mirror of
https://github.com/open-jarvis/OpenJarvis.git
synced 2026-07-30 10:52:15 +00:00
Jon Saad-FalconandClaude Opus 4.6
24972e3e52
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>
121 lines
2.8 KiB
TOML
121 lines
2.8 KiB
TOML
[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[project]
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name = "openjarvis"
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version = "1.0.0"
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description = "OpenJarvis — modular AI assistant backend with composable intelligence pillars"
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readme = "README.md"
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requires-python = ">=3.10"
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dependencies = [
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"click>=8",
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"httpx>=0.27",
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"pynvml>=13.0.1",
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"rich>=13",
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"tomli>=2.0; python_version < '3.11'",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=8",
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"pytest-asyncio>=0.24",
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"pytest-cov>=5",
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"respx>=0.22",
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"ruff>=0.4",
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]
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inference-ollama = []
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inference-vllm = []
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inference-llamacpp = []
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inference-mlx = ["mlx-lm>=0.19; sys_platform == 'darwin'"]
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inference-cloud = [
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"openai>=1.30",
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"anthropic>=0.30",
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]
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inference-google = [
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"google-genai>=1.0",
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]
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inference-litellm = ["litellm>=1.40"]
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tools-search = [
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"tavily-python>=0.3",
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]
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memory-faiss = [
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"faiss-cpu>=1.7",
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"sentence-transformers>=2.2",
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"numpy>=1.24",
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]
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memory-colbert = [
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"colbert-ai>=0.2",
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"torch>=2.0",
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]
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memory-pdf = ["pdfplumber>=0.10"]
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memory-bm25 = ["rank-bm25>=0.2.2"]
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server = [
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"fastapi>=0.110",
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"uvicorn>=0.30",
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"pydantic>=2.0",
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]
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agents = []
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openhands = ["openhands-sdk>=1.0; python_version >= '3.12'"]
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claude-code = []
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gpu-metrics = ["pynvml>=12.0"]
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energy-amd = ["amdsmi>=6.1"]
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energy-apple = ["zeus-ml[apple]"]
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energy-all = ["pynvml>=12.0", "amdsmi>=6.1", "zeus-ml[apple]"]
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learning = []
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orchestrator-training = ["torch>=2.0", "transformers>=4.40"]
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channel-telegram = ["python-telegram-bot>=21.0"]
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channel-discord = ["discord.py>=2.3"]
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channel-slack = ["slack-sdk>=3.27"]
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channel-webhook = []
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channel-email = []
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channel-whatsapp = []
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channel-signal = []
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channel-google-chat = []
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channel-irc = []
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channel-webchat = []
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channel-teams = []
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channel-matrix = []
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channel-mattermost = []
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channel-feishu = []
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channel-bluebubbles = []
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channel-whatsapp-baileys = []
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scheduler = ["croniter>=2.0"]
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docs = [
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"mkdocs>=1.6",
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"mkdocs-material>=9.5",
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"mkdocstrings[python]>=0.25",
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]
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[project.scripts]
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jarvis = "openjarvis.cli:main"
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[tool.hatch.build.targets.wheel]
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packages = ["src/openjarvis"]
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[tool.hatch.build.targets.wheel.force-include]
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"src/openjarvis/agents/claude_code_runner" = "openjarvis/agents/claude_code_runner"
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"src/openjarvis/channels/whatsapp_baileys_bridge" = "openjarvis/channels/whatsapp_baileys_bridge"
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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markers = [
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"live: requires running inference engine",
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"cloud: requires cloud API keys",
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"nvidia: requires NVIDIA GPU",
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"amd: requires AMD GPU",
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"apple: requires Apple Silicon",
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"slow: long-running test",
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]
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[tool.ruff]
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target-version = "py310"
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src = ["src", "tests"]
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[tool.ruff.lint]
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select = ["E", "F", "I", "W"]
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[tool.ruff.lint.per-file-ignores]
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"evals/datasets/*.py" = ["E501"]
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"evals/scorers/*.py" = ["E501"]
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