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feat(cloudflare,vercel-edge): Add support for LangChain instrumentation
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‎dev-packages/cloudflare-integration-tests/suites/tracing/langchain/index.ts‎

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import * as Sentry from '@sentry/cloudflare';
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import { MockChain, MockChatModel, MockTool } from './mocks';
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interface Env {
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SENTRY_DSN: string;
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}
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export default Sentry.withSentry(
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(env: Env) => ({
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dsn: env.SENTRY_DSN,
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tracesSampleRate: 1.0,
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}),
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{
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async fetch(_request, _env, _ctx) {
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// Create LangChain callback handler
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const callbackHandler = Sentry.createLangChainCallbackHandler({
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recordInputs: false,
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recordOutputs: false,
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});
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// Test 1: Chat model invocation
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const chatModel = new MockChatModel({
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model: 'claude-3-5-sonnet-20241022',
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temperature: 0.7,
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maxTokens: 100,
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});
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await chatModel.invoke('Tell me a joke', {
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callbacks: [callbackHandler],
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});
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// Test 2: Chain invocation
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const chain = new MockChain('my_test_chain');
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await chain.invoke(
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{ input: 'test input' },
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{
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callbacks: [callbackHandler],
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},
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);
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// Test 3: Tool invocation
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const tool = new MockTool('search_tool');
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await tool.call('search query', {
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callbacks: [callbackHandler],
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});
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return new Response(JSON.stringify({ success: true }));
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},
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},
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);

‎dev-packages/cloudflare-integration-tests/suites/tracing/langchain/mocks.ts‎

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// Mock LangChain types and classes for testing the callback handler
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// Minimal callback handler interface to match LangChain's callback handler signature
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export interface CallbackHandler {
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handleChatModelStart?: (
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llm: unknown,
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messages: unknown,
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runId: string,
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parentRunId?: string,
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extraParams?: Record<string, unknown>,
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tags?: string[],
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metadata?: Record<string, unknown>,
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runName?: string,
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) => unknown;
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handleLLMEnd?: (output: unknown, runId: string) => unknown;
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handleChainStart?: (chain: { name?: string }, inputs: Record<string, unknown>, runId: string) => unknown;
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handleChainEnd?: (outputs: unknown, runId: string) => unknown;
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handleToolStart?: (tool: { name?: string }, input: string, runId: string) => unknown;
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handleToolEnd?: (output: unknown, runId: string) => unknown;
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}
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export interface LangChainMessage {
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role: string;
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content: string;
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}
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export interface LangChainLLMResult {
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generations: Array<
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Array<{
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text: string;
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generationInfo?: {
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[key: string]: unknown;
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finish_reason?: string;
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};
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}>
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>;
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llmOutput?: {
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[key: string]: unknown;
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tokenUsage?: {
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promptTokens?: number;
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completionTokens?: number;
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totalTokens?: number;
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};
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model?: string;
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id?: string;
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};
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}
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export interface InvocationParams {
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[key: string]: unknown;
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model: string;
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temperature?: number;
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maxTokens?: number;
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}
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// Mock LangChain Chat Model
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export class MockChatModel {
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private _model: string;
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private _temperature?: number;
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private _maxTokens?: number;
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public constructor(params: InvocationParams) {
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this._model = params.model;
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this._temperature = params.temperature;
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this._maxTokens = params.maxTokens;
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}
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public async invoke(
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messages: LangChainMessage[] | string,
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options?: { callbacks?: CallbackHandler[] },
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): Promise<LangChainLLMResult> {
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const callbacks = options?.callbacks || [];
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const runId = crypto.randomUUID();
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// Get invocation params to match LangChain's signature
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const invocationParams = {
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model: this._model,
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temperature: this._temperature,
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max_tokens: this._maxTokens,
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};
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// Create serialized representation similar to LangChain
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const serialized = {
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lc: 1,
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type: 'constructor',
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id: ['langchain', 'anthropic', 'anthropic'], // Third element is used as system provider
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kwargs: invocationParams,
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};
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// Prepare messages in LangChain format
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const messageArray = typeof messages === 'string' ? [{ role: 'user', content: messages }] : messages;
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const formattedMessages = [
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messageArray.map(msg => ({
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lc: 1,
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type: 'human',
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id: ['langchain', 'schema', 'HumanMessage'],
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kwargs: { content: msg.content },
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})),
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];
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// Call handleChatModelStart
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// Pass tags as a record with invocation_params for proper extraction
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for (const callback of callbacks) {
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if (callback.handleChatModelStart) {
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await callback.handleChatModelStart(
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serialized,
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formattedMessages,
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runId,
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undefined,
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undefined,
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{ invocation_params: invocationParams } as unknown as string[], // LangChain can pass tags as either string[] or record
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{ ls_model_name: this._model, ls_provider: 'anthropic' },
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);
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}
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}
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// Simulate API call
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await new Promise(resolve => setTimeout(resolve, 10));
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// Create mock result
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const result: LangChainLLMResult = {
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generations: [
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[
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{
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text: 'Mock response from LangChain!',
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generationInfo: {
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finish_reason: 'stop',
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},
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},
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],
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],
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llmOutput: {
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tokenUsage: {
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promptTokens: 10,
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completionTokens: 15,
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totalTokens: 25,
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},
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model: this._model,
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id: 'chatcmpl_mock123',
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},
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};
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// Call handleLLMEnd
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for (const callback of callbacks) {
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if (callback.handleLLMEnd) {
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await callback.handleLLMEnd(result, runId);
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}
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}
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return result;
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}
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}
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// Mock LangChain Chain
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export class MockChain {
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private _name: string;
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public constructor(name: string) {
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this._name = name;
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}
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public async invoke(
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inputs: Record<string, unknown>,
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options?: { callbacks?: CallbackHandler[] },
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): Promise<Record<string, unknown>> {
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const callbacks = options?.callbacks || [];
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const runId = crypto.randomUUID();
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// Call handleChainStart
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for (const callback of callbacks) {
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if (callback.handleChainStart) {
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await callback.handleChainStart({ name: this._name }, inputs, runId);
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}
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}
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// Simulate processing
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await new Promise(resolve => setTimeout(resolve, 10));
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const outputs = { result: 'Chain execution completed!' };
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// Call handleChainEnd
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for (const callback of callbacks) {
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if (callback.handleChainEnd) {
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await callback.handleChainEnd(outputs, runId);
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}
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}
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return outputs;
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}
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}
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// Mock LangChain Tool
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export class MockTool {
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private _name: string;
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public constructor(name: string) {
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this._name = name;
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}
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public async call(input: string, options?: { callbacks?: CallbackHandler[] }): Promise<string> {
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const callbacks = options?.callbacks || [];
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const runId = crypto.randomUUID();
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// Call handleToolStart
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for (const callback of callbacks) {
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if (callback.handleToolStart) {
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await callback.handleToolStart({ name: this._name }, input, runId);
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}
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}
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// Simulate tool execution
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await new Promise(resolve => setTimeout(resolve, 10));
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const output = `Tool ${this._name} executed with input: ${input}`;
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// Call handleToolEnd
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for (const callback of callbacks) {
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if (callback.handleToolEnd) {
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await callback.handleToolEnd(output, runId);
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}
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}
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return output;
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}
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}

