Jon Saad-Falcon and Claude Opus 4.6
565282352f
feat(bench): full stats tables in bench CLI
...
Add std_latency to LatencyBenchmark metrics. New _render_stats_table
in bench_cmd.py detects stats-pattern keys (mean_X, p50_X, min_X,
max_X, std_X, p95_X) and renders Avg/Median/Min/Max/Std/P95 columns.
Falls back to simple key-value for non-stats metrics.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-02-28 17:37:02 +00:00
Jon Saad-Falcon and Claude Opus 4.6
24972e3e52
Add Phase 12+13: energy measurement, install polish, PWA, cross-hardware
...
Phase 12 — Energy Measurement Upgrade:
- EnergyMonitor ABC with multi-vendor support (NVIDIA hw counters,
AMD amdsmi, Apple zeus-ml, CPU RAPL sysfs)
- EnergyBatch batch-level energy-per-token accounting
- SteadyStateDetector CV-based thermal equilibrium detection
- EnergyBenchmark with warmup phase
- InstrumentedEngine prefers EnergyMonitor over legacy GpuMonitor
- Telemetry store/aggregator extended with energy fields
Phase 13 — Install, Hosting, Cross-Hardware:
- jarvis doctor diagnostic command (8 checks, --json output)
- jarvis init post-setup guidance with engine-specific next steps
- README Quick Start section
- MLX engine backend (Apple Silicon → mlx recommendation)
- AMD VRAM/multi-GPU detection via rocm-smi
- PyTorch MPS device selection in orchestrator trainers
- PWA support (vite-plugin-pwa, service worker, manifest, icons)
- Server static file serving fix for PWA files
- Dockerfile.gpu.rocm + docker-compose.gpu.rocm.yml for ROCm
- Eval framework display module and efficiency metrics
2244 tests pass, 37 skipped.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-02-26 20:09:07 +00:00
Jon Saad-Falcon and Claude Opus 4.6
301e9cd2d4
Implement OpenJarvis v1.0 — all five pillars, SDK, benchmarks, Docker
...
Complete implementation across six development phases (v0.1 through v1.0):
- Core: Registry system, config, event bus, types (Phase 0)
- Intelligence + Inference: Model routing, Ollama/vLLM/llama.cpp/Cloud engines (Phase 1)
- Memory: SQLite/FAISS/ColBERT/BM25/Hybrid backends, document ingest, context injection (Phase 2)
- Agents: Simple/Orchestrator/Custom/OpenClaw agents, tool system (Phase 3)
- Learning: HeuristicRouter, reward functions, GRPO stub, telemetry aggregation (Phase 4)
- SDK: Jarvis class, OpenClaw protocol/transport, benchmarks, Docker deployment (Phase 5)
520 tests passing, 8 skipped (optional deps). Ruff lint clean.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-02-17 00:52:48 +00:00
