LangChain | Sentry for Next.js

Source URL: https://docs.sentry.io/platforms/javascript/guides/nextjs/configuration/integrations/langchain

LangChain | Sentry for Next.js

Server-Side Usage

For meta-framework applications using all runtimes, you need to manually create a LangChain callback handler with createLangChainCallbackHandler. See instructions in the Browser-Side Usage section.

Browser-Side Usage

Import name: Sentry.createLangChainCallbackHandler

The createLangChainCallbackHandler helper adds instrumentation for langchain to capture spans by creating a callback handler that wraps LangChain operations and records AI agent interactions with configurable input/output recording. You need to manually create and pass this callback handler to your LangChain operations. See example below:

import { ChatAnthropic } from "@langchain/anthropic";

// Create a LangChain callback handler
const callbackHandler = Sentry.createLangChainCallbackHandler({
  recordInputs: true,
  recordOutputs: true,
});

// Use with chat models
const model = new ChatAnthropic({
  model: "claude-3-5-sonnet-20241022",
  apiKey: "your-api-key", // Warning: API key will be exposed in browser!
});

await model.invoke("Tell me a joke", {
  callbacks: [callbackHandler],
});

To customize what data is captured (such as inputs and outputs), see the Options in the Configuration section.

Configuration

• Options

The following options control what data is captured from LangChain operations:

• recordInputs

Type: boolean (optional)

Records inputs to LangChain operations (such as prompts and messages).

Defaults to true if sendDefaultPii is true.

• recordOutputs

Type: boolean (optional)

Records outputs from LangChain operations (such as generated text and responses).

Defaults to true if sendDefaultPii is true.

Usage

Using the langChainIntegration integration:

Sentry.init({
  dsn: "____PUBLIC_DSN____",
  // Tracing must be enabled for agent monitoring to work
  tracesSampleRate: 1.0,
  integrations: [
    Sentry.langChainIntegration({
      // your options here
    }),
  ],
});

Using the createLangChainCallbackHandler helper:

const callbackHandler = Sentry.createLangChainCallbackHandler({
  // your options here
});

Supported Operations

By default, tracing support is added to the following LangChain SDK calls:

• Chat model invocations - Captures spans for chat model calls
• LLM invocations - Captures spans for LLM pipeline executions
• Chain executions - Captures spans for chain invocations
• Tool executions - Captures spans for tool calls

• Runnables

The integration automatically instruments the following LangChain runnable methods:

• invoke() - Single execution
• stream() - Streaming execution
• batch() - Batch execution

• Providers

The automatic instrumentation supports the following LangChain provider packages:

• @langchain/anthropic
• @langchain/openai
• @langchain/google-genai
• @langchain/mistralai
• @langchain/google-vertexai
• @langchain/groq

Supported Versions

• langchain: >=0.1.0 <2.0.0