القائمة
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/AndrewSmigaj/OpenLLMRI --skill serverيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Uncertainty assessment before implementation — identify what you know, what you're guessing, and what to verify
Generate 2-3 genuinely different approaches to a problem and compare them
Challenge a design or approach — find real weaknesses, not performative objections
استنادا إلى تصنيف SOC المهني
عرض SKILL.md
| name | server |
| description | Start, stop, and check status of backend and frontend servers |
Manage the Concept MRI backend (FastAPI + model) and frontend (Vite) servers.
| Constant | Value |
|---|---|
| Project root | /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI |
| Python | /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/.venv/bin/python |
| Backend working dir | backend/src (relative to project root) |
| Backend URL | http://localhost:8000 |
| Frontend URL | http://localhost:5173 |
| Health endpoint | http://localhost:8000/health |
| Host binding | 0.0.0.0 (required for WSL2) |
NEVER use bare python3 — always use the full venv path above.
Each operation below is a single self-contained block. Copy the EXACT block — do not improvise or compose steps from multiple blocks.
Run this FIRST before any other operation to understand current state.
echo "=== Processes ===" && ps aux | grep -E "uvicorn|vite" | grep -v grep || echo "(none running)" && echo "=== Ports ===" && (fuser 8000/tcp 2>/dev/null && echo "8000: IN USE" || echo "8000: free") && (fuser 5173/tcp 2>/dev/null && echo "5173: IN USE" || echo "5173: free") && echo "=== Backend Health ===" && curl -s --max-time 3 http://localhost:8000/health 2>/dev/null | /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/.venv/bin/python -c "import json,sys; d=json.load(sys.stdin); s=d.get('loading',{}).get('stage','?'); e=d.get('loading',{}).get('elapsed_seconds'); print(f'Model loaded — ready' if d.get('model_loaded') else f'Stage: {s} ({e}s elapsed)' if e else f'Stage: {s}')" 2>/dev/null || echo "Not responding" && echo "=== Frontend ===" && curl -s -o /dev/null -w "HTTP %{http_code}" http://localhost:5173 2>/dev/null || echo "Not responding"
Use fuser -k (kills by port) — this is reliable on WSL2. pkill is NOT reliable here.
fuser -k 8000/tcp 2>/dev/null; fuser -k 5173/tcp 2>/dev/null; sleep 2 && echo "=== Verify ===" && (fuser 8000/tcp 2>/dev/null && echo "8000: STILL IN USE" || echo "8000: free") && (fuser 5173/tcp 2>/dev/null && echo "5173: STILL IN USE" || echo "5173: free")
If a port shows "STILL IN USE" after this, run fuser -k -9 <port>/tcp (SIGKILL).
Prerequisite: Port 8000 must be free (run OP-2 first if needed).
cd /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/backend/src && /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/.venv/bin/python -m uvicorn api.main:app --host 0.0.0.0 --port 8000 --reload
Run with run_in_background: true.
WSL2 note: On WSL2 with /mnt/c/ NTFS filesystem, inotify is unreliable. Existing endpoint edits usually reload fine, but new endpoints/routes may not be detected. If a new endpoint returns 404, do a full restart (OP-2 + OP-3). See TROUBLESHOOTING.md.
Run AFTER OP-3. Must use run_in_background: true — takes ~2-3 minutes.
The health endpoint now reports loading stage in real time (the API serves immediately while model loads in background). No need to read log files.
PY=/mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/.venv/bin/python; for i in $(seq 1 60); do H=$(curl -s --max-time 3 http://localhost:8000/health 2>/dev/null); if [ -z "$H" ]; then echo "[$i] Waiting for API..."; sleep 5; continue; fi; STAGE=$(echo "$H" | $PY -c "import json,sys; print(json.load(sys.stdin).get('loading',{}).get('stage','unknown'))"); ELAPSED=$(echo "$H" | $PY -c "import json,sys; print(json.load(sys.stdin).get('loading',{}).get('elapsed_seconds','?'))"); if [ "$STAGE" = "ready" ]; then echo "READY — model loaded in ${ELAPSED}s"; exit 0; fi; if [ "$STAGE" = "failed" ]; then echo "FAILED — check backend logs"; exit 1; fi; echo "[$i] Stage: $STAGE (${ELAPSED}s elapsed)"; sleep 5; done; echo
Expected output:
[1] Waiting for API...
[2] Stage: initializing (3.2s elapsed)
[3] Stage: loading_model (8.1s elapsed)
...
[24] Stage: loading_model (118.5s elapsed)
[25] Stage: creating_service (121.0s elapsed)
[26] READY — model loaded in 123.4s
Stages: not_started → initializing → loading_model → creating_service → ready | failed
Prerequisite: Port 5173 must be free.
cd /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/frontend && npm run dev
Run with run_in_background: true. Vite uses strictPort: true — will error if 5173 is taken.
This is the typical workflow after code changes or when the backend needs a fresh start.
run_in_background: true)run_in_background: true) — can launch in parallel with OP-3run_in_background: true)Only needed if Vite HMR stops working (rare).
fuser -k 5173/tcp 2>/dev/null; sleep 1; cd /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/frontend && npm run dev
Run with run_in_background: true.
| Change made | Action needed |
|---|---|
Frontend .tsx/.ts edit | None — Vite HMR handles it |
Backend .py edit (existing endpoint) | Usually none (--reload). If stale, full restart |
| Backend new endpoint or route | ALWAYS full restart (WSL2 inotify unreliable) |
| Backend dependency added | Full restart |
Frontend dependency added (npm install) | Restart Vite only |
fuser -k to stop, not pkill — pkill is unreliable on WSL2model_loaded: true before making API calls that need the model0.0.0.0 (not 127.0.0.1) for WSL2 networkingpython3 — always /mnt/c/Users/emily/OpenAIHackathon-ConceptMRI/.venv/bin/python