Closes Phase-1 of #298 (Native Windows Support RFC).
Reverses the long-standing "native Windows is not supported" stance. PowerShell installer at `deploy/windows/install.ps1` (published to https://open-jarvis.github.io/OpenJarvis/install.ps1) plus a `jarvis-service.ps1` scheduled-task helper that mirrors `deploy/systemd/openjarvis.service` and `deploy/launchd/com.openjarvis.plist`. Loopback default (127.0.0.1, no API key) — same as launchd.
One-liner install:
irm https://open-jarvis.github.io/OpenJarvis/install.ps1 | iex
Adversarial review caught and fixed two real bugs pre-commit:
1. `irm | iex` drops `param()` flags — added env-var fallbacks (OPENJARVIS_SKIP_SERVICE / OPENJARVIS_SERVICE / OPENJARVIS_FORCE).
2. Scheduled tasks don't inherit the registering session's env — the LAN-exposed `OPENJARVIS_API_KEY` path now persists the key to User scope so the task's logon environment can read it.
Supersedes #434 (the guidance-only "use WSL2" install.ps1).
Massive thanks to @SeCuReDmE-main-dev for the careful RFC #298 — the three-phase decomposition (install / service / shared-memory bridge) is exactly the right framing. This PR ships Phase-1 and Phase-2 of the RFC fused into one release; Phase-3 (shared memory bridge) remains future work.
Thanks also to @KadenBordeaux for raising #334 ("'bash' is not recognized as the name of a cmdlet"). That report is what made this whole Windows-support cluster a priority — without your bug report the unsupported stance would still be in the README. The friction you hit motivated #432 (numpy/python cap), #433 (CLI startup resilience), #436 (python discovery helpers), #437 (desktop launcher fix), and this PR.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Fixes#350 (API server fails to start on Windows because numpy has no cp314 wheels).
Caps `requires-python` to `>=3.10,<3.14` in pyproject.toml so uv resolves a Python that has working numpy wheels on Windows. Extends the `test-windows` CI matrix to run on both Python 3.12 and 3.13 to keep the cap honest.
Reported by @RizaldyMongi in #350. Thanks for the careful repro — the Windows-only fallout was tricky to reproduce on Linux/macOS and the issue gave us the exact symptom signature to triage from.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Auto-fixes 13 inherited ruff errors in agents/hybrid/skillorchestra/* and evals/scorers/swebench_harness.py (I001/F401/W291/W292/E703), strips trailing whitespace in evals/eval_orchestrator.py, wraps a long signature in speech/cartesia_tts.py, and extends per-file-ignores for `agents/hybrid/**` and `agents/research_loop.py` (research code with long prompt strings — same rationale as the existing evals relaxation).
Unblocks lint CI for the rest of the Windows-fix cluster (#432, #433, #436, #437, #438).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Patch release bundling the fixes merged since v1.0.1. The headline is
#372 — the v1.0.1 wheel on PyPI is missing `openjarvis/traces/`, so
every `pip install openjarvis==1.0.1` breaks at import. PyPI filenames
are immutable, so the fix has to ship under a new version number.
Bumps version 1.0.1 → 1.0.2 and adds the CHANGELOG entry covering
#372 (wheel packaging), #389 (pynvml warning), #373 (Windows RAM),
#331 (desktop uv-sync diagnostics), and #337/#352 (install URL → GitHub
Pages).
After this merges, cut the release:
uv build
unzip -l dist/openjarvis-1.0.2-*.whl | grep traces # verify
twine upload dist/openjarvis-1.0.2-*
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Fixes#389.
The legacy `pynvml` PyPI package (since version 13.x) registers a
meta-path-finder shim — `_pynvml_redirector.py` — that prints a
`FutureWarning("The pynvml package is deprecated. Please install
nvidia-ml-py instead.")` on every `import pynvml`, even when the
caller's project doesn't depend on pynvml directly. The warning was
firing on every `jarvis --version` / `jarvis ask` / any command that
touches the telemetry path.
Two-layer fix:
1. **pyproject.toml**: switch `pynvml>=13.0.1` → `nvidia-ml-py>=12.560.30`
in the core deps, `gpu-metrics` extra, and `energy-all` extra.
`nvidia-ml-py` is NVIDIA's official package and ships the same
`pynvml` module name without the redirector shim, so the warning
doesn't fire.
2. **Defensive filters** at all four `import pynvml` sites
(`telemetry/gpu_monitor.py`, `telemetry/energy_nvidia.py`,
`server/research_router.py`, `evals/backends/external/_subprocess_runner.py`):
wrap the import in a narrowly-scoped `warnings.filterwarnings("ignore",
message=r"The pynvml package is deprecated.*", category=FutureWarning)`.
Belt-and-suspenders for the case where `pynvml` gets pulled in
transitively by torch / vllm / etc. — the user's environment may
still have it installed even if our deps don't pull it in.
Verified locally:
- `uv sync` swaps pynvml → nvidia-ml-py.
- `python -c "import warnings; warnings.simplefilter('error', FutureWarning); from openjarvis.telemetry import gpu_monitor"` → no warning fires (would raise if it did).
