LangChain
Adds instrumentation for LangChain.
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.
The following options control what data is captured from LangChain operations:
Type: boolean (optional)
Records inputs to LangChain operations (such as prompts and messages).
Defaults to true if sendDefaultPii is true.
Type: boolean (optional)
Records outputs from LangChain operations (such as generated text and responses).
Defaults to true if sendDefaultPii is true.
Usage
Using the createLangChainCallbackHandler helper:
const callbackHandler = Sentry.createLangChainCallbackHandler({
// your options here
});
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
The integration automatically instruments the following LangChain runnable methods:
invoke()- Single executionstream()- Streaming executionbatch()- Batch execution
The automatic instrumentation supports the following LangChain provider packages:
@langchain/anthropic@langchain/openai@langchain/google-genai@langchain/mistralai@langchain/google-vertexai@langchain/groq
langchain:>=0.1.0 <2.0.0
Our documentation is open source and available on GitHub. Your contributions are welcome, whether fixing a typo (drat!) or suggesting an update ("yeah, this would be better").