feat: pre-commit results

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Young Han 2025-07-14 13:21:33 -07:00
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<!-- This file was auto-generated by distro_codegen.py, please edit source -->
# Llama Stack with llama.cpp
This template shows you how to run Llama Stack with [llama.cpp](https://github.com/ggerganov/llama.cpp) as the inference provider.
## Prerequisites
1. **Install llama.cpp**: Follow the installation instructions from the [llama.cpp repository](https://github.com/ggerganov/llama.cpp)
2. **Download a model**: Download a GGUF format model file (e.g., from Hugging Face)
## Starting llama.cpp Server
Before running Llama Stack, you need to start the llama.cpp server:
```bash
# Example: Start llama.cpp server with a model
./llama-server -m /path/to/your/YOUR_MODEL.gguf -c 4096 --host 0.0.0.0 --port 8080 --api-key YOUR_API_KEY --jinja -cb
```
Common llama.cpp server options:
- `-m`: Path to the GGUF model file
- `-c`: Context size (default: 512)
- `--host`: Host to bind to (default: 127.0.0.1)
- `--port`: Port to bind to (default: 8080)
- `-ngl`: Number of layers to offload to GPU
- `--chat-template`: Chat template to use
## Environment Variables
Set these environment variables before running Llama Stack:
```bash
export LLAMACPP_URL=http://localhost:8080 # URL of your llama.cpp server (without /v1 suffix)
export INFERENCE_MODEL=your-model-name # Name/identifier without gguf extension
export LLAMACPP_API_KEY="YOUR_API_KEY" # API key (leave empty for local servers)
```
## Running Llama Stack
The model name will be you gguf file name without the extension.
```bash
llama stack build --template llamacpp --image-type conda
llama stack run llamacpp --image-type conda
```
## Configuration
The template uses the following configuration:
- **Inference Provider**: `remote::llamacpp` - Connects to your llama.cpp server via OpenAI-compatible API
- **Default URL**: `http://localhost:8080` (configurable via `LLAMACPP_URL`)
- **Vector Store**: FAISS for local vector storage
- **Safety**: Llama Guard for content safety
- **Other providers**: Standard Meta reference implementations
## Model Support
This template works with any GGUF format model supported by llama.cpp, including:
- Llama 2/3 models
- Code Llama models
- Other transformer-based models converted to GGUF format
## Troubleshooting
1. **Connection refused**: Make sure your llama.cpp server is running and accessible
2. **Model not found**: Verify the model path and that the GGUF file exists
3. **Out of memory**: Reduce context size (`-c`) or use GPU offloading (`-ngl`)
4. **Slow inference**: Consider using GPU acceleration or quantized models
## Advanced Configuration
You can customize the llama.cpp server configuration by modifying the server startup command. For production use, consider:
- Using GPU acceleration with `-ngl` parameter
- Adjusting batch size with `-b` parameter
- Setting appropriate context size with `-c` parameter
- Using multiple threads with `-t` parameter
For more llama.cpp server options, run:
```bash
./llama-server --help
```

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- [remote::hf::endpoint](remote_hf_endpoint.md) - [remote::hf::endpoint](remote_hf_endpoint.md)
- [remote::hf::serverless](remote_hf_serverless.md) - [remote::hf::serverless](remote_hf_serverless.md)
- [remote::llama-openai-compat](remote_llama-openai-compat.md) - [remote::llama-openai-compat](remote_llama-openai-compat.md)
- [remote::llamacpp](remote_llamacpp.md)
- [remote::nvidia](remote_nvidia.md) - [remote::nvidia](remote_nvidia.md)
- [remote::ollama](remote_ollama.md) - [remote::ollama](remote_ollama.md)
- [remote::openai](remote_openai.md) - [remote::openai](remote_openai.md)

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# remote::llamacpp
## Configuration
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `str \| None` | No | | The llama.cpp server API key (optional for local servers) |
| `openai_compat_api_base` | `<class 'str'>` | No | http://localhost:8080/v1 | The URL for the llama.cpp server with OpenAI-compatible API |
## Sample Configuration
```yaml
openai_compat_api_base: ${env.LLAMACPP_URL:http://localhost:8080}/v1
api_key: ${env.LLAMACPP_API_KEY:}
```