mirror of
https://github.com/lordmathis/llamactl.git
synced 2025-11-05 16:44:22 +00:00
Remove misleading advanced section
This commit is contained in:
@@ -1,316 +0,0 @@
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# Backends
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Llamactl supports multiple backends for running large language models. This guide covers the available backends and their configuration.
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## Llama.cpp Backend
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The primary backend for Llamactl, providing robust support for GGUF models.
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### Features
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- **GGUF Support**: Native support for GGUF model format
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- **GPU Acceleration**: CUDA, OpenCL, and Metal support
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- **Memory Optimization**: Efficient memory usage and mapping
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- **Multi-threading**: Configurable CPU thread utilization
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- **Quantization**: Support for various quantization levels
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### Configuration
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```yaml
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backends:
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llamacpp:
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binary_path: "/usr/local/bin/llama-server"
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default_options:
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threads: 4
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context_size: 2048
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batch_size: 512
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gpu:
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enabled: true
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layers: 35
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```
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### Supported Options
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| Option | Description | Default |
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|--------|-------------|---------|
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| `threads` | Number of CPU threads | 4 |
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| `context_size` | Context window size | 2048 |
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| `batch_size` | Batch size for processing | 512 |
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| `gpu_layers` | Layers to offload to GPU | 0 |
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| `memory_lock` | Lock model in memory | false |
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| `no_mmap` | Disable memory mapping | false |
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| `rope_freq_base` | RoPE frequency base | 10000 |
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| `rope_freq_scale` | RoPE frequency scale | 1.0 |
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### GPU Acceleration
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#### CUDA Setup
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```bash
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# Install CUDA toolkit
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sudo apt update
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sudo apt install nvidia-cuda-toolkit
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# Verify CUDA installation
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nvcc --version
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nvidia-smi
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```
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#### Configuration for GPU
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```json
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{
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"name": "gpu-accelerated",
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"model_path": "/models/llama-2-13b.gguf",
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"port": 8081,
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"options": {
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"gpu_layers": 35,
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"threads": 2,
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"context_size": 4096
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}
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}
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```
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### Performance Tuning
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#### Memory Optimization
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```yaml
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# For limited memory systems
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options:
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context_size: 1024
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batch_size: 256
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no_mmap: true
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memory_lock: false
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# For high-memory systems
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options:
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context_size: 8192
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batch_size: 1024
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memory_lock: true
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no_mmap: false
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```
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#### CPU Optimization
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```yaml
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# Match thread count to CPU cores
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# For 8-core CPU:
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options:
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threads: 6 # Leave 2 cores for system
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# For high-performance CPUs:
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options:
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threads: 16
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batch_size: 1024
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```
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## Future Backends
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Llamactl is designed to support multiple backends. Planned additions:
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### vLLM Backend
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High-performance inference engine optimized for serving:
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- **Features**: Fast inference, batching, streaming
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- **Models**: Supports various model formats
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- **Scaling**: Horizontal scaling support
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### TensorRT-LLM Backend
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NVIDIA's optimized inference engine:
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- **Features**: Maximum GPU performance
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- **Models**: Optimized for NVIDIA GPUs
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- **Deployment**: Production-ready inference
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### Ollama Backend
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Integration with Ollama for easy model management:
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- **Features**: Simplified model downloading
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- **Models**: Large model library
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- **Integration**: Seamless model switching
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## Backend Selection
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### Automatic Detection
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Llamactl can automatically detect the best backend:
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```yaml
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backends:
