feat(core): Support embeddings in langchain

dev-packages/node-integration-tests/package.json

@@ -32,6 +32,7 @@
     "@hono/node-server": "^1.19.10",
     "@langchain/anthropic": "^0.3.10",
     "@langchain/core": "^0.3.80",
+    "@langchain/openai": "^0.5.0",
     "@langchain/langgraph": "^0.2.32",
     "@nestjs/common": "^11",
     "@nestjs/core": "^11",

dev-packages/node-integration-tests/suites/tracing/langchain/instrument-with-pii.mjs

@@ -9,7 +9,7 @@ Sentry.init({
   transport: loggingTransport,
   beforeSendTransaction: event => {
     // Filter out mock express server transactions
-    if (event.transaction.includes('/v1/messages')) {
+    if (event.transaction.includes('/v1/messages') || event.transaction.includes('/v1/embeddings')) {
       return null;
     }
     return event;

dev-packages/node-integration-tests/suites/tracing/langchain/instrument.mjs

@@ -9,7 +9,7 @@ Sentry.init({
   transport: loggingTransport,
   beforeSendTransaction: event => {
     // Filter out mock express server transactions
-    if (event.transaction.includes('/v1/messages')) {
+    if (event.transaction.includes('/v1/messages') || event.transaction.includes('/v1/embeddings')) {
       return null;
     }
     return event;

dev-packages/node-integration-tests/suites/tracing/langchain/scenario-embeddings.mjs

@@ -0,0 +1,82 @@
+import { OpenAIEmbeddings } from '@langchain/openai';
+import * as Sentry from '@sentry/node';
+import express from 'express';
+
+function startMockOpenAIServer() {
+  const app = express();
+  app.use(express.json());
+
+  app.post('/v1/embeddings', (req, res) => {
+    const { model, input } = req.body;
+
+    if (model === 'error-model') {
+      res.status(400).json({
+        error: {
+          message: 'Model not found',
+          type: 'invalid_request_error',
+        },
+      });
+      return;
+    }
+
+    const inputs = Array.isArray(input) ? input : [input];
+    res.json({
+      object: 'list',
+      data: inputs.map((_, i) => ({
+        object: 'embedding',
+        embedding: [0.1, 0.2, 0.3],
+        index: i,
+      })),
+      model: model,
+      usage: {
+        prompt_tokens: 10,
+        total_tokens: 10,
+      },
+    });
+  });
+
+  return new Promise(resolve => {
+    const server = app.listen(0, () => {
+      resolve(server);
+    });
+  });
+}
+
+async function run() {
+  const server = await startMockOpenAIServer();
+  const baseUrl = `http://localhost:${server.address().port}/v1`;
+
+  await Sentry.startSpan({ op: 'function', name: 'main' }, async () => {
+    // Test 1: embedQuery
+    const embeddings = new OpenAIEmbeddings({
+      model: 'text-embedding-3-small',
+      dimensions: 1536,
+      apiKey: 'mock-api-key',
+      configuration: { baseURL: baseUrl },
+    });
+
+    await embeddings.embedQuery('Hello world');
+
+    // Test 2: embedDocuments
+    await embeddings.embedDocuments(['First document', 'Second document']);
+
+    // Test 3: Error handling
+    const errorEmbeddings = new OpenAIEmbeddings({
+      model: 'error-model',
+      apiKey: 'mock-api-key',
+      configuration: { baseURL: baseUrl },
+    });
+
+    try {
+      await errorEmbeddings.embedQuery('This will fail');
+    } catch {
+      // Expected error
+    }
+  });
+
+  await Sentry.flush(2000);
+
+  server.close();
+}
+
+run();

