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feat(core): Add gen_ai.conversation.id attribute to OpenAI and LangGr… (#18703)
This PR adds support for capturing conversation/session identifiers in AI integrations to enable linking messages across API calls. ## Changes ### OpenAI - Added instrumentation for the Conversations API (`conversations.create`) - Captures `gen_ai.conversation.id` from: - `conversation` parameter in `responses.create` - `previous_response_id` parameter for response chaining - Response object from `conversations.create` ### LangGraph - Captures `gen_ai.conversation.id` from `config.configurable.thread_id` when invoking agents Closes #18702
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‎dev-packages/node-integration-tests/suites/tracing/langgraph/scenario-thread-id.mjs‎

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import { END, MessagesAnnotation, START, StateGraph } from '@langchain/langgraph';
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import * as Sentry from '@sentry/node';
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async function run() {
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await Sentry.startSpan({ op: 'function', name: 'langgraph-thread-id-test' }, async () => {
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// Define a simple mock LLM function
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const mockLlm = () => {
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return {
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messages: [
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{
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role: 'assistant',
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content: 'Mock LLM response',
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response_metadata: {
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model_name: 'mock-model',
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finish_reason: 'stop',
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tokenUsage: {
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promptTokens: 20,
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completionTokens: 10,
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totalTokens: 30,
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},
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},
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},
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],
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};
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};
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// Create and compile the graph
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const graph = new StateGraph(MessagesAnnotation)
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.addNode('agent', mockLlm)
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.addEdge(START, 'agent')
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.addEdge('agent', END)
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.compile({ name: 'thread_test_agent' });
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// Test 1: Invoke with thread_id in config
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await graph.invoke(
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{
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messages: [{ role: 'user', content: 'Hello with thread ID' }],
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},
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{
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configurable: {
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thread_id: 'thread_abc123_session_1',
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},
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},
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);
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// Test 2: Invoke with different thread_id (simulating different conversation)
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await graph.invoke(
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{
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messages: [{ role: 'user', content: 'Different conversation' }],
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},
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{
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configurable: {
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thread_id: 'thread_xyz789_session_2',
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},
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},
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);
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// Test 3: Invoke without thread_id (should not have gen_ai.conversation.id)
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await graph.invoke({
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messages: [{ role: 'user', content: 'No thread ID here' }],
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});
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});
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await Sentry.flush(2000);
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}
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run();

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

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@@ -205,4 +205,72 @@ describe('LangGraph integration', () => {
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await createRunner().ignore('event').expect({ transaction: EXPECTED_TRANSACTION_WITH_TOOLS }).start().completed();
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});
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});
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// Test for thread_id (conversation ID) support
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const EXPECTED_TRANSACTION_THREAD_ID = {
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transaction: 'langgraph-thread-id-test',
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spans: expect.arrayContaining([
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// create_agent span
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expect.objectContaining({
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data: {
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'gen_ai.operation.name': 'create_agent',
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'sentry.op': 'gen_ai.create_agent',
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'sentry.origin': 'auto.ai.langgraph',
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'gen_ai.agent.name': 'thread_test_agent',
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},
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description: 'create_agent thread_test_agent',
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op: 'gen_ai.create_agent',
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origin: 'auto.ai.langgraph',
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status: 'ok',
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}),
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// First invoke_agent span with thread_id
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expect.objectContaining({
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data: expect.objectContaining({
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'gen_ai.operation.name': 'invoke_agent',
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'sentry.op': 'gen_ai.invoke_agent',
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'sentry.origin': 'auto.ai.langgraph',
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'gen_ai.agent.name': 'thread_test_agent',
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'gen_ai.pipeline.name': 'thread_test_agent',
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// The thread_id should be captured as conversation.id
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'gen_ai.conversation.id': 'thread_abc123_session_1',
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}),
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description: 'invoke_agent thread_test_agent',
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op: 'gen_ai.invoke_agent',
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origin: 'auto.ai.langgraph',
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status: 'ok',
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}),
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// Second invoke_agent span with different thread_id
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expect.objectContaining({
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data: expect.objectContaining({
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'gen_ai.operation.name': 'invoke_agent',
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'sentry.op': 'gen_ai.invoke_agent',
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'sentry.origin': 'auto.ai.langgraph',
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'gen_ai.agent.name': 'thread_test_agent',
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'gen_ai.pipeline.name': 'thread_test_agent',
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// Different thread_id for different conversation
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'gen_ai.conversation.id': 'thread_xyz789_session_2',
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}),
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description: 'invoke_agent thread_test_agent',
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op: 'gen_ai.invoke_agent',
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origin: 'auto.ai.langgraph',
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status: 'ok',
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}),
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// Third invoke_agent span without thread_id (should NOT have gen_ai.conversation.id)
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expect.objectContaining({
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data: expect.not.objectContaining({
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'gen_ai.conversation.id': expect.anything(),
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}),
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description: 'invoke_agent thread_test_agent',
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op: 'gen_ai.invoke_agent',
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origin: 'auto.ai.langgraph',
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status: 'ok',
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}),
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]),
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};
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createEsmAndCjsTests(__dirname, 'scenario-thread-id.mjs', 'instrument.mjs', (createRunner, test) => {
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test('should capture thread_id as gen_ai.conversation.id', async () => {
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await createRunner().ignore('event').expect({ transaction: EXPECTED_TRANSACTION_THREAD_ID }).start().completed();
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});
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});
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});

