Secrets to Self-Hosting Ollama on a Remote Server

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AI Summary

Self-Hosting O Lama on a Virtual Machine

• Introduction
  • Tutorial on self-hosting O Lama without third-party reliance.
  • Process includes setting up a Linux VM on Google Cloud and installing O Lama.
• Creating a Linux Virtual Machine
  • VM can be on AWS, GCP, or Azure.
  • Steps:
    1. Sign up for Google Cloud.
    2. Navigate to Compute Engine and create a VM.
    3. Choose GPU (e.g., Nvidia T4) and machine specs (e.g., 1 vCPU, 3.75 GB memory).
    4. Increase boot disk size to 100 GB and select Ubuntu 22.04.
    5. Enable HTTP/HTTPS and set up networking with automatic IP and premium network tier.
    6. Create the VM and SSH into it.
• Installing GPU Drivers
  • Follow provided steps to install Nvidia drivers on Ubuntu.
  • Commands include apt-get update, finding Nvidia driver version, and installing Linux modules.
• Installing O Lama
  • Copy Linux command from O Lama website to install on the VM.
  • Download O Lama 3 model.
• Activating Remote Access
  • Enable firewall and allow O Lama remote access.
  • Modify settings as per documentation.
  • Use systemctl to reload and restart services.
• Creating an App Interface
  • Integrate the self-hosted O Lama server with a user interface.
  • Steps:
    1. Install streamlit library.
    2. Create a UI file with Streamlit and Async OpenAI client setup.
    3. Configure the client with the server IP and model settings.
    4. Define UI behavior and message handling functions.
    5. Run the UI with Streamlit and interact with the O Lama model.
• Conclusion
  • Successfully integrated an application with a remote O Lama server.
  • Encouragement to create more applications and maintain privacy by restricting firewalls.
  • Invitation to subscribe for more AI-related content.