Skip to content

fix: Vercel ai ESM patching #16152

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 4 commits into from
Apr 29, 2025
Merged

fix: Vercel ai ESM patching #16152

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
d48395d
fix: Vercel `ai` `import-in-the-middle` patching
timfish Apr 28, 2025
3405d36
Merge branch 'develop' into fix/vercel-ai-iitm-issue
timfish Apr 29, 2025
f4c62da
Lint fail from master
timfish Apr 29, 2025
ac18cd5
Merge branch 'develop' into fix/vercel-ai-iitm-issue
timfish Apr 29, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 9 additions & 0 deletions dev-packages/node-integration-tests/suites/tracing/ai/instrument.mjs
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,9 @@
import * as Sentry from '@sentry/node';
import { loggingTransport } from '@sentry-internal/node-integration-tests';

Sentry.init({
dsn: 'https://[email protected]/1337',
release: '1.0',
tracesSampleRate: 1.0,
transport: loggingTransport,
});
49 changes: 49 additions & 0 deletions dev-packages/node-integration-tests/suites/tracing/ai/scenario.mjs
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,49 @@
import * as Sentry from '@sentry/node';
import { generateText } from 'ai';
import { MockLanguageModelV1 } from 'ai/test';

async function run() {
await Sentry.startSpan({ op: 'function', name: 'main' }, async () => {
await generateText({
model: new MockLanguageModelV1({
doGenerate: async () => ({
rawCall: { rawPrompt: null, rawSettings: {} },
finishReason: 'stop',
usage: { promptTokens: 10, completionTokens: 20 },
text: 'First span here!',
}),
}),
prompt: 'Where is the first span?',
});

// This span should have input and output prompts attached because telemetry is explicitly enabled.
await generateText({
experimental_telemetry: { isEnabled: true },
model: new MockLanguageModelV1({
doGenerate: async () => ({
rawCall: { rawPrompt: null, rawSettings: {} },
finishReason: 'stop',
usage: { promptTokens: 10, completionTokens: 20 },
text: 'Second span here!',
}),
}),
prompt: 'Where is the second span?',
});

// This span should not be captured because we've disabled telemetry
await generateText({
experimental_telemetry: { isEnabled: false },
model: new MockLanguageModelV1({
doGenerate: async () => ({
rawCall: { rawPrompt: null, rawSettings: {} },
finishReason: 'stop',
usage: { promptTokens: 10, completionTokens: 20 },
text: 'Third span here!',
}),
}),
prompt: 'Where is the third span?',
});
});
}

run();
237 changes: 123 additions & 114 deletions dev-packages/node-integration-tests/suites/tracing/ai/test.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import { join } from 'node:path';
import { afterAll, describe, expect, test } from 'vitest';
import { cleanupChildProcesses, createRunner } from '../../../utils/runner';

Expand All @@ -7,125 +8,133 @@ describe('ai', () => {
cleanupChildProcesses();
});

