PocketLLM is a cross-platform assistant that pairs a Flutter application with a FastAPI backend to deliver secure, low-latency access to large language models. Users can connect their own provider accounts, browse real-time catalogues, import models, and chat across mobile and desktop targets with a shared experience.

IMPORTANT NOTICE — PLEASE READ BEFORE PROCEEDING

🚧 Development of this application has been temporarily halted by the original author (me). This project is NOT abandoned, but it is not actively maintained or receiving updates at this time.

If someone has forked or continued this project, feel free to use their version instead.

Work is currently focused on PocketLLM Lite and Mugshot Studios both open-source and actively developed. This project may be resumed in the future.

PocketLLM focuses on three pillars:

1. Unified catalogue – aggregate models from OpenAI, Groq, OpenRouter, and ImageRouter using official SDKs with per-user API keys.
2. Bring your own keys – users activate providers securely; secrets are encrypted at rest and never fall back to environment credentials.
3. Consistent chat experience – Flutter renders the same responsive interface on Android, iOS, macOS, Windows, Linux, and the web.

The backend exposes REST APIs that the Flutter client consumes. A Supabase instance stores provider configurations, encrypted secrets, and chat history.

PocketLLM
├── lib/                     # Flutter client (Riverpod, GoRouter, Material 3)
│   ├── component/           # Shared widgets and UI primitives
│   ├── pages/               # Screens including Library, API Keys, Chat
│   └── services/            # State management, API bridges, secure storage
├── pocketllm-backend/       # FastAPI application
│   ├── app/api/             # Versioned routes (/v1)
│   ├── app/services/        # Provider catalogue, auth, jobs, models
│   ├── app/utils/           # Crypto helpers, security utilities
│   └── database/            # Dataclasses mirroring Supabase tables
└── docs/                    # Operational guides and API references

cd pocketllm-backend
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

cp .env.example .env  # configure Supabase credentials and ENCRYPTION_KEY
uvicorn main:app --reload

Key endpoint: GET /v1/models

GET /v1/models
Authorization: Bearer <JWT>

{
  "models": [
    {
      "provider": "openai",
      "id": "gpt-4o",
      "name": "GPT-4 Omni",
      "metadata": {"owned_by": "openai"}
    }
  ],
  "message": null,
  "configured_providers": ["openai"],
  "missing_providers": ["groq", "openrouter", "imagerouter"]
}

When no API keys are stored the endpoint responds with an empty models array and a descriptive message, enabling the Flutter UI to prompt users to add credentials.

cd ..
flutter pub get
flutter run  # chooses a connected device or emulator

The API Keys page surfaces provider status, preview masks, and validation results. The Model Library consumes the unified /v1/models response and displays grouped catalogues with filtering options.

Note: Some integration suites stub external SDKs; install openai, groq, and openrouter packages locally for full coverage.

• docs/api-documentation.md – REST endpoints and schemas.
• docs/backend-guide.md – Environment variables, Supabase integration, and deployment playbooks.
• docs/groq-guide.md – Official SDK usage for catalogue, chat, audio, and reasoning APIs.
• docs/frontend_cleanup_tasks.md – Outstanding UI refinements.

Contributions are welcome! Please review CONTRIBUTING.md and ensure:

1. New features include unit or widget tests.
2. Backend changes run through pytest with optional SDKs installed.
3. Documentation and changelogs reflect API or workflow updates.
4. Secrets and API keys are never committed.

PocketLLM is released under the MIT License.

Have questions or ideas? Open an issue or join the discussion — we’d love to hear how you are using PocketLLM.