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![Build and Release](https://github.com/lordmathis/llamactl/actions/workflows/release.yaml/badge.svg) ![Go Tests](https://github.com/lordmathis/llamactl/actions/workflows/go_test.yaml/badge.svg) ![WebUI Tests](https://github.com/lordmathis/llamactl/actions/workflows/webui_test.yaml/badge.svg)
A control server for managing multiple Llama Server instances with a web-based dashboard.
**Management server for multiple llama.cpp instances with OpenAI-compatible API routing.**
## Features
## Why llamactl?
- **Multi-instance Management**: Create, start, stop, restart, and delete multiple llama-server instances
- **Web Dashboard**: Modern React-based UI for managing instances
- **Auto-restart**: Configurable automatic restart on instance failure
- **Instance Monitoring**: Real-time health checks and status monitoring
- **Log Management**: View, search, and download instance logs
- **Data Persistence**: Persistent storage of instance state.
- **REST API**: Full API for programmatic control
- **OpenAI Compatible**: Route requests to instances by instance name
- **Configuration Management**: Comprehensive llama-server parameter support
- **System Information**: View llama-server version, devices, and help
- **API Key Authentication**: Secure access with separate management and inference keys
🚀 **Multiple Model Serving**: Run different models simultaneously (7B for speed, 70B for quality)
🔗 **OpenAI API Compatible**: Drop-in replacement - route requests by model name
🌐 **Web Dashboard**: Modern React UI for visual management (unlike CLI-only tools)
🔐 **API Key Authentication**: Separate keys for management vs inference access
📊 **Instance Monitoring**: Health checks, auto-restart, log management
⚡ **Persistent State**: Instances survive server restarts
## Prerequisites
**Choose llamactl if**: You need authentication, health monitoring, auto-restart, and centralized management of multiple llama-server instances
**Choose Ollama if**: You want the simplest setup with strong community ecosystem and third-party integrations
**Choose LM Studio if**: You prefer a polished desktop GUI experience with easy model management
This project requires `llama-server` from llama.cpp to be installed and available in your PATH.
## Quick Start
**Install llama.cpp:**
Follow the installation instructions at https://github.com/ggml-org/llama.cpp
```bash
# 1. Install llama-server (one-time setup)
# See: https://github.com/ggml-org/llama.cpp#quick-start
# 2. Download and run llamactl
LATEST_VERSION=$(curl -s https://api.github.com/repos/lordmathis/llamactl/releases/latest | grep '"tag_name":' | sed -E 's/.*"([^"]+)".*/\1/')
curl -L https://github.com/lordmathis/llamactl/releases/download/${LATEST_VERSION}/llamactl-${LATEST_VERSION}-linux-amd64.tar.gz | tar -xz
sudo mv llamactl /usr/local/bin/
# 3. Start the server
llamactl
# Access dashboard at http://localhost:8080
```
## Usage
### Create and manage instances via web dashboard:
1. Open http://localhost:8080
2. Click "Create Instance"
3. Set model path and GPU layers
4. Start or stop the instance
### Or use the REST API:
```bash
# Create instance
curl -X POST localhost:8080/api/v1/instances/my-7b-model \
-H "Authorization: Bearer your-key" \
-d '{"model": "/path/to/model.gguf", "gpu_layers": 32}'
# Use with OpenAI SDK
curl -X POST localhost:8080/v1/chat/completions \
-H "Authorization: Bearer your-key" \
-d '{"model": "my-7b-model", "messages": [{"role": "user", "content": "Hello!"}]}'
```
## Installation
### Download Prebuilt Binaries
### Option 1: Download Binary (Recommended)
The easiest way to install llamactl is to download a prebuilt binary from the [releases page](https://github.com/lordmathis/llamactl/releases).
**Linux/macOS:**
```bash
# Download the latest release for your platform
curl -L https://github.com/lordmathis/llamactl/releases/latest/download/llamactl-$(curl -s https://api.github.com/repos/lordmathis/llamactl/releases/latest | grep tag_name | cut -d '"' -f 4)-linux-amd64.tar.gz | tar -xz
# Move to PATH
# Linux/macOS - Get latest version and download
LATEST_VERSION=$(curl -s https://api.github.com/repos/lordmathis/llamactl/releases/latest | grep '"tag_name":' | sed -E 's/.*"([^"]+)".*/\1/')
curl -L https://github.com/lordmathis/llamactl/releases/download/${LATEST_VERSION}/llamactl-${LATEST_VERSION}-$(uname -s | tr '[:upper:]' '[:lower:]')-$(uname -m).tar.gz | tar -xz
sudo mv llamactl /usr/local/bin/
# Run the server
llamactl
# Or download manually from the releases page:
# https://github.com/lordmathis/llamactl/releases/latest
# Windows - Download from releases page
```
**Manual Download:**
1. Go to the [releases page](https://github.com/lordmathis/llamactl/releases)
2. Download the appropriate archive for your platform
3. Extract the archive and move the binary to a directory in your PATH
### Build from Source
If you prefer to build from source or need the latest development version:
#### Build Requirements
- Go 1.24 or later
- Node.js 22 or later (for building the web UI)
#### Building with Web UI
### Option 2: Build from Source
Requires Go 1.24+ and Node.js 22+
```bash
# Clone the repository
git clone https://github.com/lordmathis/llamactl.git
cd llamactl
# Install Node.js dependencies
cd webui
npm ci
# Build the web UI
npm run build
# Return to project root and build
cd ..
cd webui && npm ci && npm run build && cd ..
go build -o llamactl ./cmd/server
```
# Run the server
./llamactl
## Prerequisites
You need `llama-server` from [llama.cpp](https://github.com/ggml-org/llama.cpp) installed:
```bash
# Quick install methods:
# Homebrew (macOS)
brew install llama.cpp
# Or build from source - see llama.cpp docs
```
## Configuration
llamactl can be configured via configuration files or environment variables. Configuration is loaded in the following order of precedence:
llamactl works out of the box with sensible defaults.