test('creates ai related spans', async () => {
const EXPECTED_TRANSACTION = {
transaction: 'main',
spans: expect.arrayContaining([
expect.objectContaining({
data: expect.objectContaining({
'ai.completion_tokens.used': 20,
'ai.model.id': 'mock-model-id',
'ai.model.provider': 'mock-provider',
'ai.model_id': 'mock-model-id',
'ai.operationId': 'ai.generateText',
'ai.pipeline.name': 'generateText',
'ai.prompt_tokens.used': 10,
'ai.response.finishReason': 'stop',
'ai.settings.maxRetries': 2,
'ai.settings.maxSteps': 1,
'ai.streaming': false,
'ai.total_tokens.used': 30,
'ai.usage.completionTokens': 20,
'ai.usage.promptTokens': 10,
'operation.name': 'ai.generateText',
'sentry.op': 'ai.pipeline.generateText',
'sentry.origin': 'auto.vercelai.otel',
}),
description: 'generateText',
op: 'ai.pipeline.generateText',
origin: 'auto.vercelai.otel',
status: 'ok',
const EXPECTED_TRANSACTION = {
transaction: 'main',
spans: expect.arrayContaining([
expect.objectContaining({
data: expect.objectContaining({
'ai.completion_tokens.used': 20,
'ai.model.id': 'mock-model-id',
'ai.model.provider': 'mock-provider',
'ai.model_id': 'mock-model-id',
'ai.operationId': 'ai.generateText',
'ai.pipeline.name': 'generateText',
'ai.prompt_tokens.used': 10,
'ai.response.finishReason': 'stop',
'ai.settings.maxRetries': 2,
'ai.settings.maxSteps': 1,
'ai.streaming': false,
'ai.total_tokens.used': 30,
'ai.usage.completionTokens': 20,
'ai.usage.promptTokens': 10,
'operation.name': 'ai.generateText',
'sentry.op': 'ai.pipeline.generateText',
'sentry.origin': 'auto.vercelai.otel',
}),
expect.objectContaining({
data: expect.objectContaining({
'sentry.origin': 'auto.vercelai.otel',
'sentry.op': 'ai.run.doGenerate',
'operation.name': 'ai.generateText.doGenerate',
'ai.operationId': 'ai.generateText.doGenerate',
'ai.model.provider': 'mock-provider',
'ai.model.id': 'mock-model-id',
'ai.settings.maxRetries': 2,
'gen_ai.system': 'mock-provider',
'gen_ai.request.model': 'mock-model-id',
'ai.pipeline.name': 'generateText.doGenerate',
'ai.model_id': 'mock-model-id',
'ai.streaming': false,
'ai.response.finishReason': 'stop',
'ai.response.model': 'mock-model-id',
'ai.usage.promptTokens': 10,
'ai.usage.completionTokens': 20,
'gen_ai.response.finish_reasons': ['stop'],
'gen_ai.usage.input_tokens': 10,
'gen_ai.usage.output_tokens': 20,
'ai.completion_tokens.used': 20,
'ai.prompt_tokens.used': 10,
'ai.total_tokens.used': 30,
}),
description: 'generateText.doGenerate',
op: 'ai.run.doGenerate',
origin: 'auto.vercelai.otel',
status: 'ok',
description: 'generateText',
op: 'ai.pipeline.generateText',
origin: 'auto.vercelai.otel',
status: 'ok',
}),
expect.objectContaining({
data: expect.objectContaining({
'sentry.origin': 'auto.vercelai.otel',
'sentry.op': 'ai.run.doGenerate',
'operation.name': 'ai.generateText.doGenerate',
'ai.operationId': 'ai.generateText.doGenerate',
'ai.model.provider': 'mock-provider',
'ai.model.id': 'mock-model-id',
'ai.settings.maxRetries': 2,
'gen_ai.system': 'mock-provider',
'gen_ai.request.model': 'mock-model-id',
'ai.pipeline.name': 'generateText.doGenerate',
'ai.model_id': 'mock-model-id',
'ai.streaming': false,
'ai.response.finishReason': 'stop',
'ai.response.model': 'mock-model-id',
'ai.usage.promptTokens': 10,
'ai.usage.completionTokens': 20,
'gen_ai.response.finish_reasons': ['stop'],
'gen_ai.usage.input_tokens': 10,
'gen_ai.usage.output_tokens': 20,
'ai.completion_tokens.used': 20,
'ai.prompt_tokens.used': 10,
'ai.total_tokens.used': 30,
}),
expect.objectContaining({
data: expect.objectContaining({
'ai.completion_tokens.used': 20,
'ai.model.id': 'mock-model-id',
'ai.model.provider': 'mock-provider',
'ai.model_id': 'mock-model-id',
'ai.prompt': '{"prompt":"Where is the second span?"}',
'ai.operationId': 'ai.generateText',
'ai.pipeline.name': 'generateText',
'ai.prompt_tokens.used': 10,
'ai.response.finishReason': 'stop',
'ai.input_messages': '{"prompt":"Where is the second span?"}',
'ai.settings.maxRetries': 2,
'ai.settings.maxSteps': 1,
'ai.streaming': false,
'ai.total_tokens.used': 30,
'ai.usage.completionTokens': 20,
'ai.usage.promptTokens': 10,
'operation.name': 'ai.generateText',
'sentry.op': 'ai.pipeline.generateText',
'sentry.origin': 'auto.vercelai.otel',
}),
description: 'generateText',
op: 'ai.pipeline.generateText',
origin: 'auto.vercelai.otel',
status: 'ok',
description: 'generateText.doGenerate',
op: 'ai.run.doGenerate',
origin: 'auto.vercelai.otel',
status: 'ok',
}),
expect.objectContaining({
data: expect.objectContaining({
'ai.completion_tokens.used': 20,
'ai.model.id': 'mock-model-id',
'ai.model.provider': 'mock-provider',
'ai.model_id': 'mock-model-id',
'ai.prompt': '{"prompt":"Where is the second span?"}',
'ai.operationId': 'ai.generateText',
'ai.pipeline.name': 'generateText',
'ai.prompt_tokens.used': 10,
'ai.response.finishReason': 'stop',
'ai.input_messages': '{"prompt":"Where is the second span?"}',
'ai.settings.maxRetries': 2,
'ai.settings.maxSteps': 1,
'ai.streaming': false,
'ai.total_tokens.used': 30,
'ai.usage.completionTokens': 20,
'ai.usage.promptTokens': 10,
'operation.name': 'ai.generateText',
'sentry.op': 'ai.pipeline.generateText',
'sentry.origin': 'auto.vercelai.otel',
}),
expect.objectContaining({
data: expect.objectContaining({
'sentry.origin': 'auto.vercelai.otel',
'sentry.op': 'ai.run.doGenerate',
'operation.name': 'ai.generateText.doGenerate',
'ai.operationId': 'ai.generateText.doGenerate',
'ai.model.provider': 'mock-provider',
'ai.model.id': 'mock-model-id',
'ai.settings.maxRetries': 2,
'gen_ai.system': 'mock-provider',
'gen_ai.request.model': 'mock-model-id',
'ai.pipeline.name': 'generateText.doGenerate',
'ai.model_id': 'mock-model-id',
'ai.streaming': false,
'ai.response.finishReason': 'stop',
'ai.response.model': 'mock-model-id',
'ai.usage.promptTokens': 10,
'ai.usage.completionTokens': 20,
'gen_ai.response.finish_reasons': ['stop'],
'gen_ai.usage.input_tokens': 10,
'gen_ai.usage.output_tokens': 20,
'ai.completion_tokens.used': 20,
'ai.prompt_tokens.used': 10,
'ai.total_tokens.used': 30,
}),
description: 'generateText.doGenerate',
op: 'ai.run.doGenerate',
origin: 'auto.vercelai.otel',
status: 'ok',
description: 'generateText',
op: 'ai.pipeline.generateText',
origin: 'auto.vercelai.otel',
status: 'ok',
}),
expect.objectContaining({
data: expect.objectContaining({
'sentry.origin': 'auto.vercelai.otel',
'sentry.op': 'ai.run.doGenerate',
'operation.name': 'ai.generateText.doGenerate',
'ai.operationId': 'ai.generateText.doGenerate',
'ai.model.provider': 'mock-provider',
'ai.model.id': 'mock-model-id',
'ai.settings.maxRetries': 2,
'gen_ai.system': 'mock-provider',
'gen_ai.request.model': 'mock-model-id',
'ai.pipeline.name': 'generateText.doGenerate',
'ai.model_id': 'mock-model-id',
'ai.streaming': false,
'ai.response.finishReason': 'stop',
'ai.response.model': 'mock-model-id',
'ai.usage.promptTokens': 10,
'ai.usage.completionTokens': 20,
'gen_ai.response.finish_reasons': ['stop'],
'gen_ai.usage.input_tokens': 10,
'gen_ai.usage.output_tokens': 20,
'ai.completion_tokens.used': 20,
'ai.prompt_tokens.used': 10,
'ai.total_tokens.used': 30,
}),
]),
};
description: 'generateText.doGenerate',
op: 'ai.run.doGenerate',
origin: 'auto.vercelai.otel',
status: 'ok',
}),
]),
};

