mirror of
https://github.com/open-jarvis/OpenJarvis.git
synced 2026-07-28 14:07:55 +00:00
4523715bff
The two eval-dataset suites that download real corpora from the HuggingFace Hub at runtime were running in the default CI lane. When the Hub was unreachable or rate-limited they failed and reddened `main` even though no code changed — confirmed by #506 (docs-only) failing on merge while its own PR run passed an hour earlier. They also dominated CI wall-time (~33 min of downloads + retry backoff on the failing run). Add a `hub` pytest marker, apply it to both suites via module-level `pytestmark`, and exclude it from the default CI lane (`-m "not live and not cloud and not hub"`). The tests stay runnable on demand with `pytest -m hub`. The ADP provider swallows per-config download errors and returns 0 records on a network failure, so a Hub outage surfaced there as `assert 1 <= 0` (not an exception) — it could not be made non-flaky by exception handling alone, only by gating. Coverage holds: removing these from CI drops total from 60.92% to ~60.73% (paranoid worst case 60.18%), still above the 60% gate. Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
205 lines
6.6 KiB
TOML
205 lines
6.6 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 = "0.1.1"
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description = "OpenJarvis — modular AI assistant backend with composable intelligence primitives"
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readme = "README.md"
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# Upper bound: numpy 2.2.x (pinned transitively via datasets/pandas) ships no
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# cp314 Windows wheel, so under Python 3.14 uv would compile numpy from source
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# (Meson) and fail on Windows boxes without a C toolchain (#350). Cap to the
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# range that has prebuilt wheels; matches the classifiers (3.10–3.13).
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requires-python = ">=3.10,<3.14"
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license = {text = "Apache-2.0"}
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authors = [
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{name = "Open Jarvis Contributors"},
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]
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classifiers = [
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"Development Status :: 3 - Alpha",
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"Intended Audience :: Developers",
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"License :: OSI Approved :: Apache Software License",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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]
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dependencies = [
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"click>=8",
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"datasets>=4.5.0",
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"ddgs>=9.11.4",
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"httpx>=0.27",
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"openai>=1.30",
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"nvidia-ml-py>=12.560.30",
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"posthog>=3.0",
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"python-telegram-bot>=22.6",
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"rich>=13",
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"tomli>=2.0; python_version < '3.11'",
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"tomlkit>=0.12",
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"websockets>=15.0.1",
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]
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[project.optional-dependencies]
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dev = [
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"maturin>=1.12.6",
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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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"pre-commit>=3.0",
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]
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inference-mlx = ["mlx-lm>=0.31.1; sys_platform == 'darwin'"]
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inference-vllm = ["vllm>=0.16.0"]
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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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inference-gemma = ["pygemma>=0.1.3"]
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tools-search = [
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"tavily-python>=0.3",
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"ddgs>=9.11.4",
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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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"python-multipart>=0.0.9",
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]
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openhands = ["openhands-sdk>=1.0; python_version >= '3.12'"]
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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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orchestrator-training = ["torch>=2.0", "transformers>=4.40"]
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learning-dspy = ["dspy>=2.6"]
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learning-gepa = ["gepa>=0.1"]
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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-line = ["line-bot-sdk>=3.0"]
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channel-viber = ["viberbot>=1.0"]
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channel-messenger = ["pymessenger>=0.0.7"]
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channel-reddit = ["praw>=7.0"]
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channel-mastodon = ["Mastodon.py>=1.8"]
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channel-xmpp = ["slixmpp>=1.8"]
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channel-rocketchat = ["rocketchat-API>=1.30"]
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channel-zulip = ["zulip>=0.9"]
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channel-twitter = ["httpx>=0.27"]
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channel-twitch = ["twitchio>=2.6"]
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channel-nostr = ["pynostr>=0.6"]
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channel-twilio = ["twilio>=9.0"]
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channel-gmail = [
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"google-api-python-client>=2.0",
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"google-auth-oauthlib>=1.0",
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"google-auth-httplib2>=0.2",
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]
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browser = ["playwright>=1.40"]
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media = ["openai>=1.30"]
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mining-pearl-vllm = ["docker>=7.0", "httpx>=0.27"]
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pdf = ["pdfplumber>=0.10"]
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scheduler = ["croniter>=2.0"]
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security-signing = ["cryptography>=43"]
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sandbox-wasm = ["wasmtime>=25"]
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sandbox-docker = ["docker>=7.0"]
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dashboard = ["textual>=0.80"]
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speech = ["faster-whisper>=1.0"]
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speech-deepgram = ["deepgram-sdk>=3.0"]
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eval-wandb = ["wandb>=0.17"]
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eval-sheets = ["gspread>=6.0", "google-auth>=2.0"]
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mining-pearl-cpu = [
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# Pearl Python packages (py-pearl-mining, miner-base, pearl-gateway) are
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# not on PyPI yet. They are installed at first `mine init` via the
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# build-from-pin path in src/openjarvis/mining/_install.py:build_from_pin().
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# When Pearl publishes wheels, replace the line below with version pins.
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#
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# The extra remains as a feature-flag namespace so users can run
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# `uv sync --extra mining-pearl-cpu` to opt-in (it succeeds with no
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# additional resolution today; the actual install happens on demand).
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]
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framework-comparison = ["polars>=1.0"]
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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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"mkdocs-gen-files>=0.5",
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"mkdocs-literate-nav>=0.6",
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]
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[project.urls]
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Homepage = "https://github.com/open-jarvis/OpenJarvis"
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Documentation = "https://open-jarvis.github.io/OpenJarvis/"
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Repository = "https://github.com/open-jarvis/OpenJarvis"
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Issues = "https://github.com/open-jarvis/OpenJarvis/issues"
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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" = "_node_modules/claude_code_runner"
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"src/openjarvis/channels/whatsapp_baileys_bridge" = "_node_modules/whatsapp_baileys_bridge"
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"scripts/install" = "_install_scripts"
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"deploy/windows" = "_deploy/windows"
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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markers = [
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"amd: requires AMD GPU",
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"apple: requires Apple Silicon",
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"cloud: requires cloud API keys",
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"docker: requires a working Docker daemon (no GPU required)",
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"live: requires running inference engine",
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"macos15: requires macOS 15+ (Sequoia) for Apple FM",
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"live_channel: requires real channel credentials (env vars)",
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"nvidia: requires NVIDIA GPU",
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"slow: long-running test",
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"hub: downloads real datasets from the HuggingFace Hub at runtime; excluded from the default CI lane (run with -m hub)",
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"live_external: requires HERMES_AGENT_PATH and OPENCLAW_PATH; spawns real foreign-framework subprocesses",
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"modal: requires Modal token + network; runs real swebench harness on Modal",
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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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"src/openjarvis/evals/datasets/*.py" = ["E501"]
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"src/openjarvis/evals/scorers/*.py" = ["E501"]
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# hybrid/ is research code with long prompt strings and paradigm-specific
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# config dicts — same relaxation as evals research code above. The ``**`` glob
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# also covers subpackages (e.g. hybrid/skillorchestra/), which the prior
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# ``hybrid/*.py`` glob missed.
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"src/openjarvis/agents/hybrid/**/*.py" = ["E501"]
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# research_loop.py carries long prompt strings too (documented in CLAUDE.md);
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# the ignore was missing here.
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"src/openjarvis/agents/research_loop.py" = ["E501"]
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[dependency-groups]
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dev = [
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"maturin>=1.12.6",
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]
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