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auto_detect: true
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preference_order:
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- "llamacpp"
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- "vllm"
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- "tensorrt"
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```
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### Manual Selection
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Force a specific backend for an instance:
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```json
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{
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"name": "manual-backend",
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"backend": "llamacpp",
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"model_path": "/models/model.gguf",
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"port": 8081
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}
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```
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## Backend-Specific Features
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### Llama.cpp Features
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#### Model Formats
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- **GGUF**: Primary format, best compatibility
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- **GGML**: Legacy format (limited support)
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#### Quantization Levels
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- `Q2_K`: Smallest size, lower quality
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- `Q4_K_M`: Balanced size and quality
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- `Q5_K_M`: Higher quality, larger size
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- `Q6_K`: Near-original quality
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- `Q8_0`: Minimal loss, largest size
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#### Advanced Options
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```yaml
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advanced:
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rope_scaling:
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type: "linear"
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factor: 2.0
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attention:
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flash_attention: true
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grouped_query: true
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```
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## Monitoring Backend Performance
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### Metrics Collection
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Monitor backend-specific metrics:
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```bash
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# Get backend statistics
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curl http://localhost:8080/api/instances/my-instance/backend/stats
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```
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**Response:**
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```json
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{
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"backend": "llamacpp",
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"version": "b1234",
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"metrics": {
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"tokens_per_second": 15.2,
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"memory_usage": 4294967296,
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"gpu_utilization": 85.5,
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"context_usage": 75.0
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}
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}
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```
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### Performance Optimization
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#### Benchmark Different Configurations
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```bash
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# Test various thread counts
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for threads in 2 4 8 16; do
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echo "Testing $threads threads"
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curl -X PUT http://localhost:8080/api/instances/benchmark \
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-d "{\"options\": {\"threads\": $threads}}"
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# Run performance test
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done
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```
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#### Memory Usage Optimization
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```bash
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# Monitor memory usage
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watch -n 1 'curl -s http://localhost:8080/api/instances/my-instance/stats | jq .memory_usage'
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```
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## Troubleshooting Backends
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### Common Llama.cpp Issues
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**Model won't load:**
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```bash
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# Check model file
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file /path/to/model.gguf
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# Verify format
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llama-server --model /path/to/model.gguf --dry-run
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```
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**GPU not detected:**
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```bash
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# Check CUDA installation
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nvidia-smi
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# Verify llama.cpp GPU support
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llama-server --help | grep -i gpu
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```
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**Performance issues:**
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```bash
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# Check system resources
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htop
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nvidia-smi
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# Verify configuration
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curl http://localhost:8080/api/instances/my-instance/config
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```
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## Custom Backend Development
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### Backend Interface
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Implement the backend interface for custom backends:
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```go
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type Backend interface {
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Start(config InstanceConfig) error
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Stop(instance *Instance) error
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Health(instance *Instance) (*HealthStatus, error)
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Stats(instance *Instance) (*Stats, error)
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}
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```
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### Registration
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Register your custom backend:
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```go
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func init() {
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backends.Register("custom", &CustomBackend{})
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}
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```