dev-packages/node-integration-tests/suites/tracing/langchain/test.ts

@@ -1,9 +1,12 @@
 import { SEMANTIC_ATTRIBUTE_SENTRY_OP, SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN } from '@sentry/core';
 import { afterAll, describe, expect } from 'vitest';
 import {
+  GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+  GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE,
   GEN_AI_INPUT_MESSAGES_ATTRIBUTE,
   GEN_AI_INPUT_MESSAGES_ORIGINAL_LENGTH_ATTRIBUTE,
   GEN_AI_OPERATION_NAME_ATTRIBUTE,
+  GEN_AI_REQUEST_DIMENSIONS_ATTRIBUTE,
   GEN_AI_REQUEST_MAX_TOKENS_ATTRIBUTE,
   GEN_AI_REQUEST_MODEL_ATTRIBUTE,
   GEN_AI_REQUEST_TEMPERATURE_ATTRIBUTE,
@@ -430,4 +433,120 @@ describe('LangChain integration', () => {
         .completed();
     });
   });
+
+  // =========================================================================
+  // Embeddings tests
+  // =========================================================================
+
+  const EXPECTED_TRANSACTION_EMBEDDINGS = {
+    transaction: 'main',
+    spans: expect.arrayContaining([
+      // embedQuery span
+      expect.objectContaining({
+        data: expect.objectContaining({
+          [GEN_AI_OPERATION_NAME_ATTRIBUTE]: 'embed',
+          [SEMANTIC_ATTRIBUTE_SENTRY_OP]: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+          [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.langchain',
+          [GEN_AI_SYSTEM_ATTRIBUTE]: 'openai',
+          [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-3-small',
+          [GEN_AI_REQUEST_DIMENSIONS_ATTRIBUTE]: 1536,
+        }),
+        description: 'embed text-embedding-3-small',
+        op: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+        origin: 'auto.ai.langchain',
+        status: 'ok',
+      }),
+      // embedDocuments span
+      expect.objectContaining({
+        data: expect.objectContaining({
+          [GEN_AI_OPERATION_NAME_ATTRIBUTE]: 'embed_many',
+          [SEMANTIC_ATTRIBUTE_SENTRY_OP]: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+          [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.langchain',
+          [GEN_AI_SYSTEM_ATTRIBUTE]: 'openai',
+          [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-3-small',
+        }),
+        description: 'embed_many text-embedding-3-small',
+        op: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+        origin: 'auto.ai.langchain',
+        status: 'ok',
+      }),
+      // Error span
+      expect.objectContaining({
+        data: expect.objectContaining({
+          [GEN_AI_OPERATION_NAME_ATTRIBUTE]: 'embed',
+          [SEMANTIC_ATTRIBUTE_SENTRY_OP]: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+          [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.langchain',
+          [GEN_AI_SYSTEM_ATTRIBUTE]: 'openai',
+          [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'error-model',
+        }),
+        description: 'embed error-model',
+        op: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+        origin: 'auto.ai.langchain',
+        status: 'internal_error',
+      }),
+    ]),
+  };
+
+  const EXPECTED_TRANSACTION_EMBEDDINGS_PII = {
+    transaction: 'main',
+    spans: expect.arrayContaining([
+      // embedQuery span with input recorded
+      expect.objectContaining({
+        data: expect.objectContaining({
+          [GEN_AI_OPERATION_NAME_ATTRIBUTE]: 'embed',
+          [SEMANTIC_ATTRIBUTE_SENTRY_OP]: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+          [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: 'auto.ai.langchain',
+          [GEN_AI_SYSTEM_ATTRIBUTE]: 'openai',
+          [GEN_AI_REQUEST_MODEL_ATTRIBUTE]: 'text-embedding-3-small',
+          [GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE]: 'Hello world',
+        }),
+        description: 'embed text-embedding-3-small',
+        op: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+        origin: 'auto.ai.langchain',
+        status: 'ok',
+      }),
+      // embedDocuments span with input recorded
+      expect.objectContaining({
+        data: expect.objectContaining({
+          [GEN_AI_OPERATION_NAME_ATTRIBUTE]: 'embed_many',
+          [GEN_AI_EMBEDDINGS_INPUT_ATTRIBUTE]: JSON.stringify(['First document', 'Second document']),
+        }),
+        description: 'embed_many text-embedding-3-small',
+        op: GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE,
+        origin: 'auto.ai.langchain',
+        status: 'ok',
+      }),
+    ]),
+  };
+
+  createEsmAndCjsTests(__dirname, 'scenario-embeddings.mjs', 'instrument.mjs', (createRunner, test) => {
+    test('creates embedding spans with sendDefaultPii: false', async () => {
+      await createRunner().ignore('event').expect({ transaction: EXPECTED_TRANSACTION_EMBEDDINGS }).start().completed();
+    });
+
+    test('does not create duplicate embedding spans from double module patching', async () => {
+      await createRunner()
+        .ignore('event')
+        .expect({
+          transaction: event => {
+            const spans = event.spans || [];
+            const embeddingSpans = spans.filter(span => span.op === GEN_AI_EMBED_DO_EMBED_OPERATION_ATTRIBUTE);
+            // The scenario makes 3 embedding calls (2 successful + 1 error).
+            expect(embeddingSpans).toHaveLength(3);
+          },
+        })
+        .start()
+        .completed();
+    });
+  });
+
+  createEsmAndCjsTests(__dirname, 'scenario-embeddings.mjs', 'instrument-with-pii.mjs', (createRunner, test) => {
+    test('creates embedding spans with sendDefaultPii: true', async () => {
+      await createRunner()
+        .ignore('event')
+        .expect({ transaction: EXPECTED_TRANSACTION_EMBEDDINGS_PII })
+        .start()
+        .completed();
+    });
+  });
 });

