# Installation Guide Complete installation guide for the LedGrab server. ## Table of Contents 1. [Docker Installation (recommended)](#docker-installation) 2. [Manual Installation](#manual-installation) 3. [First-Time Setup](#first-time-setup) 4. [Configuration Reference](#configuration-reference) 5. [Troubleshooting](#troubleshooting) > **Home Assistant integration** has moved to a separate repository: > [ledgrab-haos-integration](https://git.dolgolyov-family.by/alexei.dolgolyov/ledgrab-haos-integration) --- ## Docker Installation The fastest way to get running. Requires [Docker](https://docs.docker.com/get-docker/) with Compose. 1. **Clone and start:** ```bash git clone https://git.dolgolyov-family.by/alexei.dolgolyov/ledgrab.git cd ledgrab/server docker compose up -d ``` 2. **Verify:** ```bash curl http://localhost:8080/health # → {"status":"healthy", ...} ``` 3. **Open the dashboard:** 4. **View logs:** ```bash docker compose logs -f ``` 5. **Stop / restart:** ```bash docker compose down # stop docker compose up -d # start again (data is persisted) ``` ### Docker manual build (without Compose) ```bash cd server docker build -t ledgrab . docker run -d \ --name ledgrab \ -p 8080:8080 \ -v $(pwd)/data:/app/data \ -v $(pwd)/logs:/app/logs \ -v $(pwd)/config:/app/config:ro \ ledgrab ``` ### Linux screen capture in Docker Screen capture from inside a container requires X11 access. Uncomment `network_mode: host` in `docker-compose.yml` and ensure the `DISPLAY` variable is set. Wayland is not currently supported for in-container capture. --- ## Manual Installation ### Requirements | Dependency | Version | Purpose | | ---------- | ------- | ------- | | Python | 3.11+ | Backend server | | Node.js | 18+ | Frontend build (esbuild) | | pip | latest | Python package installer | | npm | latest | Node package manager | ### Steps 1. **Clone the repository:** ```bash git clone https://git.dolgolyov-family.by/alexei.dolgolyov/ledgrab.git cd ledgrab/server ``` 2. **Build the frontend bundle:** ```bash npm ci npm run build ``` This compiles TypeScript and bundles JS/CSS into `src/ledgrab/static/dist/`. 3. **Create a virtual environment:** ```bash python -m venv venv # Linux / macOS source venv/bin/activate # Windows (cmd) venv\Scripts\activate # Windows (PowerShell) venv\Scripts\Activate.ps1 ``` 4. **Install Python dependencies:** ```bash pip install . ``` Optional extras: ```bash pip install ".[perf]" # DXCam, BetterCam, WGC (Windows only) pip install ".[notifications]" # OS notification capture pip install ".[dev]" # pytest, black, ruff (development) ``` 5. **Set PYTHONPATH and start the server:** ```bash # Linux / macOS export PYTHONPATH=$(pwd)/src uvicorn ledgrab.main:app --host 0.0.0.0 --port 8080 # Windows (cmd) set PYTHONPATH=%CD%\src uvicorn ledgrab.main:app --host 0.0.0.0 --port 8080 ``` 6. **Verify:** open in your browser. --- ## First-Time Setup ### Change the default API key The server ships with a development API key (`development-key-change-in-production`). **Change it before exposing the server on your network.** Option A -- edit the config file: ```yaml # server/config/default_config.yaml auth: api_keys: dev: "your-secure-key-here" # replace the dev key ``` Option B -- set an environment variable: ```bash export LEDGRAB_AUTH__API_KEYS__dev="your-secure-key-here" ``` Generate a random key: ```bash openssl rand -hex 32 ``` ### Configure CORS for LAN access By default the server only allows requests from `http://localhost:8080`. To access the dashboard from another machine on your LAN, add its origin: ```yaml # server/config/default_config.yaml server: cors_origins: - "http://localhost:8080" - "http://192.168.1.100:8080" # your server's LAN IP ``` Or via environment variable: ```bash LEDGRAB_SERVER__CORS_ORIGINS='["http://localhost:8080","http://192.168.1.100:8080"]' ``` ### Discover devices Open the dashboard and go to the **Devices** tab. Click **Discover** to find WLED devices on your network via mDNS. You can also add devices manually by IP address. --- ## Configuration Reference The server reads configuration from three sources (in order of priority): 1. **Environment variables** -- prefix `LEDGRAB_`, double underscore as nesting delimiter (e.g., `LEDGRAB_SERVER__PORT=9090`) 2. **YAML config file** -- `server/config/default_config.yaml` (or set `LEDGRAB_CONFIG_PATH` to override) 3. **Built-in defaults** See [`server/.env.example`](server/.env.example) for every available variable with descriptions. ### Key settings | Variable | Default | Description | | -------- | ------- | ----------- | | `LEDGRAB_SERVER__PORT` | `8080` | HTTP listen port | | `LEDGRAB_SERVER__LOG_LEVEL` | `INFO` | `DEBUG`, `INFO`, `WARNING`, `ERROR` | | `LEDGRAB_SERVER__CORS_ORIGINS` | `["http://localhost:8080"]` | Allowed CORS origins (JSON array) | | `LEDGRAB_AUTH__API_KEYS` | `{"dev":"development-key..."}` | API keys (JSON object) | | `LEDGRAB_STORAGE__DATABASE_FILE` | `data/ledgrab.db` | SQLite database path | | `LEDGRAB_MQTT__ENABLED` | `false` | Enable MQTT for HA auto-discovery | | `LEDGRAB_MQTT__BROKER_HOST` | `localhost` | MQTT broker address | | `LEDGRAB_DEMO` | `false` | Enable demo mode (sandbox with virtual devices) | --- ## Troubleshooting ### Server will not start **Check Python version:** ```bash python --version # must be 3.11+ ``` **Check the frontend bundle exists:** ```bash ls server/src/ledgrab/static/dist/app.bundle.js ``` If missing, run `cd server && npm ci && npm run build`. **Check logs:** ```bash # Docker docker compose logs -f # Manual install tail -f logs/ledgrab.log ``` ### Cannot access the dashboard from another machine 1. Verify the server is reachable: `curl http://SERVER_IP:8080/health` 2. Check your firewall allows inbound traffic on port 8080. 3. Add your server's LAN IP to `cors_origins` (see [Configure CORS](#configure-cors-for-lan-access) above). ### WLED device not responding 1. Confirm the device is powered on and connected to Wi-Fi. 2. Test it directly: `curl http://DEVICE_IP/json/info` 3. Check that the server and the device are on the same subnet. 4. Try restarting the WLED device. ### Low FPS or high latency 1. Lower the target FPS in the stream settings. 2. Reduce `border_width` to decrease the number of sampled pixels. 3. Check CPU usage on the server (`htop` or Task Manager). 4. On Windows, install the `perf` extra for GPU-accelerated capture: `pip install ".[perf]"` --- ## Next Steps - [API Documentation](docs/API.md) - [Calibration Guide](docs/CALIBRATION.md) - [Repository Issues](https://git.dolgolyov-family.by/alexei.dolgolyov/ledgrab/issues)