Mise (pronounced "meez") is the kitchen term for "everything in its place" - this app keeps your meals, pantry, and shopping just as organized.

A smart, AI-assisted meal planner that learns your preferences, understands what is in your kitchen, suggests meals that minimize waste, and keeps leftovers and shopping lists in sync. The project now includes a dedicated ASI orchestration service (mise-asi/) so the heavy AI/tool-calling logic runs server-side.

You can try the Mise AI agent on Agentverse
https://agentverse.ai/agents/details/agent1qt354vjymslddeu26y2zgtxjm27cpv3035xwmlyll7nyf38ez68s5w3w687/profile

• Personalized meal suggestions that respect dietary preferences, allergies, and nutrition goals.
• Pantry and shopping list management backed by Supabase (inventory, leftovers, preferences, notes).
• Parallel tool execution for faster responses and richer context gathering.
• Leftover tracking with portion adjustments to cut food waste.
• Server-side orchestration layer (mise-asi) that mirrors the frontend toolset and exposes a simple HTTP API.

mise-asi/ is a Python/Flask service that replaces the old Supabase edge proxy. It:

• Exposes /health, /chat, and /tools endpoints for the React app (src/hooks/chat/asiProxy.ts).
• Runs an orchestrator that calls an OpenAI-compatible ASI Cloud model with the full tool registry.
• Dispatches function calls to domain handlers (inventory, shopping list, meals, preferences, leftovers, notes, Amazon search placeholder).
• Persists and reads data from Supabase tables (user_inventory, shopping_lists, user_preferences, user_leftovers).

React + Vite UI (chat, pantry, leftovers)
   |
   | HTTP (VITE_ASI_ENDPOINT)
   v
Flask adapter (/chat, /tools, /health)
   |
   v
Orchestrator (OpenAI client -> ASI Cloud)
   |
   |-- Tool registry (OpenAI function schemas)
   `-- Handlers (inventory, shopping list, preferences, leftovers, meals, notes, Amazon)
           |
           v
     Supabase Postgres

• mise-asi/main.py - entrypoint that validates env vars and boots Flask.
• mise-asi/adapters/flask_app.py - HTTP adapter, CORS, routes.
• mise-asi/orchestration/orchestrator.py - chat loop, OpenAI-compatible calls, tool execution.
• mise-asi/registry/ - tool definitions grouped by domain.
• mise-asi/handlers/ - executes tool calls and formats responses.
• mise-asi/utils/supabase_client.py - Supabase client and CRUD helpers.
• mise-asi/config/settings.py - environment-driven settings.

.
|-- src/                      # React app (chat, UI, hooks)
|   `-- hooks/chat/asiProxy.ts # Frontend -> mise-asi bridge
|-- supabase/                 # Supabase config, migrations, edge function legacy
|-- public/                   # Static assets (screenshot)
|-- mise-asi/                 # ASI orchestration service (Python/Flask)
|   |-- adapters/             # HTTP adapter
|   |-- orchestration/        # Orchestrator and types
|   |-- registry/             # Tool schemas
|   |-- handlers/             # Domain handlers
|   |-- utils/                # Supabase + logging helpers
|   `-- config/               # Settings and env validation
`-- package.json, vite.config.ts, etc.

• Node.js 18+
• Python 3.10+ (for mise-asi)
• Supabase project (tables: user_inventory, shopping_lists, user_preferences, user_leftovers)
• ASI Cloud/OpenAI-compatible API key

1. Install deps: npm install

2. Configure .env.local (defaults to localhost if omitted):

   VITE_ASI_ENDPOINT=http://localhost:8001

3. Start Vite dev server: npm run dev

4. Open http://localhost:5173

1. cd mise-asi

2. (Optional) Create a venv: python -m venv .venv && .venv\Scripts\activate

3. Install deps: pip install -r requirements.txt

4. Create .env (see .env.example):

   PORT=8001
   FLASK_ENV=development
   SUPABASE_URL=your_supabase_url
   SUPABASE_KEY=your_supabase_service_key
   ASICLOUD_API_KEY=your_asi_cloud_key
   ASICLOUD_BASE_URL=https://inference.asicloud.cudos.org/v1
   MODEL_NAME=openai/gpt-oss-20b
   AGENT_SEED=mise-asi-agent-seed-phrase

5. Start the Flask server (API & Orchestrator): python main.py

6. (Optional) Start the uAgent runner (Standalone Agent): python -m uagent.runner

   • This runs the agent as a separate process, useful for decentralized communication.

7. Check health: curl http://localhost:8001/health

The system is deployed on AgentVerse.

• Frontend: Deployed on Vercel (or similar).
• Backend: mise-asi runs on a cloud provider (e.g., Render, AWS) and connects to AgentVerse for agent discovery.

If you want to run Supabase locally instead of the hosted project:

npx supabase init
npx supabase db push     # apply migrations in supabase/migrations

Ensure the tables mentioned above exist; the handlers expect them.

• Utility: current time.
• Inventory: get, create/update/delete items, categorize and format inventory for the model.
• Shopping list: view/add/remove items, UI "open" command.
• Preferences: read/update/create dietary preferences and goals.
• Leftovers: manage servings, add/remove/update leftovers, UI "open" command.
• Meals: format model-generated meal suggestions and update meal plans.
• Notes: store freeform user notes.
• Amazon search: placeholder responses; wire up RapidAPI + keys to enable real calls.

• Point VITE_ASI_ENDPOINT to the deployed mise-asi host.
• mise-asi can be served with gunicorn: gunicorn -w 4 -b 0.0.0.0:8001 main:app.
• Keep Supabase service keys server-side; the frontend only calls the orchestrator.

Built to help keep every meal, ingredient, and leftover in its place. Enjoy!