LangSmith

Trace AI SDK calls into LangSmith with the wrapAISDK helper.

LangSmith is LangChain's observability and eval platform. If you are already in the LangChain or LangGraph ecosystem, LangSmith is the natural pairing: traces, datasets, prompt versioning, and LLM-as-judge evals share state with the rest of the LangChain stack.

This page covers the AI SDK path. If you use @assistant-ui/react-langgraph, tracing flows through LangGraph Cloud automatically; you only need this guide when your route handler talks to AI SDK directly.

How it works

LangSmith provides a wrapper around the ai namespace. You call wrapAISDK(ai), get back the same exports (generateText, streamText, generateObject, streamObject), and use those in place of the originals. Every call is then traced.

your route  ──►  wrapped streamText  ──►  LangSmith client  ──►  LangSmith

Setup

Get LangSmith credentials

.env.local

LANGSMITH_TRACING=true
LANGSMITH_API_KEY=lsv2_pt_...
LANGSMITH_PROJECT=assistant-ui

LANGSMITH_PROJECT controls which project receives traces; the default project applies if you omit it. See LangSmith's environment variable reference for the full list.

Install the LangSmith SDK

npm install langsmith

Wrap the AI SDK

wrapAISDK re-exports generateText, streamText, generateObject, and streamObject with tracing enabled. Use the wrapped versions in your route.

app/api/chat/route.ts

import * as ai from "ai";
import { wrapAISDK } from "langsmith/experimental/vercel";
import { openai } from "@ai-sdk/openai";
import type { UIMessage } from "ai";

const { streamText } = wrapAISDK(ai);

export async function POST(req: Request) {
  const { messages }: { messages: UIMessage[] } = await req.json();

  const result = streamText({
    model: openai("gpt-4o"),
    messages: await ai.convertToModelMessages(messages),
  });

  return result.toUIMessageStreamResponse();
}

convertToModelMessages is not part of the wrapper, so import it from ai directly.

Add metadata for grouping (optional)

Pass a langsmith provider option to tag traces with user, session, or run identifiers. Use createLangSmithProviderOptions to build the value:

import { createLangSmithProviderOptions } from "langsmith/experimental/vercel";

const result = streamText({
  model: openai("gpt-4o"),
  messages: await ai.convertToModelMessages(messages),
  providerOptions: {
    langsmith: createLangSmithProviderOptions({
      name: "chat-completion",
      metadata: { userId, threadId },
    }),
  },
});

name becomes the run name in LangSmith. Traces filter by the metadata fields you pass; resolve userId and threadId from your auth and thread state, don't ship literal strings.

Run and verify

Send a message. The trace should appear in your LangSmith project within seconds. Confirm:

A new run named according to name (or the default streamText).
Inputs (messages), outputs (completion), token usage, and latency are populated.
Metadata fields appear as filters.

Notes

Serverless flush. Serverless functions exit before LangSmith flushes batched traces. Before returning, force the flush with the Client from langsmith:
```
import { Client } from "langsmith";
const client = new Client();
// ...inside your route handler, after streamText:
await client.awaitPendingTraceBatches();
```
Without this you will lose traces on Vercel, AWS Lambda, and similar platforms.
experimental_telemetry vs wrapAISDK. The AI SDK has a generic experimental_telemetry flag that emits OpenTelemetry spans (used by Langfuse). wrapAISDK is LangSmith's own path; you do not need to set experimental_telemetry when using it.
LangGraph users. If your backend is LangGraph Cloud, prefer the LangGraph runtime; tracing is built in. Use wrapAISDK only when calling AI SDK directly outside of LangGraph.
Version requirements. LangSmith documents AI SDK v5 as the minimum and langsmith >= 0.3.63. The wrapper continues to work against v6 in practice; if you hit an incompatibility, check LangSmith's release notes.

LangGraph runtimeIf your backend is LangGraph, tracing flows through LangGraph Cloud automatically.LangfuseOpenTelemetry-based alternative; OSS and self-hostable.AI SDK runtimeThe runtime that ferries traces from the route to the chat UI.