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2253d05618
Remove the nested v3/ subdirectory by moving all active source code, tests, configs, and assets directly to the project root. Archive v2/ (dead code, 847MB) to v2-archive.tar.gz. Key changes: - Move v3/src/ → src/, v3/tests/ → tests/, v3/packages/ → packages/ - Move v3/tsconfig.json, v3/vitest.config.ts to root - Merge v3/package.json into root package.json (ESM, scripts, deps, exports) - Merge v3/scripts/ into scripts/, v3/implementation/ into docs/implementation/ - Update all CI workflows to remove "cd v3 &&" and v3/ path prefixes - Fix all init installer path resolution (3-level-up → 2-level-up) - Fix hooks to use "node ./dist/cli/bundle.js" instead of bare "aqe" - Update settings.json ADR/DDD directories to docs/implementation/ - Fix helper scripts (statusline, adr-compliance, ddd-tracker, guidance-hooks) - Update 58 agent definitions: aqe/v3/ → aqe/ memory namespaces - Update 15 guidance shards: v3/src/ → src/ path references - Fix sync interfaces: remove v3/ and v2/ path references - Fix test path calculations (process.cwd() + '..' no longer needed) - Fix flaky perf test threshold (500ms → 1000ms for CI environments) - Fix complexity-analyzer test to match ADR-051 keyword-based eligibility Build passes, 17,901 tests pass, CLI and MCP bundles verified. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
356 lines
12 KiB
TypeScript
356 lines
12 KiB
TypeScript
/**
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* End-to-End Integration Tests: ADR-042 Token Tracking
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*
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* These tests verify the REAL integration flow:
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* 1. LLM Providers -> TokenMetricsCollector (via HTTP mock)
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* 2. EarlyExitTokenOptimizer -> Pattern Store
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* 3. CLI Commands -> TokenMetricsCollector
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* 4. Persistence -> File System
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*/
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import { describe, it, expect, beforeEach, afterEach, vi } from 'vitest';
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import { TokenMetricsCollector } from '../../src/learning/token-tracker.js';
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import { ClaudeProvider } from '../../src/shared/llm/providers/claude.js';
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import { OpenAIProvider } from '../../src/shared/llm/providers/openai.js';
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import { OllamaProvider } from '../../src/shared/llm/providers/ollama.js';
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import * as fs from 'fs';
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import * as path from 'path';
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// Mock fetch at the HTTP level (not at the provider level)
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const mockFetch = vi.fn();
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global.fetch = mockFetch;
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describe('ADR-042: End-to-End Token Tracking Integration', () => {
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beforeEach(() => {
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TokenMetricsCollector.reset();
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mockFetch.mockReset();
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});
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afterEach(() => {
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vi.restoreAllMocks();
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});
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describe('LLM Provider Integration (HTTP-level mock)', () => {
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it('should track tokens when ClaudeProvider.generate() is called', async () => {
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// Setup: Mock Claude API response at HTTP level
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mockFetch.mockResolvedValueOnce({
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ok: true,
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json: async () => ({
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id: 'msg-123',
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type: 'message',
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role: 'assistant',
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content: [{ type: 'text', text: 'Hello, world!' }],
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model: 'claude-sonnet-4-20250514',
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stop_reason: 'end_turn',
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usage: {
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input_tokens: 50,
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output_tokens: 25,
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},
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}),
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});
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// Act: Call the provider (this should trigger TokenMetricsCollector)
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const provider = new ClaudeProvider({ apiKey: 'test-key' });
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const result = await provider.generate('Hello');
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// Assert: Verify tokens were tracked
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expect(result.usage.promptTokens).toBe(50);
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expect(result.usage.completionTokens).toBe(25);
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expect(result.usage.totalTokens).toBe(75);
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// Verify TokenMetricsCollector captured the usage
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const agentMetrics = TokenMetricsCollector.getAgentMetrics('claude-provider');
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expect(agentMetrics).toBeDefined();
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expect((agentMetrics as any).totalTokens).toBe(75);
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expect((agentMetrics as any).totalInputTokens).toBe(50);
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expect((agentMetrics as any).totalOutputTokens).toBe(25);
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});
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it('should track tokens when OpenAIProvider.generate() is called', async () => {
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// Setup: Mock OpenAI API response
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mockFetch.mockResolvedValueOnce({
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ok: true,
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json: async () => ({
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id: 'chatcmpl-123',
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object: 'chat.completion',
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created: Date.now(),
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model: 'gpt-4o',
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choices: [{
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index: 0,
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message: { role: 'assistant', content: 'Test response' },
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finish_reason: 'stop',
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}],
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usage: {
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prompt_tokens: 100,
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completion_tokens: 50,
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total_tokens: 150,
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},
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}),
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});
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// Act
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const provider = new OpenAIProvider({ apiKey: 'test-key' });
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const result = await provider.generate('Hello OpenAI');
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// Assert
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expect(result.usage.totalTokens).toBe(150);
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const agentMetrics = TokenMetricsCollector.getAgentMetrics('openai-provider');
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expect(agentMetrics).toBeDefined();
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expect((agentMetrics as any).totalTokens).toBe(150);
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});
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it('should track tokens when OllamaProvider.generate() is called', async () => {
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// Setup: Mock Ollama API response