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## Best Practices
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### Production Deployments
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1. **Resource allocation**: Plan for peak usage
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2. **Backend selection**: Choose based on requirements
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3. **Monitoring**: Set up comprehensive monitoring
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4. **Fallback**: Configure backup backends
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### Development
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1. **Rapid iteration**: Use smaller models
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2. **Resource monitoring**: Track usage patterns
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3. **Configuration testing**: Validate settings
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4. **Performance profiling**: Optimize bottlenecks
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## Next Steps
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- Learn about [Monitoring](monitoring.md) backend performance
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- Explore [Troubleshooting](troubleshooting.md) guides
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- Set up [Production Monitoring](monitoring.md)
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@@ -1,420 +0,0 @@
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# Monitoring
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Comprehensive monitoring setup for Llamactl in production environments.
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## Overview
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Effective monitoring of Llamactl involves tracking:
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- Instance health and performance
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- System resource usage
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- API response times
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- Error rates and alerts
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## Built-in Monitoring
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### Health Checks
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Llamactl provides built-in health monitoring:
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```bash
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# Check overall system health
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curl http://localhost:8080/api/system/health
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# Check specific instance health
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curl http://localhost:8080/api/instances/{name}/health
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```
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### Metrics Endpoint
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Access Prometheus-compatible metrics:
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```bash
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curl http://localhost:8080/metrics
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```
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**Available Metrics:**
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- `llamactl_instances_total`: Total number of instances
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- `llamactl_instances_running`: Number of running instances
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- `llamactl_instance_memory_bytes`: Instance memory usage
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- `llamactl_instance_cpu_percent`: Instance CPU usage
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- `llamactl_api_requests_total`: Total API requests
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- `llamactl_api_request_duration_seconds`: API response times
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## Prometheus Integration
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### Configuration
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Add Llamactl as a Prometheus target:
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```yaml
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# prometheus.yml
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scrape_configs:
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- job_name: 'llamactl'
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static_configs:
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- targets: ['localhost:8080']
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metrics_path: '/metrics'
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scrape_interval: 15s
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```
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### Custom Metrics
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Enable additional metrics in Llamactl:
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```yaml
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# config.yaml
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monitoring:
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enabled: true
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prometheus:
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enabled: true
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path: "/metrics"
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metrics:
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- instance_stats
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- api_performance
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- system_resources
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```
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## Grafana Dashboards
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### Llamactl Dashboard
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Import the official Grafana dashboard:
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1. Download dashboard JSON from releases
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2. Import into Grafana
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3. Configure Prometheus data source
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### Key Panels
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**Instance Overview:**
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- Instance count and status
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- Resource usage per instance
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- Health status indicators
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**Performance Metrics:**
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- API response times
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- Tokens per second
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- Memory usage trends
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**System Resources:**
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- CPU and memory utilization
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- Disk I/O and network usage
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- GPU utilization (if applicable)
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|
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### Custom Queries
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**Instance Uptime:**
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```promql
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(time() - llamactl_instance_start_time_seconds) / 3600
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```
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**Memory Usage Percentage:**
|
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```promql
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(llamactl_instance_memory_bytes / llamactl_system_memory_total_bytes) * 100
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```
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**API Error Rate:**
|
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```promql
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rate(llamactl_api_requests_total{status=~"4.."}[5m]) / rate(llamactl_api_requests_total[5m]) * 100
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```
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||||
|
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## Alerting