- `jarvis --version` → clean output, no FutureWarning preceding the version string.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
uv.lock pinned mlx-lm==0.29.1, which predates the qwen3_5 architecture.
Running mlx_lm.server with mlx-community/Qwen3.5-* models therefore
fails with 'Model type qwen3_5 not supported.' on every uv sync, even
when pyproject.toml's loose constraint (>=0.19) would otherwise allow
a newer release.
Tighten the inference-mlx extra to mlx-lm>=0.31.1 (the first release
with Qwen3.5 support) and regenerate uv.lock — resolves to mlx-lm
0.31.3.
The lockfile diff is large because uv produces a single cross-platform
lock and adds 'split' entries for a handful of transitive deps
(transformers, vllm, huggingface-hub, mistral-common, etc.). Every
split entry is marker-gated to:
python_full_version >= '3.14' and sys_platform != 'linux'
and sys_platform != 'win32'
i.e. macOS on Python 3.14+ — the very subset that actually pulls in
mlx-lm 0.31.x. Linux, Windows, and Python <= 3.13 paths keep the
existing pins (transformers 4.57.6, vllm 0.17.1, …).
Closes#191
Now that the `openjarvis` name is available on PyPI, rename the
distribution from `OpenJarvisAI` to `OpenJarvis` so `pip install
openjarvis` matches the import name and the in-code install hints
(e.g. `pip install openjarvis[channel-gmail]`).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
openjarvis was already taken on PyPI, so the package is registered as
OpenJarvisAI. Update pyproject.toml and docs badges to match.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Merge main into fix/ssrf-check, keeping both the auto-recover
logic for error-state agents and the async streaming support
for the send_message endpoint.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When Tavily API is unavailable (no API key, import error, or API error),
the web_search tool now falls back to DuckDuckGo search instead of
failing. This ensures the tool always works for users without a
Tavily API key.
- Add DuckDuckGo search as fallback using ddgs package
- Catch specific Tavily exceptions (MissingAPIKeyError, InvalidAPIKeyError,
ForbiddenError, UsageLimitExceededError, TimeoutError, BadRequestError)
- Add logger.debug calls to log when falling back to DuckDuckGo
- Use ddgs instead of deprecated duckduckgo-search package name
- Add test for DuckDuckGo fallback result formatting
- Simplify test mocking to use consistent monkeypatch patterns
Closes#81
- Add root CONTRIBUTING.md with incentives (paper acknowledgment, Mac Mini
giveaway), contribution tiers, PR process, and maintainership path
- Add CODE_OF_CONDUCT.md (Contributor Covenant v2.1)
- Add .pre-commit-config.yaml with ruff lint + format hooks
- Add GitHub issue templates (bug report, feature request, new eval dataset)
- Add PR template with test/lint/format checklist
- Rewrite docs roadmap with GitHub Projects structure, current focus areas,
and collapsible version history
- Remove Development section from MkDocs nav; replace with top-level Roadmap tab
- Delete changelog, extending docs (consolidated into CONTRIBUTING.md)
- Delete root ROADMAP.md (content now lives in docs site)
- Add pre-commit to dev extras in pyproject.toml
- Add Roadmap link to README
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* chore: create learning subdirectory structure (routing, agents, intelligence)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: extract classify_query to routing/_utils.py
Move the classify_query() function and its regex patterns into a shared
utility module so multiple routing policies can import it without
depending on the full trace_policy module.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: move routing files to learning/routing/ subdirectory
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: create LearnedRouterPolicy merging trace-driven + SFT routing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add conditional Algolia DocSearch integration
Add Algolia DocSearch as an optional search upgrade — native lunr.js
search remains the default until credentials are configured. Includes
CDN assets, Jinja2 conditional config injection, init script with
graceful fallback, light/dark theme CSS, improved search tokenization
for snake_case/dotted identifiers, and search boosts for key pages.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: move agent_evolver and skill_discovery to learning/agents/
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: move learning/orchestrator to learning/intelligence/orchestrator
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: delete removed learning policies, rewrite __init__.py, clean up api_routes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add SFT/GRPO/DSPy/GEPA config dataclasses, update LearningConfig
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add general-purpose SFT trainer (intelligence/sft_trainer.py)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: update stale imports in multi_model_router example
Update imports to use new learning/routing/ paths after the
subdirectory reorganization. Replace BanditRouterPolicy with
LearnedRouterPolicy.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add general-purpose GRPO trainer (intelligence/grpo_trainer.py)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add DSPy agent optimizer (agents/dspy_optimizer.py)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add GEPA agent optimizer (agents/gepa_optimizer.py)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add learning-dspy and learning-gepa optional dependency extras
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: update integration test to check for learned policy instead of grpo
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: clean up stale APIs and unused params in examples
- deep_research: remove system_prompt and max_turns params not accepted
by Jarvis.ask(), inline system prompt into the query instead
- doc_qa: remove unused --top-k CLI arg that was never passed to the API
- multi_model_router: fix select_model() call to match single-arg signature
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: import SFT/GRPO trainers in intelligence/__init__.py for registry
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: remove .md file changes from PR
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: restore search boost frontmatter for key docs pages
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
