实现分布式追踪

有时，你需要跨多个服务追踪一个请求。

LangSmith 开箱即用地支持分布式追踪，通过上下文传播标头（langsmith-trace 和可选的 baggage 用于元数据/标签）在服务之间链接追踪中的运行。

客户端-服务器设置示例

• 追踪在客户端开始
• 在服务器上继续

Python 中的分布式追踪

# client.py
from langsmith.run_helpers import get_current_run_tree, traceable
import httpx

@traceable
async def my_client_function():
    headers = {}
    async with httpx.AsyncClient(base_url="...") as client:
        if run_tree := get_current_run_tree():
            # add langsmith-id to headers
            headers.update(run_tree.to_headers())
        return await client.post("/my-route", headers=headers)

然后，服务器（或其他服务）可以通过适当处理标头来继续追踪。如果你正在使用 asgi 应用 Starlette 或 FastAPI，你可以使用 LangSmith 的 TracingMiddleware 连接分布式追踪。

信息

TracingMiddleware 类在 langsmith==0.1.133 中添加。

使用 FastAPI 的示例

from langsmith import traceable
from langsmith.middleware import TracingMiddleware
from fastapi import FastAPI, Request


app = FastAPI()  # Or Flask, Django, or any other framework
app.add_middleware(TracingMiddleware)

@traceable
async def some_function():
    ...

@app.post("/my-route")
async def fake_route(request: Request):
  return await some_function()

或者在 Starlette 中

from starlette.applications import Starlette
from starlette.middleware import Middleware
from langsmith.middleware import TracingMiddleware

routes = ...

middleware = [
    Middleware(TracingMiddleware),
]

app = Starlette(..., middleware=middleware)

如果你正在使用其他服务器框架，你始终可以通过 langsmith_extra 传入标头来“接收”分布式追踪

# server.py
from langsmith import traceable
from langsmith.run_helpers import tracing_context
from fastapi import FastAPI, Request


@traceable
async def my_application():
    ...


app = FastAPI()  # Or Flask, Django, or any other framework


@app.post("/my-route")
async def fake_route(request: Request):
    # request.headers:  {"langsmith-trace": "..."}
    # as well as optional metadata/tags in `baggage`
    with tracing_context(parent=request.headers):
        return await my_application()

上面的示例使用了 tracing_context 上下文管理器。你也可以在用 @traceable 包装的方法的 langsmith_extra 参数中直接指定父运行上下文。

from langsmith.run_helpers import traceable, trace
# ... same as above
@app.post("/my-route")
async def fake_route(request: Request):
    # request.headers:  {"langsmith-trace": "..."}
    my_application(langsmith_extra={"parent": request.headers})

TypeScript 中的分布式追踪

注意

TypeScript 中的分布式追踪需要 langsmith 版本 >=0.1.31

首先，我们从客户端获取当前的运行树，并将其转换为 langsmith-trace 和 baggage 标头值，我们可以将其传递给服务器

// client.mts
import { getCurrentRunTree, traceable } from "langsmith/traceable";

const client = traceable(
  async () => {
    const runTree = getCurrentRunTree();
    return await fetch("...", {
      method: "POST",
      headers: runTree.toHeaders(),
    }).then((a) => a.text());
  },
  { name: "client" }
);

await client();

然后，服务器将标头转换回运行树，并使用它来进一步继续追踪。

要将新创建的运行树传递给可追踪的函数，我们可以使用 withRunTree 助手，这将确保运行树在可追踪的调用中传播。

Express.JS

// server.mts
import { RunTree } from "langsmith";
import { traceable, withRunTree } from "langsmith/traceable";

import express from "express";
import bodyParser from "body-parser";

const server = traceable(
  (text: string) => `Hello from the server! Received "${text}"`,
  { name: "server" }
);

const app = express();

app.use(bodyParser.text());

app.post("/", async (req, res) => {
  const runTree = RunTree.fromHeaders(req.headers);
  const result = await withRunTree(runTree, () => server(req.body));
  res.send(result);
});

Hono

// server.mts
import { RunTree } from "langsmith";
import { traceable, withRunTree } from "langsmith/traceable";

import { Hono } from "hono";

const server = traceable(
  (text: string) => `Hello from the server! Received "${text}"`,
  { name: "server" }
);

const app = new Hono();

app.post("/", async (c) => {
  const body = await c.req.text();
  const runTree = RunTree.fromHeaders(c.req.raw.headers);
  const result = await withRunTree(runTree, () => server(body));
  return c.body(result);
});