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-cost-table.ts

@@ -0,0 +1,106 @@
+/**
+ * LLM Cost Table
+ *
+ * Maps model names to per-token costs in microdollars (USD * 1,000,000).
+ * For example, $0.003 per 1K tokens = 3,000 microdollars per 1K tokens = 3 microdollars per token.
+ *
+ * Costs are split into input (prompt) and output (completion) pricing.
+ * Ollama models run locally and are free (0 cost).
+ */
+
+/**
+ * Per-token cost in microdollars for a single model.
+ */
+export interface ModelCost {
+  /** Cost per input token in microdollars */
+  inputPerToken: number;
+  /** Cost per output token in microdollars */
+  outputPerToken: number;
+}
+
+/**
+ * Cost table mapping model name prefixes to per-token pricing.
+ *
+ * Model matching is prefix-based: "claude-sonnet-4-5" matches "claude-sonnet-4-5-20250929".
+ * More specific prefixes are checked first (longest match wins).
+ *
+ * Prices sourced from provider pricing pages as of 2026-02.
+ */
+const MODEL_COSTS: Record<string, ModelCost> = {
+  // Anthropic Claude models (per-token microdollars)
+  // claude-sonnet-4-5: $3/M input, $15/M output
+  "claude-sonnet-4-5": { inputPerToken: 3, outputPerToken: 15 },
+  // claude-opus-4: $15/M input, $75/M output
+  "claude-opus-4": { inputPerToken: 15, outputPerToken: 75 },
+  // claude-3-5-haiku / claude-haiku-4-5: $0.80/M input, $4/M output
+  "claude-haiku-4-5": { inputPerToken: 0.8, outputPerToken: 4 },
+  "claude-3-5-haiku": { inputPerToken: 0.8, outputPerToken: 4 },
+  // claude-3-5-sonnet: $3/M input, $15/M output
+  "claude-3-5-sonnet": { inputPerToken: 3, outputPerToken: 15 },
+  // claude-3-opus: $15/M input, $75/M output
+  "claude-3-opus": { inputPerToken: 15, outputPerToken: 75 },
+  // claude-3-sonnet: $3/M input, $15/M output
+  "claude-3-sonnet": { inputPerToken: 3, outputPerToken: 15 },
+  // claude-3-haiku: $0.25/M input, $1.25/M output
+  "claude-3-haiku": { inputPerToken: 0.25, outputPerToken: 1.25 },
+
+  // OpenAI models (per-token microdollars)
+  // gpt-4o: $2.50/M input, $10/M output
+  "gpt-4o-mini": { inputPerToken: 0.15, outputPerToken: 0.6 },
+  "gpt-4o": { inputPerToken: 2.5, outputPerToken: 10 },
+  // gpt-4-turbo: $10/M input, $30/M output
+  "gpt-4-turbo": { inputPerToken: 10, outputPerToken: 30 },
+  // gpt-4: $30/M input, $60/M output
+  "gpt-4": { inputPerToken: 30, outputPerToken: 60 },
+  // gpt-3.5-turbo: $0.50/M input, $1.50/M output
+  "gpt-3.5-turbo": { inputPerToken: 0.5, outputPerToken: 1.5 },
+
+  // Ollama / local models: free
+  // These are catch-all entries; any model not matched above falls through to getModelCost default
+};
+
+/**
+ * Sorted model prefixes from longest to shortest for greedy prefix matching.
+ * Ensures "gpt-4o-mini" matches before "gpt-4o" and "claude-3-5-haiku" before "claude-3-haiku".
+ */
+const SORTED_PREFIXES = Object.keys(MODEL_COSTS).sort((a, b) => b.length - a.length);
+
+/**
+ * Look up per-token cost for a given model name.
+ *
+ * Uses longest-prefix matching: the model name is compared against known
+ * prefixes from longest to shortest. If no prefix matches, returns zero cost
+ * (assumes local/free model).
+ *
+ * @param modelName - Full model name (e.g. "claude-sonnet-4-5-20250929", "gpt-4o")
+ * @returns Per-token cost in microdollars
+ */
+export function getModelCost(modelName: string): ModelCost {
+  const normalized = modelName.toLowerCase();
+
+  for (const prefix of SORTED_PREFIXES) {
+    if (normalized.startsWith(prefix)) {
+      return MODEL_COSTS[prefix];
+    }
+  }
+
+  // Unknown or local model — assume free
+  return { inputPerToken: 0, outputPerToken: 0 };
+}
+
+/**
+ * Calculate total cost in microdollars for a given model and token counts.
+ *
+ * @param modelName - Full model name
+ * @param inputTokens - Number of input (prompt) tokens
+ * @param outputTokens - Number of output (completion) tokens
+ * @returns Total cost in microdollars (USD * 1,000,000)
+ */
+export function calculateCostMicrodollars(
+  modelName: string,
+  inputTokens: number,
+  outputTokens: number
+): number {
+  const cost = getModelCost(modelName);
+  return Math.round(cost.inputPerToken * inputTokens + cost.outputPerToken * outputTokens);
+}