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OpenJarvis/pyproject.toml
T
Andrew Park e6c47e9532 orchestrator: track the SFT training pipeline and fix ToolOrchestra tracing
The orchestrator SFT pipeline was living entirely in the working tree and
never got committed. One script in that lineage (clean_sft_data.py) has
already been lost with no way to recover it, so track the rest before the
same thing happens again:

  run_sft_fsdp.py      full-parameter FSDP trainer (launched via accelerate)
  sft_tokenize.py      conversation -> tokens + assistant-only masking
  render_sft_data.py   record -> chat-template rendering
  make_splits.py       train / holdout / overfit splits
  chat_orchestrator.py REPL for eyeballing a trained checkpoint's routing
  format_eval_sample.py, upload_to_braintrust.py
  scripts/train/       fsdp4.yaml, fsdp8.yaml, eval sbatch

toolorchestra/tracing.py was also untracked despite being imported by
unified.py and rollout.py, which left the branch broken for a fresh
checkout. Add it along with the rest of the ToolOrchestra package split.

Also here: mmlu_pro / supergpqa scorers, expert pricing for the OpenRouter
Qwen builds (estimates, flagged in-file), an expanded calculator/web_search
tool surface, and the reject-sampling clean gate that run_sft_fsdp reads
via --require-clean.

GRPO is left at its upstream state -- the RL stage hasn't been run yet, so
it stays out of this change. Paths in the sbatch are env-driven rather than
hardcoded to one cluster home.
2026-07-11 12:23:47 -07:00