1. Hardcoded defaults
2. Configuration file
3. Environment variables
```yaml
server:
host: "0.0.0.0" # Server host to bind to
port: 8080 # Server port to bind to
allowed_origins: ["*"] # Allowed CORS origins (default: all)
enable_swagger: false # Enable Swagger UI for API docs
instances:
port_range: [8000, 9000] # Port range for instances
data_dir: ~/.local/share/llamactl # Data directory (platform-specific, see below)
configs_dir: ~/.local/share/llamactl/instances # Instance configs directory
logs_dir: ~/.local/share/llamactl/logs # Logs directory
auto_create_dirs: true # Auto-create data/config/logs dirs if missing
max_instances: -1 # Max instances (-1 = unlimited)
llama_executable: llama-server # Path to llama-server executable
default_auto_restart: true # Auto-restart new instances by default
default_max_restarts: 3 # Max restarts for new instances
default_restart_delay: 5 # Restart delay (seconds) for new instances
auth:
require_inference_auth: true # Require auth for inference endpoints
inference_keys: [] # Keys for inference endpoints
require_management_auth: true # Require auth for management endpoints
management_keys: [] # Keys for management endpoints
```
<details><summary><strong>Full Configuration Guide</strong></summary>
llamactl can be configured via configuration files or environment variables. Configuration is loaded in the following order of precedence:
```
Defaults < Configuration file < Environment variables
```
### Configuration Files
@@ -168,147 +210,8 @@ auth:
- `LLAMACTL_REQUIRE_MANAGEMENT_AUTH` - Require auth for management endpoints (true/false)
- `LLAMACTL_MANAGEMENT_KEYS` - Comma-separated management API keys
### Example Configuration
```yaml
server:
host: "0.0.0.0"
port: 8080
instances:
port_range: [8001, 8100]
data_dir: "/var/lib/llamactl"
configs_dir: "/var/lib/llamactl/instances"
logs_dir: "/var/log/llamactl"
auto_create_dirs: true
max_instances: 10
llama_executable: "/usr/local/bin/llama-server"
default_auto_restart: true
default_max_restarts: 5
default_restart_delay: 10
auth:
require_inference_auth: true
inference_keys: ["sk-inference-abc123"]
require_management_auth: true
management_keys: ["sk-management-xyz456"]
```
## Usage
### Starting the Server
```bash
# Start with default configuration
./llamactl
# Start with custom config file
LLAMACTL_CONFIG_PATH=/path/to/config.yaml ./llamactl
# Start with environment variables
LLAMACTL_PORT=9090 LLAMACTL_LOG_DIR=/custom/logs ./llamactl
```
### Authentication
llamactl supports API Key authentication for both management and inference (OpenAI-compatible) endpoints. There are separate keys for management and inference APIs:
- **Management keys** grant full access to instance management
- **Inference keys** grant access to OpenAI-compatible endpoints
- Management keys also work for inference endpoints (higher privilege)
**How to Use:**
Pass your API key in requests using one of:
- `Authorization: Bearer <key>` header
- `X-API-Key: <key>` header
- `api_key=<key>` query parameter
**Auto-generated keys**: If no keys are set and authentication is required, a key will be generated and printed to the terminal at startup. For production, set your own keys in config or environment variables.
### Web Dashboard
Open your browser and navigate to `http://localhost:8080` to access the web dashboard.
### API Usage
The REST API is available at `http://localhost:8080/api/v1`. See the Swagger documentation at `http://localhost:8080/swagger/` for complete API reference.
#### Create an Instance
```bash
curl -X POST http://localhost:8080/api/v1/instances/my-instance \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-management-your-key" \
-d '{
"model": "/path/to/model.gguf",
"gpu_layers": 32,
"auto_restart": true
}'
```
#### List Instances
```bash
curl -H "Authorization: Bearer sk-management-your-key" \
http://localhost:8080/api/v1/instances
```
#### Start/Stop Instance
```bash
# Start
curl -X POST \
-H "Authorization: Bearer sk-management-your-key" \
http://localhost:8080/api/v1/instances/my-instance/start
# Stop
curl -X POST \
-H "Authorization: Bearer sk-management-your-key" \
http://localhost:8080/api/v1/instances/my-instance/stop
```
### OpenAI Compatible Endpoints
Route requests to instances by including the instance name as the model parameter:
```bash
curl -X POST http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-inference-your-key" \
-d '{
"model": "my-instance",
"messages": [{"role": "user", "content": "Hello!"}]
}'
```
## Development
### Running Tests
```bash
# Go tests
go test ./...
# Web UI tests
cd webui
npm test
```
### Development Server
```bash
# Start Go server in development mode
go run ./cmd/server
# Start web UI development server (in another terminal)
cd webui
npm run dev
```
## API Documentation
Interactive API documentation is available at `http://localhost:8080/swagger/` when the server is running.
</details>
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
MIT License - see [LICENSE](LICENSE) file.