packages/aws-serverless/src/index.ts

@@ -44,6 +44,7 @@ export {
   getSentryRelease,
   createGetModuleFromFilename,
   createLangChainCallbackHandler,
+  wrapLangChainEmbeddings,
   httpHeadersToSpanAttributes,
   winterCGHeadersToDict,
   // eslint-disable-next-line deprecation/deprecation

packages/browser/src/index.ts

@@ -70,6 +70,7 @@ export {
   instrumentGoogleGenAIClient,
   instrumentLangGraph,
   createLangChainCallbackHandler,
+  wrapLangChainEmbeddings,
   logger,
 } from '@sentry/core';
 export type { Span, FeatureFlagsIntegration } from '@sentry/core';

packages/browser/src/integrations-bundle/index.wraplangchainembeddings.ts

@@ -0,0 +1 @@
+export { wrapLangChainEmbeddings } from '@sentry/core';

packages/bun/src/index.ts

@@ -67,6 +67,7 @@ export {
   getSentryRelease,
   createGetModuleFromFilename,
   createLangChainCallbackHandler,
+  wrapLangChainEmbeddings,
   httpHeadersToSpanAttributes,
   winterCGHeadersToDict,
   // eslint-disable-next-line deprecation/deprecation

packages/cloudflare/src/index.ts

@@ -102,6 +102,7 @@ export {
   consoleLoggingIntegration,
   createConsolaReporter,
   createLangChainCallbackHandler,
+  wrapLangChainEmbeddings,
   featureFlagsIntegration,
   growthbookIntegration,
   logger,

packages/core/src/index.ts

@@ -158,7 +158,7 @@ export { ANTHROPIC_AI_INTEGRATION_NAME } from './tracing/anthropic-ai/constants'
 export { instrumentGoogleGenAIClient } from './tracing/google-genai';
 export { GOOGLE_GENAI_INTEGRATION_NAME } from './tracing/google-genai/constants';
 export type { GoogleGenAIResponse } from './tracing/google-genai/types';
-export { createLangChainCallbackHandler } from './tracing/langchain';
+export { createLangChainCallbackHandler, wrapEmbeddingMethod, wrapLangChainEmbeddings } from './tracing/langchain';
 export { LANGCHAIN_INTEGRATION_NAME } from './tracing/langchain/constants';
 export type { LangChainOptions, LangChainIntegration } from './tracing/langchain/types';
 export { instrumentStateGraphCompile, instrumentLangGraph } from './tracing/langgraph';