@nghyane/omp-stats

Local observability dashboard for AI usage statistics.

Features

• Session log parsing: Reads JSONL session logs from ~/.omp/agent/sessions/
• SQLite aggregation: Efficient stats storage and querying using bun:sqlite
• Web dashboard: Real-time metrics visualization with Chart.js
• Incremental sync: Only processes new/modified log entries

Metrics Tracked

| Metric | Calculation | |--------|-------------| | Tokens/s | output_tokens / (duration / 1000) | | Cache Rate | cache_read / (input + cache_read) * 100 | | Error Rate | count(stopReason=error) / total_calls * 100 | | Total Cost | Sum of usage.cost.total | | Avg Latency | Mean of duration | | TTFT | Mean of ttft (time to first token) |

Usage

Via CLI

# Start dashboard server (default: http://localhost:3847)
omp stats

# Custom port
omp stats --port 8080

# Print summary to console
omp stats --summary

# Output as JSON (for scripting)
omp stats --json

Programmatic

import { getDashboardStats, syncAllSessions } from "@nghyane/omp-stats";

// Sync session logs to database
const { processed, files } = await syncAllSessions();

// Get aggregated stats
const stats = await getDashboardStats();
console.log(stats.overall.totalCost);
console.log(stats.byModel[0].avgTokensPerSecond);

API Endpoints

| Endpoint | Description | |----------|-------------| | GET /api/stats | Overall stats with all breakdowns | | GET /api/stats/models | Per-model statistics | | GET /api/stats/folders | Per-folder/project statistics | | GET /api/stats/timeseries | Hourly time series data | | GET /api/sync | Trigger sync and return counts |

Data Storage

• Session logs: ~/.omp/agent/sessions/ (JSONL files)
• Stats database: ~/.omp/stats.db (SQLite)

Dashboard

The web dashboard provides:

• Overall metrics cards (requests, cost, cache rate, error rate, duration, tokens/s)
• Time series chart showing requests and errors over time
• Per-model breakdown table
• Per-folder breakdown table
• Auto-refresh every 30 seconds

License

MIT