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||||
|
||||
### Prometheus Alerts
|
||||
|
||||
Configure alerts for critical conditions:
|
||||
|
||||
```yaml
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# alerts.yml
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groups:
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||||
- name: llamactl
|
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rules:
|
||||
- alert: InstanceDown
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expr: llamactl_instance_up == 0
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for: 1m
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labels:
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severity: critical
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annotations:
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summary: "Llamactl instance {{ $labels.instance_name }} is down"
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||||
|
||||
- alert: HighMemoryUsage
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expr: llamactl_instance_memory_percent > 90
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for: 5m
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labels:
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severity: warning
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annotations:
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summary: "High memory usage on {{ $labels.instance_name }}"
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||||
|
||||
- alert: APIHighLatency
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expr: histogram_quantile(0.95, rate(llamactl_api_request_duration_seconds_bucket[5m])) > 2
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for: 2m
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labels:
|
||||
severity: warning
|
||||
annotations:
|
||||
summary: "High API latency detected"
|
||||
```
|
||||
|
||||
### Notification Channels
|
||||
|
||||
Configure alert notifications:
|
||||
|
||||
**Slack Integration:**
|
||||
```yaml
|
||||
# alertmanager.yml
|
||||
route:
|
||||
group_by: ['alertname']
|
||||
receiver: 'slack'
|
||||
|
||||
receivers:
|
||||
- name: 'slack'
|
||||
slack_configs:
|
||||
- api_url: 'https://hooks.slack.com/services/...'
|
||||
channel: '#alerts'
|
||||
title: 'Llamactl Alert'
|
||||
text: '{{ range .Alerts }}{{ .Annotations.summary }}{{ end }}'
|
||||
```
|
||||
|
||||
## Log Management
|
||||
|
||||
### Centralized Logging
|
||||
|
||||
Configure log aggregation:
|
||||
|
||||
```yaml
|
||||
# config.yaml
|
||||
logging:
|
||||
level: "info"
|
||||
output: "json"
|
||||
destinations:
|
||||
- type: "file"
|
||||
path: "/var/log/llamactl/app.log"
|
||||
- type: "syslog"
|
||||
facility: "local0"
|
||||
- type: "elasticsearch"
|
||||
url: "http://elasticsearch:9200"
|
||||
```
|
||||
|
||||
### Log Analysis
|
||||
|
||||
Use ELK stack for log analysis:
|
||||
|
||||
**Elasticsearch Index Template:**
|
||||
```json
|
||||
{
|
||||
"index_patterns": ["llamactl-*"],
|
||||
"mappings": {
|
||||
"properties": {
|
||||
"timestamp": {"type": "date"},
|
||||
"level": {"type": "keyword"},
|
||||
"message": {"type": "text"},
|
||||
"instance": {"type": "keyword"},
|
||||
"component": {"type": "keyword"}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**Kibana Visualizations:**
|
||||
- Log volume over time
|
||||
- Error rate by instance
|
||||
- Performance trends
|
||||
- Resource usage patterns
|
||||
|
||||
## Application Performance Monitoring
|
||||
|
||||
### OpenTelemetry Integration
|
||||
|
||||
Enable distributed tracing:
|
||||
|
||||
```yaml
|
||||
# config.yaml
|
||||
telemetry:
|
||||
enabled: true
|
||||
otlp:
|
||||
endpoint: "http://jaeger:14268/api/traces"
|
||||
sampling_rate: 0.1
|
||||
```
|
||||
|
||||
### Custom Spans
|
||||
|
||||
Add custom tracing to track operations:
|
||||
|
||||
```go
|
||||
ctx, span := tracer.Start(ctx, "instance.start")
|
||||
defer span.End()
|
||||
|
||||
// Track instance startup time
|
||||
span.SetAttributes(
|
||||
attribute.String("instance.name", name),
|
||||
attribute.String("model.path", modelPath),
|
||||
)
|
||||
```
|
||||
|
||||
## Health Check Configuration
|
||||
|
||||
### Readiness Probes
|
||||
|
||||
Configure Kubernetes readiness probes:
|
||||
|
||||
```yaml
|
||||
readinessProbe:
|
||||
httpGet:
|
||||
path: /api/health
|
||||
port: 8080
|
||||
initialDelaySeconds: 30
|
||||
periodSeconds: 10
|
||||
```
|
||||
|
||||
### Liveness Probes
|
||||
|
||||
Configure liveness probes:
|
||||
|
||||
```yaml
|
||||
livenessProbe:
|
||||
httpGet:
|
||||
path: /api/health/live
|
||||
port: 8080
|
||||
initialDelaySeconds: 60
|
||||
periodSeconds: 30
|
||||
```
|
||||
|
||||
### Custom Health Checks
|
||||
|
||||
Implement custom health checks:
|
||||
|
||||
```go
|
||||
func (h *HealthHandler) CustomCheck(ctx context.Context) error {
|
||||
// Check database connectivity
|
||||
if err := h.db.Ping(); err != nil {
|
||||
return fmt.Errorf("database unreachable: %w", err)
|
||||
}
|
||||
|
||||
// Check instance responsiveness
|
||||
for _, instance := range h.instances {
|
||||
if !instance.IsHealthy() {
|
||||
return fmt.Errorf("instance %s unhealthy", instance.Name)
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
```
|
||||
|
||||
## Performance Profiling
|
||||
|
||||
### pprof Integration
|
||||
|
||||
Enable Go profiling:
|
||||
|
||||
```yaml
|
||||
# config.yaml
|
||||
debug:
|
||||
pprof_enabled: true
|
||||
pprof_port: 6060
|
||||
```
|
||||
|
||||
Access profiling endpoints:
|
||||
```bash
|
||||
# CPU profile
|
||||
go tool pprof http://localhost:6060/debug/pprof/profile
|
||||
|
||||
# Memory profile
|
||||
go tool pprof http://localhost:6060/debug/pprof/heap
|
||||
|
||||
# Goroutine profile
|
||||
go tool pprof http://localhost:6060/debug/pprof/goroutine
|
||||
```
|
||||
|
||||
### Continuous Profiling
|
||||
|
||||
Set up continuous profiling with Pyroscope:
|
||||
|
||||
```yaml
|
||||
# config.yaml
|
||||
profiling:
|
||||
enabled: true
|
||||
pyroscope:
|
||||
server_address: "http://pyroscope:4040"
|
||||
application_name: "llamactl"
|
||||
```
|
||||
|
||||
## Security Monitoring
|
||||
|
||||
### Audit Logging
|
||||
|
||||
Enable security audit logs:
|
||||
|
||||
```yaml
|
||||
# config.yaml
|
||||
audit:
|
||||
enabled: true
|
||||
log_file: "/var/log/llamactl/audit.log"
|
||||
events:
|
||||
- "auth.login"
|
||||
- "auth.logout"
|
||||
- "instance.create"
|
||||
- "instance.delete"
|
||||
- "config.update"
|
||||
```
|
||||
|
||||
### Rate Limiting Monitoring
|
||||
|
||||
Track rate limiting metrics:
|
||||
|
||||
```bash
|
||||
# Monitor rate limit hits
|
||||
curl http://localhost:8080/metrics | grep rate_limit
|
||||
```
|
||||
|
||||
## Troubleshooting Monitoring
|
||||
|
||||
### Common Issues
|
||||
|
||||
**Metrics not appearing:**
|
||||
1. Check Prometheus configuration
|
||||
2. Verify network connectivity
|
||||
3. Review Llamactl logs for errors
|
||||
|
||||
**High memory usage:**
|
||||
1. Check for memory leaks in profiles
|
||||
2. Monitor garbage collection metrics
|
||||
3. Review instance configurations
|
||||
|
||||
**Alert fatigue:**
|
||||
1. Tune alert thresholds
|
||||
2. Implement alert severity levels
|
||||
3. Use alert routing and suppression
|
||||
|
||||
### Debug Tools
|
||||
|
||||
**Monitoring health:**
|
||||
```bash
|
||||
# Check monitoring endpoints
|
||||
curl -v http://localhost:8080/metrics
|
||||
curl -v http://localhost:8080/api/health
|
||||
|
||||
# Review logs
|
||||
tail -f /var/log/llamactl/app.log
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
### Production Monitoring
|
||||
|
||||
1. **Comprehensive coverage**: Monitor all critical components
|
||||
2. **Appropriate alerting**: Balance sensitivity and noise
|
||||
3. **Regular review**: Analyze trends and patterns
|
||||
4. **Documentation**: Maintain runbooks for alerts
|
||||
|
||||
### Performance Optimization
|
||||
|
||||
1. **Baseline establishment**: Know normal operating parameters
|
||||
2. **Trend analysis**: Identify performance degradation early
|
||||
3. **Capacity planning**: Monitor resource growth trends
|
||||
4. **Optimization cycles**: Regular performance tuning
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Set up [Troubleshooting](troubleshooting.md) procedures
|
||||
- Learn about [Backend optimization](backends.md)
|
||||
- Configure [Production deployment](../development/building.md)
|
||||
@@ -148,15 +148,3 @@ llamactl --help
|
||||
```
|
||||
|
||||
You can also override configuration using command line flags when starting llamactl.
