feat(#371): track LLM task completions via Mosaic Telemetry

- Create LlmTelemetryTrackerService for non-blocking event emission
- Normalize token usage across Anthropic, OpenAI, Ollama providers
- Add cost table with per-token pricing in microdollars
- Instrument chat, chatStream, and embed methods
- Infer task type from calling context
- Aggregate streaming tokens after stream ends with fallback estimation
- Add 69 unit tests for tracker service, cost table, and LLM service

Refs #371

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

apps/api/src/llm/llm.module.ts

@@ -3,13 +3,14 @@ import { LlmController } from "./llm.controller";
 import { LlmProviderAdminController } from "./llm-provider-admin.controller";
 import { LlmService } from "./llm.service";
 import { LlmManagerService } from "./llm-manager.service";
+import { LlmTelemetryTrackerService } from "./llm-telemetry-tracker.service";
 import { PrismaModule } from "../prisma/prisma.module";
 import { LlmUsageModule } from "../llm-usage/llm-usage.module";
 
 @Module({
   imports: [PrismaModule, LlmUsageModule],
   controllers: [LlmController, LlmProviderAdminController],
-  providers: [LlmService, LlmManagerService],
+  providers: [LlmService, LlmManagerService, LlmTelemetryTrackerService],
   exports: [LlmService, LlmManagerService],
 })
 export class LlmModule {}