Commit Graph
4 Commits
Author SHA1 Message Date
Jon Saad-FalconandClaude Opus 4.6 2606c283e9 feat(evals): add W&B and Google Sheets result trackers
Introduce ResultTracker ABC with pluggable experiment tracking for the
eval framework, enabling per-sample streaming to W&B and summary-row
appending to Google Sheets — critical for the NeurIPS paper sweep.

- ResultTracker ABC: on_run_start/on_result/on_summary/on_run_end
- WandbTracker: per-sample wandb.log with sample/ prefix, flattened
  MetricStats in run summary, reinit=True for suite mode
- SheetsTracker: summary-only (no per-sample API calls), 29-column
  canonical row, idempotent header, service account + ADC auth
- EvalRunner: trackers wired into lifecycle, all calls try/except
  wrapped so tracker failures never abort an eval run
- CLI: 7 new flags (--wandb-project/entity/tags/group,
  --sheets-id/worksheet/creds) on both jarvis eval run and
  python -m openjarvis.evals run
- Config: tracker fields parsed from TOML [run] section, propagated
  through expand_suite() for suite mode
- pyproject.toml: eval-wandb and eval-sheets optional dependency groups
- 9 new tests (lifecycle, crash resilience, mock W&B/Sheets)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-04 01:00:47 +00:00
Jon Saad-FalconandClaude Opus 4.6 a9518e1574 refactor: move evals/ into src/openjarvis/evals/ as proper subpackage
Move the standalone evals framework from the project root into the
openjarvis package. Rewrite all ~50+ import statements from 'from evals.'
to 'from openjarvis.evals.' across the package, CLI, and tests. Remove
the evals-specific pyproject.toml (no longer a standalone package).
Update ruff per-file-ignores paths and fix line-length violations
introduced by the longer import paths.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-02 21:06:08 +00:00
Jon Saad-FalconandClaude Opus 4.6 2aebcd7d77 feat: Phase 23 — Differentiated functionalities
Trace-driven learning pipeline:
- TrainingDataMiner: extract SFT/routing/agent pairs from traces
- LoRATrainer: fine-tune local models from trace-derived data
- AgentConfigEvolver: rewrite agent configs from trace analysis
- LearningOrchestrator: coordinate mine→train→evolve cycle, wired into SystemBuilder

Eval framework (15 real IPW benchmarks):
- Datasets: SuperGPQA, GPQA, MMLU-Pro, MATH-500, Natural Reasoning, HLE,
  SimpleQA, WildChat, IPW, GAIA, FRAMES, SWE-bench, SWEfficiency,
  TerminalBench, TerminalBench Native
- Scorers: MCQ extraction, LLM-judge, exact match, structural validation
- CLI: jarvis eval list|run|compare|report

Composable abstractions:
- Recipe system: TOML composition of all 5 pillars (3 built-in recipes)
- Agent templates: 15 pre-configured TOML manifests with system prompts
- Bundled skills: 20 ready-to-use TOML skill manifests
- Operator recipes: researcher (4h), correspondent (5min), sentinel (2h)

102 files changed, ~11,500 lines added. 3241 tests pass (44 skipped).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-02 05:34:46 +00:00
Jon Saad-FalconandClaude 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