‎dev-packages/node-integration-tests/suites/tracing/openai/scenario-conversation.mjs‎

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import * as Sentry from '@sentry/node';
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import express from 'express';
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import OpenAI from 'openai';
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function startMockServer() {
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const app = express();
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app.use(express.json());
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// Conversations API endpoint - create conversation
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app.post('/openai/conversations', (req, res) => {
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res.send({
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id: 'conv_689667905b048191b4740501625afd940c7533ace33a2dab',
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object: 'conversation',
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created_at: 1704067200,
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metadata: {},
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});
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});
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// Responses API endpoint - with conversation support
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app.post('/openai/responses', (req, res) => {
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const { model, conversation, previous_response_id } = req.body;
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res.send({
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id: 'resp_mock_conv_123',
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object: 'response',
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created_at: 1704067210,
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model: model,
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output: [
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{
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type: 'message',
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id: 'msg_mock_output_1',
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status: 'completed',
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role: 'assistant',
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content: [
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{
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type: 'output_text',
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text: `Response with conversation: ${conversation || 'none'}, previous_response_id: ${previous_response_id || 'none'}`,
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annotations: [],
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},
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],
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},
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],
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output_text: `Response with conversation: ${conversation || 'none'}`,
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status: 'completed',
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usage: {
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input_tokens: 10,
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output_tokens: 15,
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total_tokens: 25,
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},
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});
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});
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return new Promise(resolve => {
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const server = app.listen(0, () => {
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resolve(server);
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});
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});
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}
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async function run() {
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const server = await startMockServer();
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await Sentry.startSpan({ op: 'function', name: 'conversation-test' }, async () => {
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const client = new OpenAI({
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baseURL: `http://localhost:${server.address().port}/openai`,
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apiKey: 'mock-api-key',
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});
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// Test 1: Create a conversation
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const conversation = await client.conversations.create();
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// Test 2: Use conversation ID in responses.create
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await client.responses.create({
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model: 'gpt-4',
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input: 'Hello, this is a conversation test',
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conversation: conversation.id,
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});
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// Test 3: Use previous_response_id for chaining (without formal conversation)
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const firstResponse = await client.responses.create({
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model: 'gpt-4',
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input: 'Tell me a joke',
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});
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await client.responses.create({
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model: 'gpt-4',
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input: 'Explain why that is funny',
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previous_response_id: firstResponse.id,
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});
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});
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server.close();
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}
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run();