test('creates ai related spans - cjs', async () => {
await createRunner(__dirname, 'scenario.js').expect({ transaction: EXPECTED_TRANSACTION }).start().completed();
});

test('creates ai related spans - esm', async () => {
await createRunner(__dirname, 'scenario.mjs')
.withFlags('--import', join(__dirname, 'instrument.mjs'))
.expect({ transaction: EXPECTED_TRANSACTION })
.start()
.completed();
});
});
27 changes: 20 additions & 7 deletions packages/node/src/integrations/tracing/vercelai/instrumentation.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,7 @@ export class SentryVercelAiInstrumentation extends InstrumentationBase {
this._callbacks.forEach(callback => callback());
this._callbacks = [];

function generatePatch(name: string) {
function generatePatch(originalMethod: (...args: MethodArgs) => unknown) {
return (...args: MethodArgs) => {
const existingExperimentalTelemetry = args[0].experimental_telemetry || {};
const isEnabled = existingExperimentalTelemetry.isEnabled;
Expand All @@ -83,15 +83,28 @@ export class SentryVercelAiInstrumentation extends InstrumentationBase {
}

// @ts-expect-error we know that the method exists
return moduleExports[name].apply(this, args);
return originalMethod.apply(this, args);
};
}

const patchedModuleExports = INSTRUMENTED_METHODS.reduce((acc, curr) => {
acc[curr] = generatePatch(curr);
return acc;
}, {} as PatchedModuleExports);
// Is this an ESM module?
// https://tc39.es/ecma262/#sec-module-namespace-objects
if (Object.prototype.toString.call(moduleExports) === '[object Module]') {
// In ESM we take the usual route and just replace the exports we want to instrument
for (const method of INSTRUMENTED_METHODS) {
moduleExports[method] = generatePatch(moduleExports[method]);
}

return { ...moduleExports, ...patchedModuleExports };
return moduleExports;
} else {
// In CJS we can't replace the exports in the original module because they
// don't have setters, so we create a new object with the same properties
const patchedModuleExports = INSTRUMENTED_METHODS.reduce((acc, curr) => {
acc[curr] = generatePatch(moduleExports[curr]);
return acc;
}, {} as PatchedModuleExports);

return { ...moduleExports, ...patchedModuleExports };
}
}
}
Loading