mistral-observability

# Mistral AI Observability ## Overview Monitor Mistral AI API usage, latency, token consumption, error rates, and costs. Covers instrumented client wrapper, Prometheus metrics, Grafana dashboard panels, alerting rules, and structured logging. ## Prerequisites - Mistral API integration in production - Prometheus or OpenTelemetry-compatible metrics backend - Alerting system (Alertmanager, PagerDuty, or similar) ## Instructions ### Step 1: Instrumented Client Wrapper ```typescript import { Mistral } from '@mistralai/mistralai'; const PRICING: Record<string, { input: number; output: number }> = { 'mistral-small-latest': { input: 0.10, output: 0.30 }, 'mistral-large-latest': { input: 0.50, output: 1.50 }, 'codestral-latest': { input: 0.30, output: 0.90 }, 'mistral-embed': { input: 0.10, output: 0 }, }; interface MetricsEvent { model: string; endpoint: string; durationMs: number; status: 'success' | 'error'; statusCode?: number; inputTokens?: number; outputTokens?: number; costUsd?: number; } function emitMetrics(event: MetricsEvent): void { // Push to your metrics backend (Prometheus, Datadog, etc.) console.log(JSON.stringify({ type: 'mistral_metric', ...event })); } async function instrumentedChat( client: Mistral, model: string, messages: any[], options?: any, ) { const start = performance.now(); try { const response = await client.chat.complete({ model, messages, ...options }); const duration = Math.round(p...