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[build-system]
requires = ["hatchling", "hatch-vcs"]
build-backend = "hatchling.build"
[project]
name = "OpenJarvis"
dynamic = ["version"]
description = "OpenJarvis — modular AI assistant backend with composable intelligence primitives"
readme = "README.md"
# Upper bound: numpy 2.2.x (pinned transitively via datasets/pandas) ships no
# cp314 Windows wheel, so under Python 3.14 uv would compile numpy from source
# (Meson) and fail on Windows boxes without a C toolchain (#350). Cap to the
# range that has prebuilt wheels; matches the classifiers (3.103.13).
requires-python = ">=3.10,<3.14"
license = {text = "Apache-2.0"}
authors = [
{name = "Open Jarvis Contributors"},
]
classifiers = [
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dependencies = [
"braintrust>=0.0.150",
"click>=8",
"datasets>=4.5.0",
"ddgs>=9.11.4",
"httpx>=0.27",
"openai>=1.30",
"nvidia-ml-py>=12.560.30",
"posthog>=3.0",
"python-telegram-bot>=22.6",
"rich>=13",
"tomli>=2.0; python_version < '3.11'",
"tomlkit>=0.12",
"websockets>=15.0.1",
]
[project.optional-dependencies]
dev = [
"maturin>=1.12.6",
"pytest>=8",
"pytest-asyncio>=0.24",
"pytest-cov>=5",
"pytest-xdist>=3",
"respx>=0.22",
"ruff>=0.4",
"pre-commit>=3.0",
]
inference-mlx = ["mlx-lm>=0.31.1; sys_platform == 'darwin'"]
inference-vllm = ["vllm>=0.16.0"]
inference-cloud = [
"openai>=1.30",
"anthropic>=0.30",
]
inference-google = [
"google-genai>=1.0",
]
inference-litellm = ["litellm>=1.40"]
inference-gemma = ["pygemma>=0.1.3"]
tools-search = [
"tavily-python>=0.3",
"ddgs>=9.11.4",
]
memory-faiss = [
"faiss-cpu>=1.7",
"sentence-transformers>=2.2",
"numpy>=1.24",
]
memory-colbert = [
"colbert-ai>=0.2",
"torch>=2.0",
]
memory-pdf = ["pdfplumber>=0.10"]
memory-bm25 = ["rank-bm25>=0.2.2"]
server = [
"fastapi>=0.110",
"uvicorn>=0.30",
"pydantic>=2.0",
"python-multipart>=0.0.9",
]
desktop = [
"fastapi>=0.110",
"uvicorn>=0.30",
"pydantic>=2.0",
"python-multipart>=0.0.9",
"faster-whisper>=1.0",
]
openhands = ["openhands-sdk>=1.0; python_version >= '3.12'"]
gpu-metrics = ["pynvml>=12.0"]
energy-amd = ["amdsmi>=6.1"]
energy-apple = ["zeus-ml[apple]"]
energy-all = ["pynvml>=12.0", "amdsmi>=6.1", "zeus-ml[apple]"]
orchestrator-training = ["torch>=2.0", "transformers>=4.40"]
learning-dspy = ["dspy>=2.6"]
learning-gepa = ["gepa>=0.1"]
channel-telegram = ["python-telegram-bot>=21.0"]
channel-discord = ["discord.py>=2.3"]
channel-slack = ["slack-sdk>=3.27"]
channel-line = ["line-bot-sdk>=3.0"]
channel-viber = ["viberbot>=1.0"]
channel-messenger = ["pymessenger>=0.0.7"]
channel-reddit = ["praw>=7.0"]
channel-mastodon = ["Mastodon.py>=1.8"]
channel-xmpp = ["slixmpp>=1.8"]
channel-rocketchat = ["rocketchat-API>=1.30"]
channel-zulip = ["zulip>=0.9"]
channel-twitter = ["httpx>=0.27"]
channel-twitch = ["twitchio>=2.6"]
channel-nostr = ["pynostr>=0.6"]
channel-twilio = ["twilio>=9.0"]
channel-gmail = [
"google-api-python-client>=2.0",
"google-auth-oauthlib>=1.0",
"google-auth-httplib2>=0.2",
]
browser = ["playwright>=1.40"]
media = ["openai>=1.30"]
mining-pearl-vllm = ["docker>=7.0", "httpx>=0.27"]
pdf = ["pdfplumber>=0.10"]
scheduler = ["croniter>=2.0"]
security-signing = ["cryptography>=43"]
sandbox-wasm = ["wasmtime>=25"]
sandbox-docker = ["docker>=7.0"]
dashboard = ["textual>=0.80"]
speech = ["faster-whisper>=1.0"]
speech-deepgram = ["deepgram-sdk>=3.0"]
eval-wandb = ["wandb>=0.17"]
eval-sheets = ["gspread>=6.0", "google-auth>=2.0"]
mining-pearl-cpu = [
# Pearl Python packages (py-pearl-mining, miner-base, pearl-gateway) are
# not on PyPI yet. They are installed at first `mine init` via the
# build-from-pin path in src/openjarvis/mining/_install.py:build_from_pin().
# When Pearl publishes wheels, replace the line below with version pins.
#
# The extra remains as a feature-flag namespace so users can run
# `uv sync --extra mining-pearl-cpu` to opt-in (it succeeds with no
# additional resolution today; the actual install happens on demand).
]
framework-comparison = ["polars>=1.0"]
docs = [
"mkdocs>=1.6",
"mkdocs-material>=9.5",
"mkdocstrings[python]>=0.25",
