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* fix(windows): desktop backend spawn (#531) + model-aware engine selection (#532) Two runtime bugs found during end-to-end testing on a clean Windows 11 24H2 Azure VM. #531 - Desktop "Failed to get response": run_jarvis_command spawned the backend with .output(), which waits for the process to exit. `jarvis serve` never exits, so the Tauri command hung forever (the Start button never resolved); and it ran `uv run jarvis` with no cwd, so in a packaged install -- where the cwd isn't the checkout -- `jarvis` wasn't found and the server never started. Now: run from find_project_root(), and for `serve` spawn detached (.spawn()), drain stderr, and poll /health for readiness (mirrors start_backend); short commands keep .output(). The server layer itself was verified healthy on Windows (/health and /v1/chat/completions both 200, localhost included) -- the fault was the Tauri spawn path. #532 - "OpenAI client not available" after reboot: when the local engine is down, get_engine's fallback selected CloudEngine because health() is True if ANY provider client exists -- without checking the resolved model's provider has a client. A user with e.g. OPENROUTER_API_KEY and a gpt-* model then hit the OpenAI path with no client. Add CloudEngine.can_serve(model) (checks the specific provider client via the same routing generate()/stream() use) + a default can_serve->True on the base engine, and make get_engine model-aware so it skips an engine that can't serve the model -- the user falls through to the helpful "no engine available / start ollama" message instead. Tests: engine discovery/cloud/model-matrix + cli serve/ask suites pass (the one ask_e2e failure is a pre-existing version-banner flake, fails identically on main). The Tauri crate couldn't be compiled locally (no GTK/webkit sys-libs in this env); relies on CI. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * test(engine): cover model-aware engine selection + CloudEngine.can_serve (#532) #533 added a `model` arg to get_engine and a can_serve() gate but shipped no tests. Add them: - get_engine skips a healthy engine that can't serve the requested model (the cloud-fallback-for-unservable-model case behind #532), - model=None preserves the legacy model-agnostic selection, - CloudEngine.can_serve gates on the per-provider client (gpt->OpenAI, claude->Anthropic, ...), verified empirically. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: Jon Saad-Falcon <jonsaadfalcon@gmail.com>