Pull just qwen3.5:2b (~2.7GB) during the SetupScreen so the app opens
quickly. Remaining Qwen3.5 models that fit in RAM download in the
background after the server is running — they appear in the model
list as each one finishes.
- Boot sequence: Phase 2 now pulls ALL Qwen3.5 models that fit in RAM
before the server starts. SetupScreen blocks until every model is
downloaded, showing per-model progress. No more background Phase 4.
- Default model: third-largest fitting model (qwen3.5:9b on 64GB).
- Download button: added pull_ollama_model and delete_ollama_model Tauri
commands. Frontend uses Tauri invoke in desktop mode, fixing the
"Load failed!" CORS/timeout issue with fetch().
* feat: model catalogue with download/delete and auto-pull Qwen3.5
- Desktop boot: start server immediately with fallback model (qwen3:0.6b),
then pull preferred model (qwen3.5:4b) and remaining Qwen3.5 variants
that fit in RAM in the background. No more broken "Select model" state.
- Backend: add POST /v1/models/pull and DELETE /v1/models/{name} endpoints
so the frontend can trigger model downloads and deletions via Ollama.
- Frontend: redesign CommandPalette (Cmd+K) with two tabs — "Installed"
shows pulled models with select/delete, "Download Models" shows a
catalogue of popular models plus a custom model input field.
- Fix ollama_has_model() to use exact tag matching instead of prefix
matching, preventing false positives.
* fix: streaming, model switching, second-largest default, and tests
- Streaming: use direct engine streaming for non-tool requests so tokens
arrive in real-time instead of being batched by the agent bridge.
Add error handling to _handle_stream so engine errors surface as
content chunks instead of silent failures.
- Model selection: pick the second-largest Qwen3.5 model that fits
(leaves headroom for OS/apps) instead of the absolute largest.
- Model switching: abort in-flight stream when the user changes models
mid-generation, preventing stale-model errors. Improve error messages
in catch blocks.
- Tests: add tests/server/test_model_management.py with 11 tests
covering model pull/delete endpoints, streaming error resilience,
direct-engine streaming bypass, and model listing. All 100 server
tests pass.
Detect system RAM at startup and automatically pull all Qwen3.5 model
variants (0.8b through 122b) that can run on the user's machine. The
smallest model is pulled first so the app is usable immediately, then
remaining models download in the background. The server starts with the
largest fitting model as default.
Also fixes ollama_has_model() to use exact tag matching instead of
prefix matching, which previously caused false positives (e.g. qwen3:0.6b
matching qwen3.5 queries).
The SecurityHeadersMiddleware ran before CORSMiddleware (Starlette
executes middleware in LIFO order) and added headers to OPTIONS
preflight requests. The Content-Security-Policy: default-src 'self'
header told the browser to reject cross-origin connections, so fetch()
from the Tauri webview (https://tauri.localhost) to the API server
(http://127.0.0.1) was blocked — causing "Failed to get response" on
every chat message in the desktop app.
Two fixes:
- Skip security headers on OPTIONS requests so CORS preflight works
- Remove Content-Security-Policy from API responses — it is a
document-level browser policy irrelevant to JSON API responses and
breaks any cross-origin API consumer
Three issues fixed:
1. The desktop-latest release accumulated stale artifacts across builds
because tauri-action adds new files without removing old ones. Users
could download an outdated DMG. Added a clean-release job that wipes
all existing assets before the build matrix runs.
2. The frontend hardcoded DESKTOP_API to port 8000 but the Tauri backend
starts the server on port 8222. Added a get_api_base Tauri command so
the frontend fetches the port from the Rust backend at startup,
keeping JARVIS_PORT as the single source of truth.
3. frontend/package.json version was 1.0.0 while desktop and pyproject
are 0.1.0, causing duplicate artifact names in the release.
The desktop app's find_project_root() only checked 4 hardcoded paths
when the .app bundle couldn't walk up to a pyproject.toml. Users who
cloned OpenJarvis into non-standard locations (e.g. ~/Documents/work/
OpenJarvis) would see "Jarvis server did not become healthy in time"
after a 120-second timeout with no actionable guidance.
Three improvements:
- Check OPENJARVIS_ROOT env var first for explicit override
- Expand direct path checks and add shallow scan of common parent
directories (~/Documents/*/OpenJarvis, ~/Desktop/*/OpenJarvis, etc.)
- Fail fast with a clear error message when the project root cannot be
found, instead of spawning a doomed server and timing out silently
getBase() reads settings.apiUrl from localStorage so the API URL
configured in the Settings page is actually used by api.ts and sse.ts.
Previously hardcoded to localhost:8000, causing "Failed to get response"
when the backend ran on a different port.
Co-authored-by: robbym-dev <robbym-dev@users.noreply.github.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>
OLLAMA_HOST env var was unconditionally overriding the host parameter
in OllamaEngine.__init__, even when explicitly set via config.toml.
Priority is now: config.toml > OLLAMA_HOST env var > hardcoded default.
Two minor frontend bugs:
- App.tsx: browser app hardcoded energy_wh_saved and flops_saved to 0
when submitting to the leaderboard instead of computing them from
per_provider data (desktop app was already correct)
- GetStartedPage.tsx: CodeBlock code props used JSX string attributes
(code="...\n...") which render \n literally; switched to JS
expressions (code={"...\n..."}) so newlines render correctly
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Jon Saad-Falcon