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mockFetch.mockResolvedValueOnce({
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ok: true,
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json: async () => ({
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model: 'llama3.1',
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created_at: new Date().toISOString(),
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response: 'Local LLM response',
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done: true,
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prompt_eval_count: 80,
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eval_count: 40,
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}),
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});
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// Act
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const provider = new OllamaProvider();
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const result = await provider.generate('Hello Ollama');
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// Assert
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expect(result.usage.promptTokens).toBe(80);
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expect(result.usage.completionTokens).toBe(40);
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const agentMetrics = TokenMetricsCollector.getAgentMetrics('ollama-provider');
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expect(agentMetrics).toBeDefined();
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expect((agentMetrics as any).totalTokens).toBe(120);
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});
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it('should aggregate tokens from multiple providers', async () => {
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// Setup: Mock both providers
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mockFetch
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.mockResolvedValueOnce({
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ok: true,
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json: async () => ({
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id: 'msg-1',
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type: 'message',
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role: 'assistant',
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content: [{ type: 'text', text: 'Claude' }],
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model: 'claude-sonnet-4-20250514',
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stop_reason: 'end_turn',
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usage: { input_tokens: 100, output_tokens: 50 },
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}),
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})
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.mockResolvedValueOnce({
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ok: true,
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json: async () => ({
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id: 'chatcmpl-1',
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object: 'chat.completion',
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choices: [{ message: { role: 'assistant', content: 'GPT' }, finish_reason: 'stop' }],
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usage: { prompt_tokens: 200, completion_tokens: 100, total_tokens: 300 },
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}),
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});
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// Act
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const claude = new ClaudeProvider({ apiKey: 'test' });
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const openai = new OpenAIProvider({ apiKey: 'test' });
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await claude.generate('Test Claude');
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await openai.generate('Test OpenAI');
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// Assert: Session summary should include both
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const summary = TokenMetricsCollector.getSessionSummary();
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expect(summary.totalUsage.totalTokens).toBe(450); // 150 + 300
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expect(summary.byAgent.size).toBe(2);
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expect(summary.byAgent.get('claude-provider')?.totalTokens).toBe(150);
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expect(summary.byAgent.get('openai-provider')?.totalTokens).toBe(300);
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});
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});
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describe('Persistence Integration', () => {
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const testFilePath = '/tmp/test-token-metrics.json';
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beforeEach(() => {
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// Configure persistence with test file
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TokenMetricsCollector.configurePersistence({
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filePath: testFilePath,
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autoSaveIntervalMs: 0, // Disable auto-save for tests
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});
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// Clean up test file
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if (fs.existsSync(testFilePath)) {
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fs.unlinkSync(testFilePath);
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}
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});
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afterEach(() => {
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// Clean up
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if (fs.existsSync(testFilePath)) {
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fs.unlinkSync(testFilePath);
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}
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});
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it('should save metrics to file', async () => {
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// Record some usage
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TokenMetricsCollector.recordTokenUsage('task-1', 'agent-1', 'test', 'op', {
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inputTokens: 100,
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outputTokens: 50,
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totalTokens: 150,
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});
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// Save
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await TokenMetricsCollector.save();
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// Verify file exists
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expect(fs.existsSync(testFilePath)).toBe(true);
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// Verify content
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const content = JSON.parse(fs.readFileSync(testFilePath, 'utf-8'));
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expect(content.version).toBe('1.0.0');
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expect(content.taskMetrics.length).toBe(1);
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expect(content.taskMetrics[0].usage.totalTokens).toBe(150);
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});
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it('should load metrics from file', async () => {
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// Create a persisted file
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const persistedData = {
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version: '1.0.0',
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sessionId: 'old-session',
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sessionStartTime: Date.now() - 3600000,
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taskMetrics: [
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{
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taskId: 'old-task',
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agentId: 'old-agent',
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domain: 'historical',
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operation: 'test',
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timestamp: Date.now() - 3600000,
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usage: {
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inputTokens: 500,
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outputTokens: 250,
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totalTokens: 750,
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},
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patternReused: false,
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},
