE TABLE hotels(
  id            INTEGER NOT NULL PRIMARY KEY,
  name          VARCHAR NOT NULL,
  location      VARCHAR NOT NULL,
  price_tier    VARCHAR NOT NULL,
  booked        BIT     NOT NULL
);

INSERT INTO hotels(id, name, location, price_tier, booked)
VALUES
  (1, 'Hilton Basel', 'Basel', 'Luxury', B'0'),
  (2, 'Marriott Zurich', 'Zurich', 'Upscale', B'0'),
  (3, 'Hyatt Regency Basel', 'Basel', 'Upper Upscale', B'0');

brew install mcp-toolbox

sources:
  my-pg-source:
    kind: postgres
    host: 127.0.0.1
    port: 5432
    database: toolbox_db
    user: toolbox_user
    password: my-password

tools:
  search-hotels-by-location:
    kind: postgres-sql
    source: my-pg-source
    description: 根据位置搜索酒店。
    parameters:
      - name: location
        type: string
        description: 酒店的位置。
    statement: SELECT id, name, location, price_tier FROM hotels WHERE location ILIKE '%' || $1 || '%';
  book-hotel:
    kind: postgres-sql
    source: my-pg-source
    description: >-
        通过 ID 预订酒店。如果酒店预订成功，返回确认消息。
    parameters:
      - name: hotel_id
        type: integer
        description: 要预订的酒店 ID。
    statement: UPDATE hotels SET booked = B'1' WHERE id = $1;

toolsets:
  hotel_toolset:
    - search-hotels-by-location
    - book-hotel

toolbox --tools-file "tools.yaml"

!pip install toolbox-langchain

from toolbox_langchain import ToolboxClient

with ToolboxClient("http://127.0.0.1:5000") as client:
    search_tool = await client.aload_tool("search-hotels-by-location")

from toolbox_langchain import ToolboxClient

with ToolboxClient("http://127.0.0.1:5000") as client:
    search_tool = await client.aload_tool("search-hotels-by-location")
    results = search_tool.invoke({"location": "Basel"})
    print(results)

[{"id":1,"location":"Basel","name":"Hilton Basel","price_tier":"Luxury"},{"id":3,"location":"Basel","name":"Hyatt Regency Basel","price_tier":"Upper Upscale"}]

pip install -qU toolbox-langchain langgraph langchain-google-vertexai

from langchain.agents import create_agent
from langchain_google_vertexai import ChatVertexAI
from langgraph.checkpoint.memory import MemorySaver
from toolbox_langchain import ToolboxClient


prompt = """
你是一个有用的酒店助手。你处理酒店搜索和预订。
当用户搜索酒店时，列出找到的每个酒店的完整详细信息：id、name、location 和 price_tier。
始终使用酒店 ID 进行预订操作。
对于任何预订，请提供清晰的确认消息。
不要向用户请求澄清或确认；直接执行请求的操作。
"""


async def run_queries(agent_executor):
    config = {"configurable": {"thread_id": "hotel-thread-1"}}

    # --- 查询 1：搜索酒店 ---
    query1 = "我需要在巴塞尔找一家酒店。"
    print(f'\n--- 用户: "{query1}" ---')
    inputs1 = {"messages": [("user", prompt + query1)]}
    async for event in agent_executor.astream_events(
        inputs1, config=config, version="v2"
    ):
        if event["event"] == "on_chat_model_end" and event["data"]["output"].content:
            print(f"--- 代理: ---\n{event['data']['output'].content}")

    # --- 查询 2：预订酒店 ---
    query2 = "好的，请为我预订巴塞尔凯悦酒店。"
    print(f'\n--- 用户: "{query2}" ---')
    inputs2 = {"messages": [("user", query2)]}
    async for event in agent_executor.astream_events(
        inputs2, config=config, version="v2"
    ):
        if event["event"] == "on_chat_model_end" and event["data"]["output"].content:
            print(f"--- 代理: ---\n{event['data']['output'].content}")

async def main():
    await run_hotel_agent()


async def run_hotel_agent():
    model = ChatVertexAI(model_name="gemini-2.5-flash")

    # 从运行的 MCP 工具箱服务器加载工具
    async with ToolboxClient("http://127.0.0.1:5000") as client:
        tools = await client.aload_toolset("hotel_toolset")

        agent = create_agent(model, tools, checkpointer=MemorySaver())

        await run_queries(agent)


await main()