mirror of
https://github.com/lordmathis/llamactl.git
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Initial support for docker
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45
.dockerignore
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45
.dockerignore
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# Git and version control
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.git/
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.gitignore
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# Documentation
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*.md
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docs/
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# Development files
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.vscode/
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.idea/
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# Build artifacts
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webui/node_modules/
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webui/dist/
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webui/.next/
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*.log
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*.tmp
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# Data directories
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data/
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models/
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logs/
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# Test files
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*_test.go
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**/*_test.go
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# CI/CD
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.github/
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# Local configuration
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llamactl.yaml
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config.yaml
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.env
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.env.local
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# OS files
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.DS_Store
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Thumbs.db
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# Backup files
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*.bak
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*.backup
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*~
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Dockerfile.llamacpp
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Dockerfile.llamacpp
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FROM ghcr.io/ggml-org/llama.cpp:server
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# Install curl for downloading llamactl
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RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/*
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# Download and install the latest llamactl release
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RUN LATEST_VERSION=$(curl -s https://api.github.com/repos/lordmathis/llamactl/releases/latest | grep '"tag_name":' | sed -E 's/.*"([^"]+)".*/\1/') && \
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curl -L "https://github.com/lordmathis/llamactl/releases/download/${LATEST_VERSION}/llamactl-${LATEST_VERSION}-linux-amd64.tar.gz" | tar -xz && \
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mv llamactl /usr/local/bin/ && \
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chmod +x /usr/local/bin/llamactl
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# Create data directory for llamactl
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RUN mkdir -p /data
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# Set working directory
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WORKDIR /data
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# Expose the default llamactl port
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EXPOSE 8080
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# Set llamactl as the entrypoint
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ENTRYPOINT ["llamactl"]
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Dockerfile.vllm
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Dockerfile.vllm
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FROM vllm/vllm-openai:latest
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# Install curl for downloading llamactl
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RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/*
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# Download and install the latest llamactl release
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RUN LATEST_VERSION=$(curl -s https://api.github.com/repos/lordmathis/llamactl/releases/latest | grep '"tag_name":' | sed -E 's/.*"([^"]+)".*/\1/') && \
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curl -L "https://github.com/lordmathis/llamactl/releases/download/${LATEST_VERSION}/llamactl-${LATEST_VERSION}-linux-amd64.tar.gz" | tar -xz && \
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mv llamactl /usr/local/bin/ && \
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chmod +x /usr/local/bin/llamactl
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# Create data directory for llamactl
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RUN mkdir -p /data
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# Set working directory
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WORKDIR /data
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# Expose the default llamactl port
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EXPOSE 8080
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# Set llamactl as the entrypoint
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ENTRYPOINT ["llamactl"]
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25
README.md
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README.md
@@ -95,7 +95,26 @@ sudo mv llamactl /usr/local/bin/
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# Windows - Download from releases page
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```
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### Option 2: Build from Source
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### Option 2: Docker (No local backend installation required)
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```bash
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# Clone repository and build Docker images
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git clone https://github.com/lordmathis/llamactl.git
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cd llamactl
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mkdir -p data/llamacpp data/vllm models
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# Build and start llamactl with llama.cpp CUDA backend
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docker-compose up llamactl-llamacpp -d
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# Build and start llamactl with vLLM CUDA backend
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docker-compose up llamactl-vllm -d
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```
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**Features:** Full CUDA support, automatic latest release installation, no backend dependencies.
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For detailed Docker setup and configuration, see the [Installation Guide](docs/getting-started/installation.md).
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### Option 3: Build from Source
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Requires Go 1.24+ and Node.js 22+
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```bash
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git clone https://github.com/lordmathis/llamactl.git
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@@ -147,9 +166,9 @@ pip install vllm
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# Or use Docker - no local installation required
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```
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## Docker Support
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## Backend Docker Support
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llamactl supports running backends in Docker containers - perfect for production deployments without local backend installation. Simply enable Docker in your configuration:
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llamactl can run backends in Docker containers:
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```yaml
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backends:
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docker-compose.yml
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docker-compose.yml
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version: '3.8'
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services:
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llamactl-llamacpp:
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build:
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context: .