"mkdocs-gen-files>=0.5",
"mkdocs-literate-nav>=0.6",
]
[project.urls]
Homepage = "https://github.com/open-jarvis/OpenJarvis"
Documentation = "https://open-jarvis.github.io/OpenJarvis/"
Repository = "https://github.com/open-jarvis/OpenJarvis"
Issues = "https://github.com/open-jarvis/OpenJarvis/issues"
[project.scripts]
jarvis = "openjarvis.cli:main"
openjarvis-eval = "openjarvis.evals.cli:main"
# Version is derived from git tags by hatch-vcs (see #526). For source/editable
# checkouts this yields the true `git describe` version (e.g. 1.0.3.dev109+g<sha>)
# rather than a stale static string. CI release builds override this with
# SETUPTOOLS_SCM_PRETEND_VERSION so the published version equals the pushed tag.
#
# setuptools_scm cannot bump custom `.devN` tags (only `.dev0`), so the autotag
# `vX.Y.Z.devN` tags are deliberately EXCLUDED from version derivation here; the
# base is taken from the latest plain release tag (vX.Y.Z) and the dev distance
# is computed from commit count since that release.
[tool.hatch.version]
source = "vcs"
[tool.hatch.version.raw-options]
tag_regex = '^v(?P<version>[0-9]+\.[0-9]+\.[0-9]+)$'
git_describe_command = [
"git", "describe", "--dirty", "--tags", "--long",
"--match", "v[0-9]*", "--exclude", "*dev*", "--exclude", "*rc*", "--exclude", "desktop-*",
]
# Builds without a git checkout (e.g. the `COPY src/ src/` Docker stages, which
# never include .git) can't run `git describe`. Without a fallback that would
# hard-fail the build. Mirror the runtime sentinel in src/openjarvis/__init__.py.
# Such builds can inject the real version via SETUPTOOLS_SCM_PRETEND_VERSION.
fallback_version = "0.0.0+unknown"
[tool.uv.sources]
openjarvis-rust = { path = "rust/crates/openjarvis-python" }
[tool.hatch.build.targets.wheel]
packages = ["src/openjarvis"]
[tool.hatch.build.targets.wheel.force-include]
"src/openjarvis/agents/claude_code_runner" = "_node_modules/claude_code_runner"
"src/openjarvis/channels/whatsapp_baileys_bridge" = "_node_modules/whatsapp_baileys_bridge"
"scripts/install" = "_install_scripts"
"deploy/windows" = "_deploy/windows"
[tool.pytest.ini_options]
testpaths = ["tests"]
markers = [
"amd: requires AMD GPU",
"apple: requires Apple Silicon",
"cloud: requires cloud API keys",
"docker: requires a working Docker daemon (no GPU required)",
"live: requires running inference engine",
"macos15: requires macOS 15+ (Sequoia) for Apple FM",
"live_channel: requires real channel credentials (env vars)",
"nvidia: requires NVIDIA GPU",
"slow: long-running test",
"hub: downloads real datasets from the HuggingFace Hub at runtime; excluded from the default CI lane (run with -m hub)",
"live_external: requires HERMES_AGENT_PATH and OPENCLAW_PATH; spawns real foreign-framework subprocesses",
"modal: requires Modal token + network; runs real swebench harness on Modal",
]
[tool.ruff]
target-version = "py310"
src = ["src", "tests"]
[tool.ruff.lint]
select = ["E", "F", "I", "W"]
[tool.ruff.lint.per-file-ignores]
"src/openjarvis/evals/datasets/*.py" = ["E501"]
"src/openjarvis/evals/scorers/*.py" = ["E501"]
# hybrid/ is research code with long prompt strings and paradigm-specific
# config dicts — same relaxation as evals research code above. The ``**`` glob
# also covers subpackages (e.g. hybrid/skillorchestra/), which the prior
# ``hybrid/*.py`` glob missed.
"src/openjarvis/agents/hybrid/**/*.py" = ["E501"]
# research_loop.py carries long prompt strings too (documented in CLAUDE.md);
# the ignore was missing here.
"src/openjarvis/agents/research_loop.py" = ["E501"]
[dependency-groups]
dev = [
"maturin>=1.12.6",
]
# openjarvis_rust is the native PyO3 extension, built from the local Rust
# workspace. It lives in a uv dependency group (PEP 735) — not the published
# `desktop` extra — so `uv sync --group desktop-native` builds it from source
# for the desktop app, while `pip install openjarvis[desktop]` from PyPI does
# NOT try to resolve openjarvis-rust from PyPI, where it isn't published
# (dependency groups are excluded from wheel metadata). See #584 / #615.
desktop-native = [
"openjarvis-rust",
]