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https://github.com/FJurmanovic/sugarr.git
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The previous cached-tokens commit added cache_read_input_tokens (a flat-schema key) alongside prompt_tokens/completion_tokens (OpenAI's native schema) in the same usageDetails object. Langfuse's ingestion explicitly does not support mixing those two schemas, and doing so broke generation.update()'s output field - confirmed live: prompt/ response content was landing in the Usage panel instead of Input/ Output. Fixed by staying entirely within OpenAI's native schema: cached tokens now nest under prompt_tokens_details.cached_tokens instead of using the flat cache_read_input_tokens key. Cast past the installed @langfuse/tracing SDK's usageDetails type (which only exposes a 3-field camelCase shape with no _details nesting, unlike the wire schema in @langfuse/core) since the nesting is valid on the wire even though the SDK's public type doesn't model it. Verified: full suite (82/82) passing, tsc/eslint clean.
134 lines
5.2 KiB
TypeScript
134 lines
5.2 KiB
TypeScript
import { describe, expect, it, vi } from 'vitest';
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const {
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forceFlush,
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shutdown,
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sdkStart,
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sdkShutdown,
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generationUpdate,
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generationEnd,
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childStartObservation,
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startObservation,
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propagateAttributes,
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} = vi.hoisted(() => {
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const generationUpdate = vi.fn();
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const generationEnd = vi.fn();
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const generation = { update: generationUpdate, end: generationEnd };
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const childStartObservation = vi.fn().mockReturnValue(generation);
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const rootSpan = { traceId: 'lf-trace-1', startObservation: childStartObservation };
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return {
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forceFlush: vi.fn().mockResolvedValue(undefined),
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shutdown: vi.fn().mockResolvedValue(undefined),
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sdkStart: vi.fn(),
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sdkShutdown: vi.fn().mockResolvedValue(undefined),
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generationUpdate,
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generationEnd,
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childStartObservation,
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startObservation: vi.fn().mockReturnValue(rootSpan),
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propagateAttributes: vi.fn().mockImplementation((_attrs: unknown, fn: () => unknown) => fn()),
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};
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});
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vi.mock('@langfuse/otel', () => ({
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LangfuseSpanProcessor: vi.fn().mockImplementation(() => ({ forceFlush, shutdown })),
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}));
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vi.mock('@opentelemetry/sdk-node', () => ({
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NodeSDK: vi.fn().mockImplementation(() => ({ start: sdkStart, shutdown: sdkShutdown })),
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}));
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vi.mock('@langfuse/tracing', () => ({ startObservation, propagateAttributes }));
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import { LangfuseTracer } from '../../../src/core/langfuse/LangfuseTracer';
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describe('LangfuseTracer', () => {
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it('starts the OTEL SDK with a LangfuseSpanProcessor on construction', () => {
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new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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expect(sdkStart).toHaveBeenCalled();
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});
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it('starts a root observation and exposes its trace id', () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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const handle = tracer.startTrace('my-pipeline', { foo: 'bar' });
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expect(startObservation).toHaveBeenCalledWith('my-pipeline', { metadata: { foo: 'bar' } });
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expect(handle.id).toBe('lf-trace-1');
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});
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it('startGeneration creates a child generation observation and end() forwards output/usage', () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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const handle = tracer.startTrace('my-pipeline');
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const gen = handle.startGeneration({ name: 'step-1', model: 'llama3', input: ['hi'] });
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gen.end({
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output: 'done',
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usage: { promptTokens: 10, completionTokens: 5, totalTokens: 15 },
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});
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expect(childStartObservation).toHaveBeenCalledWith(
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'step-1',
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expect.objectContaining({ model: 'llama3', input: ['hi'] }),
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{ asType: 'generation' }
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);
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expect(generationUpdate).toHaveBeenCalledWith(
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expect.objectContaining({
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output: 'done',
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usageDetails: { prompt_tokens: 10, completion_tokens: 5, total_tokens: 15 },
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})
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);
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expect(generationEnd).toHaveBeenCalledTimes(1);
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});
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it('maps cachedTokens to the OpenAI-native nested prompt_tokens_details.cached_tokens, not a mixed flat key', () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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const handle = tracer.startTrace('my-pipeline');
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const gen = handle.startGeneration({ name: 'step-1', model: 'gpt-4o-mini', input: ['hi'] });
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gen.end({
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output: 'done',
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usage: { promptTokens: 100, completionTokens: 20, totalTokens: 120, cachedTokens: 80 },
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});
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expect(generationUpdate).toHaveBeenCalledWith(
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expect.objectContaining({
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usageDetails: {
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prompt_tokens: 100,
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completion_tokens: 20,
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total_tokens: 120,
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prompt_tokens_details: { cached_tokens: 80 },
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},
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})
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);
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});
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it('omits usageDetails entirely when no usage is reported', () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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const handle = tracer.startTrace('my-pipeline');
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const gen = handle.startGeneration({ name: 'step-1', model: 'llama3', input: ['hi'] });
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gen.end({ output: 'done' });
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expect(generationUpdate).toHaveBeenCalledWith(expect.objectContaining({ usageDetails: undefined }));
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});
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it('flush() force-flushes the span processor without shutting down the SDK', async () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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await tracer.flush();
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expect(forceFlush).toHaveBeenCalledTimes(1);
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expect(sdkShutdown).not.toHaveBeenCalled();
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});
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it('shutdown() shuts down the underlying OTEL SDK', async () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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await tracer.shutdown();
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expect(sdkShutdown).toHaveBeenCalledTimes(1);
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});
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it('runWithSession propagates sessionId/tags to the callback via propagateAttributes and returns its result', async () => {
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const tracer = new LangfuseTracer({ publicKey: 'pk', secretKey: 'sk', baseUrl: 'http://lf' });
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const fn = vi.fn().mockResolvedValue('done');
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const result = await tracer.runWithSession({ sessionId: 'session-1', tags: ['cron'] }, fn);
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expect(propagateAttributes).toHaveBeenCalledWith({ sessionId: 'session-1', tags: ['cron'] }, fn);
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expect(result).toBe('done');
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});
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});
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