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dockerfile: Dockerfile.llamacpp
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image: llamactl:llamacpp-cuda
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container_name: llamactl-llamacpp
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ports:
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- "8080:8080"
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volumes:
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- ./data/llamacpp:/data
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- ./models:/models # Mount models directory
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environment:
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# Configure llamactl to use llama-server from the base image
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- LLAMACTL_LLAMACPP_COMMAND=llama-server
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# Enable Docker mode for nested containers (if needed)
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- LLAMACTL_LLAMACPP_DOCKER_ENABLED=false
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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restart: unless-stopped
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llamactl-vllm:
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build:
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context: .
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dockerfile: Dockerfile.vllm
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image: llamactl:vllm-cuda
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container_name: llamactl-vllm
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ports:
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- "8081:8080" # Use different port to avoid conflicts
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volumes:
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- ./data/vllm:/data
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- ./models:/models # Mount models directory
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- ~/.cache/huggingface:/root/.cache/huggingface # HuggingFace cache
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environment:
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# Configure llamactl to use vllm from the base image
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- LLAMACTL_VLLM_COMMAND=vllm
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- LLAMACTL_VLLM_ARGS=serve
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# Enable Docker mode for nested containers (if needed)
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- LLAMACTL_VLLM_DOCKER_ENABLED=false
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# vLLM specific environment variables
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- CUDA_VISIBLE_DEVICES=all
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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restart: unless-stopped
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networks:
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default:
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name: llamactl-network
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@@ -71,7 +71,72 @@ sudo mv llamactl /usr/local/bin/
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# Windows - Download from releases page
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```
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### Option 2: Build from Source
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### Option 2: Docker
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llamactl provides Dockerfiles for creating Docker images with CUDA support for llama.cpp and vLLM backends. The resulting images include the latest llamactl release with the respective backend pre-installed.
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**Available Dockerfiles:**
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- **llamactl with llama.cpp CUDA**: `Dockerfile.llamacpp` (based on `ghcr.io/ggml-org/llama.cpp:server`)
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- **llamactl with vLLM CUDA**: `Dockerfile.vllm` (based on `vllm/vllm-openai:latest`)
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#### Using Docker Compose
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```bash
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# Clone the repository
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git clone https://github.com/lordmathis/llamactl.git
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cd llamactl
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# Create directories for data and models
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mkdir -p data/llamacpp data/vllm models
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# Start llamactl with llama.cpp backend
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docker-compose up llamactl-llamacpp -d
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# Or start llamactl with vLLM backend
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docker-compose up llamactl-vllm -d
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```
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Access the dashboard at:
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- llamactl with llama.cpp: http://localhost:8080
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- llamactl with vLLM: http://localhost:8081
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#### Using Docker Build and Run
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**llamactl with llama.cpp CUDA:**
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```bash
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docker build -f Dockerfile.llamacpp -t llamactl:llamacpp-cuda .
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docker run -d \
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--name llamactl-llamacpp \
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--gpus all \
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-p 8080:8080 \
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-v $(pwd)/data/llamacpp:/data \
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-v $(pwd)/models:/models \
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-e LLAMACTL_LLAMACPP_COMMAND=llama-server \
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llamactl:llamacpp-cuda
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```
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**llamactl with vLLM CUDA:**
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```bash
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docker build -f Dockerfile.vllm -t llamactl:vllm-cuda .
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docker run -d \
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--name llamactl-vllm \
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--gpus all \
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-p 8080:8080 \
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-v $(pwd)/data/vllm:/data \
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-v $(pwd)/models:/models \
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-v ~/.cache/huggingface:/root/.cache/huggingface \
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-e LLAMACTL_VLLM_COMMAND=vllm \
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-e LLAMACTL_VLLM_ARGS=serve \
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llamactl:vllm-cuda
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```
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**Docker-Specific Configuration:**
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- Set `LLAMACTL_LLAMACPP_COMMAND=llama-server` to use the pre-installed llama-server
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- Set `LLAMACTL_VLLM_COMMAND=vllm` to use the pre-installed vLLM
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- Volume mount `/data` for llamactl data and `/models` for your model files
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- Use `--gpus all` for GPU access
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### Option 3: Build from Source
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Requirements:
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- Go 1.24 or later
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