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

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});
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},
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);
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// Test for conversation ID support (Conversations API and previous_response_id)
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const EXPECTED_TRANSACTION_CONVERSATION = {
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transaction: 'conversation-test',
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spans: expect.arrayContaining([
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// First span - conversations.create returns conversation object with id
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expect.objectContaining({
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data: expect.objectContaining({
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'gen_ai.operation.name': 'conversations',
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'sentry.op': 'gen_ai.conversations',
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'sentry.origin': 'auto.ai.openai',
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'gen_ai.system': 'openai',
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// The conversation ID should be captured from the response
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'gen_ai.conversation.id': 'conv_689667905b048191b4740501625afd940c7533ace33a2dab',
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}),
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description: 'conversations unknown',
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op: 'gen_ai.conversations',
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origin: 'auto.ai.openai',
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status: 'ok',
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}),
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// Second span - responses.create with conversation parameter
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expect.objectContaining({
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data: expect.objectContaining({
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'gen_ai.operation.name': 'responses',
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'sentry.op': 'gen_ai.responses',
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'sentry.origin': 'auto.ai.openai',
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'gen_ai.system': 'openai',
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'gen_ai.request.model': 'gpt-4',
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// The conversation ID should be captured from the request
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'gen_ai.conversation.id': 'conv_689667905b048191b4740501625afd940c7533ace33a2dab',
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}),
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op: 'gen_ai.responses',
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origin: 'auto.ai.openai',
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status: 'ok',
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}),
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// Third span - responses.create without conversation (first in chain, should NOT have gen_ai.conversation.id)
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expect.objectContaining({
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data: expect.not.objectContaining({
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'gen_ai.conversation.id': expect.anything(),
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}),
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op: 'gen_ai.responses',
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origin: 'auto.ai.openai',
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status: 'ok',
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}),
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// Fourth span - responses.create with previous_response_id (chaining)
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expect.objectContaining({
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data: expect.objectContaining({
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'gen_ai.operation.name': 'responses',
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'sentry.op': 'gen_ai.responses',
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'sentry.origin': 'auto.ai.openai',
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'gen_ai.system': 'openai',
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'gen_ai.request.model': 'gpt-4',
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// The previous_response_id should be captured as conversation.id
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'gen_ai.conversation.id': 'resp_mock_conv_123',
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}),
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op: 'gen_ai.responses',
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origin: 'auto.ai.openai',
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status: 'ok',
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}),
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]),
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};
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createEsmAndCjsTests(__dirname, 'scenario-conversation.mjs', 'instrument.mjs', (createRunner, test) => {
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test('captures conversation ID from Conversations API and previous_response_id', async () => {
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await createRunner()
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.ignore('event')
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.expect({ transaction: EXPECTED_TRANSACTION_CONVERSATION })
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.start()
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.completed();
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});
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});
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});

‎packages/core/src/tracing/ai/gen-ai-attributes.ts‎

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@@ -154,6 +154,13 @@ export const GEN_AI_AGENT_NAME_ATTRIBUTE = 'gen_ai.agent.name';
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*/
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export const GEN_AI_PIPELINE_NAME_ATTRIBUTE = 'gen_ai.pipeline.name';
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/**
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* The conversation ID for linking messages across API calls
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* For OpenAI Assistants API: thread_id
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* For LangGraph: configurable.thread_id
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*/
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export const GEN_AI_CONVERSATION_ID_ATTRIBUTE = 'gen_ai.conversation.id';
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/**
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* The number of cache creation input tokens used
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*/
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CHAT: 'chat',
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RESPONSES: 'responses',
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EMBEDDINGS: 'embeddings',
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CONVERSATIONS: 'conversations',
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} as const;
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// =============================================================================

‎packages/core/src/tracing/langgraph/index.ts‎

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import { SPAN_STATUS_ERROR } from '../../tracing';
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import {
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GEN_AI_AGENT_NAME_ATTRIBUTE,
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GEN_AI_CONVERSATION_ID_ATTRIBUTE,
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GEN_AI_INVOKE_AGENT_OPERATION_ATTRIBUTE,
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GEN_AI_OPERATION_NAME_ATTRIBUTE,
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GEN_AI_PIPELINE_NAME_ATTRIBUTE,
@@ -113,6 +114,15 @@ function instrumentCompiledGraphInvoke(
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span.updateName(`invoke_agent ${graphName}`);
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}
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// Extract thread_id from the config (second argument)
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// LangGraph uses config.configurable.thread_id for conversation/session linking
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const config = args.length > 1 ? (args[1] as Record<string, unknown> | undefined) : undefined;
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const configurable = config?.configurable as Record<string, unknown> | undefined;
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const threadId = configurable?.thread_id;
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if (threadId && typeof threadId === 'string') {
123+
span.setAttribute(GEN_AI_CONVERSATION_ID_ATTRIBUTE, threadId);
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}
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// Extract available tools from the graph instance
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const tools = extractToolsFromCompiledGraph(graphInstance);
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if (tools) {

‎packages/core/src/tracing/openai/constants.ts‎

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@@ -2,7 +2,15 @@ export const OPENAI_INTEGRATION_NAME = 'OpenAI';
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// https://platform.openai.com/docs/quickstart?api-mode=responses
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// https://platform.openai.com/docs/quickstart?api-mode=chat
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export const INSTRUMENTED_METHODS = ['responses.create', 'chat.completions.create', 'embeddings.create'] as const;
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// https://platform.openai.com/docs/api-reference/conversations
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export const INSTRUMENTED_METHODS = [
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'responses.create',
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'chat.completions.create',
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'embeddings.create',
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// Conversations API - for conversation state management
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// https://platform.openai.com/docs/guides/conversation-state
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'conversations.create',
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] as const;
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export const RESPONSES_TOOL_CALL_EVENT_TYPES = [
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'response.output_item.added',
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'response.function_call_arguments.delta',

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