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

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import { expect, it } from 'vitest';
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import { createRunner } from '../../../runner';
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// These tests are not exhaustive because the instrumentation is
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// already tested in the node integration tests and we merely
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// want to test that the instrumentation does not break in our
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// cloudflare SDK.
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it('traces langchain chat model, chain, and tool invocations', async ({ signal }) => {
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const runner = createRunner(__dirname)
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.ignore('event')
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.expect(envelope => {
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const transactionEvent = envelope[1]?.[0]?.[1] as any;
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expect(transactionEvent.transaction).toBe('GET /');
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expect(transactionEvent.spans).toEqual(
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expect.arrayContaining([
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// Chat model span
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expect.objectContaining({
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data: expect.objectContaining({
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'gen_ai.operation.name': 'chat',
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'sentry.op': 'gen_ai.chat',
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'sentry.origin': 'auto.ai.langchain',
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'gen_ai.system': 'anthropic',
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'gen_ai.request.model': 'claude-3-5-sonnet-20241022',
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'gen_ai.request.temperature': 0.7,
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'gen_ai.request.max_tokens': 100,
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'gen_ai.usage.input_tokens': 10,
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'gen_ai.usage.output_tokens': 15,
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'gen_ai.usage.total_tokens': 25,
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}),
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description: 'chat claude-3-5-sonnet-20241022',
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op: 'gen_ai.chat',
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origin: 'auto.ai.langchain',
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}),
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// Chain span
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expect.objectContaining({
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data: expect.objectContaining({
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'sentry.origin': 'auto.ai.langchain',
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'sentry.op': 'gen_ai.invoke_agent',
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'langchain.chain.name': 'my_test_chain',
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}),
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description: 'chain my_test_chain',
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op: 'gen_ai.invoke_agent',
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origin: 'auto.ai.langchain',
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}),
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// Tool span
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expect.objectContaining({
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data: expect.objectContaining({
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'sentry.origin': 'auto.ai.langchain',
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'sentry.op': 'gen_ai.execute_tool',
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'gen_ai.tool.name': 'search_tool',
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}),
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description: 'execute_tool search_tool',
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op: 'gen_ai.execute_tool',
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origin: 'auto.ai.langchain',
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}),
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]),
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);
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})
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.start(signal);
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await runner.makeRequest('get', '/');
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await runner.completed();
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});

‎dev-packages/cloudflare-integration-tests/suites/tracing/langchain/wrangler.jsonc‎

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{
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"name": "worker-name",
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"compatibility_date": "2025-06-17",
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"main": "index.ts",
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"compatibility_flags": ["nodejs_compat"],
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}

‎packages/cloudflare/src/index.ts‎

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wrapMcpServerWithSentry,
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consoleLoggingIntegration,
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createConsolaReporter,
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createLangChainCallbackHandler,
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featureFlagsIntegration,
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growthbookIntegration,
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logger,

‎packages/vercel-edge/src/index.ts‎

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wrapMcpServerWithSentry,
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consoleLoggingIntegration,
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createConsolaReporter,
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createLangChainCallbackHandler,
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featureFlagsIntegration,
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logger,
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} from '@sentry/core';

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