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],
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optimizationStats: {
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cacheHits: 5,
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earlyExits: 3,
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totalTokensSaved: 1000,
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totalPatternsReused: 2,
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},
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lastSavedAt: Date.now() - 3600000,
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};
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fs.writeFileSync(testFilePath, JSON.stringify(persistedData));
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// Load
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const loaded = await TokenMetricsCollector.load();
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expect(loaded).toBe(true);
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// Verify historical data is loaded
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const summary = TokenMetricsCollector.getSessionSummary();
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expect(summary.optimizationStats.cacheHits).toBeGreaterThanOrEqual(5);
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expect(summary.optimizationStats.tokensSaved).toBeGreaterThanOrEqual(1000);
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// Verify metrics are merged
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const tasks = TokenMetricsCollector.getTaskMetrics();
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expect(tasks.length).toBeGreaterThanOrEqual(1);
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});
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it('should track dirty state correctly', async () => {
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expect(TokenMetricsCollector.hasUnsavedChanges()).toBe(false);
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// Record usage
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TokenMetricsCollector.recordTokenUsage('task-1', 'agent-1', 'test', 'op', {
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inputTokens: 100,
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outputTokens: 50,
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totalTokens: 150,
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});
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expect(TokenMetricsCollector.hasUnsavedChanges()).toBe(true);
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// Save
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await TokenMetricsCollector.save();
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expect(TokenMetricsCollector.hasUnsavedChanges()).toBe(false);
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});
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});
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describe('Token Savings Tracking', () => {
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it('should track pattern reuse correctly', () => {
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// Simulate pattern reuse flow
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TokenMetricsCollector.recordPatternReuse('task-1', 500);
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TokenMetricsCollector.recordPatternReuse('task-2', 300);
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const summary = TokenMetricsCollector.getSessionSummary();
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expect(summary.optimizationStats.tokensSaved).toBe(800);
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expect(summary.optimizationStats.patternsReused).toBe(2);
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});
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it('should track early exits correctly', () => {
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TokenMetricsCollector.recordEarlyExit(400);
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TokenMetricsCollector.recordEarlyExit(200);
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const summary = TokenMetricsCollector.getSessionSummary();
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expect(summary.optimizationStats.earlyExits).toBe(2);
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expect(summary.optimizationStats.tokensSaved).toBe(600);
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});
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it('should calculate savings percentage correctly', () => {
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// Record actual usage
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TokenMetricsCollector.recordTokenUsage('task-1', 'agent-1', 'test', 'op', {
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inputTokens: 500,
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outputTokens: 500,
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totalTokens: 1000,
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});
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// Record savings
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TokenMetricsCollector.recordPatternReuse('task-2', 500);
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TokenMetricsCollector.recordEarlyExit(500);
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const summary = TokenMetricsCollector.getSessionSummary();
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// Total tokens used: 1000
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// Total tokens saved: 1000
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// Savings percentage: 1000 / (1000 + 1000) * 100 = 50%
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expect(summary.optimizationStats.savingsPercentage).toBeCloseTo(50, 1);
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});
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});
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describe('Domain Aggregation', () => {
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it('should aggregate tokens by domain correctly', () => {
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TokenMetricsCollector.recordTokenUsage('t1', 'a1', 'test-generation', 'gen', {
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inputTokens: 100, outputTokens: 50, totalTokens: 150,
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});
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TokenMetricsCollector.recordTokenUsage('t2', 'a1', 'test-generation', 'gen', {
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inputTokens: 200, outputTokens: 100, totalTokens: 300,
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});
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TokenMetricsCollector.recordTokenUsage('t3', 'a2', 'coverage-analysis', 'analyze', {
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inputTokens: 300, outputTokens: 150, totalTokens: 450,
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});
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const domainMetrics = TokenMetricsCollector.getDomainMetrics() as Map<string, any>;
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expect(domainMetrics.get('test-generation')?.totalTokens).toBe(450);
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expect(domainMetrics.get('coverage-analysis')?.totalTokens).toBe(450);
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});
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});
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describe('Efficiency Report', () => {
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it('should generate recommendations based on usage patterns', () => {
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// Record many tasks without pattern reuse
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for (let i = 0; i < 25; i++) {
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TokenMetricsCollector.recordTokenUsage(`task-${i}`, 'agent-1', 'test-generation', 'gen', {
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inputTokens: 100, outputTokens: 100, totalTokens: 200,
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});
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}
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const report = TokenMetricsCollector.getTokenEfficiency();
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expect(report.recommendations.length).toBeGreaterThan(0);
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// Should recommend enabling pattern reuse since rate is 0%
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expect(report.recommendations.some(r => r.includes('pattern'))).toBe(true);
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// Should recommend early exit since none used
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expect(report.recommendations.some(r => r.includes('Early exit') || r.includes('exit'))).toBe(true);
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});
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});
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});
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