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Learn about [Managing Instances](../user-guide/managing-instances.md)
|
||||
- Explore [Advanced Configuration](../advanced/monitoring.md)
|
||||
- Set up [Monitoring](../advanced/monitoring.md)
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Learn about [Managing Instances](../user-guide/managing-instances.md)
|
||||
- Explore [Advanced Configuration](../advanced/monitoring.md)
|
||||
- Set up [Monitoring](../advanced/monitoring.md)
|
||||
|
||||
@@ -40,14 +40,13 @@ Llamactl is designed to simplify the deployment and management of llama-server i
|
||||
- [Web UI Guide](user-guide/web-ui.md) - Learn to use the web interface
|
||||
- [Managing Instances](user-guide/managing-instances.md) - Instance lifecycle management
|
||||
- [API Reference](user-guide/api-reference.md) - Complete API documentation
|
||||
- [Monitoring](advanced/monitoring.md) - Health checks and monitoring
|
||||
- [Backends](advanced/backends.md) - Backend configuration options
|
||||
|
||||
|
||||
## Getting Help
|
||||
|
||||
If you need help or have questions:
|
||||
|
||||
- Check the [Troubleshooting](advanced/troubleshooting.md) guide
|
||||
- Check the [Troubleshooting](user-guide/troubleshooting.md) guide
|
||||
- Visit the [GitHub repository](https://github.com/lordmathis/llamactl)
|
||||
- Review the [Configuration Guide](getting-started/configuration.md) for advanced settings
|
||||
|
||||
|
||||
@@ -462,9 +462,3 @@ curl -X POST http://localhost:8080/api/instances/example/stop
|
||||
# Delete instance
|
||||
curl -X DELETE http://localhost:8080/api/instances/example
|
||||
```
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Learn about [Managing Instances](managing-instances.md) in detail
|
||||
- Explore [Advanced Configuration](../advanced/backends.md)
|
||||
- Set up [Monitoring](../advanced/monitoring.md) for production use
|
||||
|
||||
@@ -163,9 +163,3 @@ curl -X POST http://localhost:8080/api/instances/stop-all
|
||||
# Get status of all instances
|
||||
curl http://localhost:8080/api/instances
|
||||
```
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Learn about the [Web UI](web-ui.md) interface
|
||||
- Explore the complete [API Reference](api-reference.md)
|
||||
- Set up [Monitoring](../advanced/monitoring.md) for production use
|
||||
|
||||
@@ -552,9 +552,3 @@ cp ~/.llamactl/config.yaml ~/.llamactl/config.yaml.backup
|
||||
# Backup instance configurations
|
||||
curl http://localhost:8080/api/instances > instances-backup.json
|
||||
```
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Set up [Monitoring](monitoring.md) to prevent issues
|
||||
- Learn about [Advanced Configuration](backends.md)
|
||||
- Review [Best Practices](../development/contributing.md)
|
||||
@@ -208,9 +208,3 @@ Some features may be limited on mobile:
|
||||
- Log viewing (use horizontal scrolling)
|
||||
- Complex configuration forms
|
||||
- File browser functionality
|
||||
|
||||
## Next Steps
|
||||
|
||||
- Learn about [API Reference](api-reference.md) for programmatic access
|
||||
- Set up [Monitoring](../advanced/monitoring.md) for production use
|
||||
- Explore [Advanced Configuration](../advanced/backends.md) options
|
||||
|
||||
Reference in New Issue
Block a user