How to run OllOllama on Docker

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AI Summary

Summary: Installing and Running Ollama with Docker

• Installation Methods:
  • Primary method: Use the installer from Ollama.com.
  • Alternative method: Use Docker for a self-contained environment.
• Docker Advantages:
  • Isolates dependencies.
  • Clean removal of programs.
• Performance Considerations:
  • Minor performance impact on Linux.
  • More significant impact on Mac and Windows due to virtual machines.
  • No GPU pass-through on Mac.
• Model Storage:
  • Models are stored separately due to their large size.
  • Docker allows flexibility in model storage location.
• Docker Setup:
  • Assumes Docker is installed.
  • Command: docker run -g gpus=all -v <host_dir>:<container_dir> -p 11434:11434 --name Ollama <image_name>
• Docker Commands:
  • docker run: Starts a new container.
  • -d: Runs container in the background.
  • --gpus all: Allows GPU pass-through (not on Mac).
  • -v: Mounts a volume from host to container.
  • -p: Maps container port to host port.
  • --name: Sets a container name.
  • Image updates: Use docker pull to get the latest image.
• Container vs. Image:
  • Image: Blueprint on Docker Hub (e.g., ol/olOllama).
  • Container: Running instance of an image.
• Using Ollama:
  • Run Ollama client inside the container with docker exec.
  • Create aliases for convenience.
  • Add aliases to shell RC files for persistence.
• Accessing Ollama Remotely:
  • On the same network: Expose container with ollama host=0.0.0.0.
  • On different networks: Use solutions like TailScale for secure access.
• Logs and Cleanup:
  • Use docker logs to view container logs.
  • Use docker stop and docker rm to stop and remove containers.
  • Use docker rmi to remove images.
• Final Notes:
  • Native install is preferred, but Docker is an option.
  • Questions and video suggestions are welcomed in the comments.