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Running RunPod on Mods

Mods is an AI-powered tool designed for the command line and built to seamlessly integrate with pipelines. It provides a convenient way to interact with language models directly from your terminal.

How Mods Works

Mods operates by reading standard input and prefacing it with a prompt supplied in the Mods arguments. It sends the input text to a language model (LLM) and prints out the generated result. Optionally, you can ask the LLM to format the response as Markdown. This allows you to "question" the output of a command, making it a powerful tool for interactive exploration and analysis. Additionally, Mods can work with standard input or an individually supplied argument prompt.

Getting Started

To start using Mods, follow these step-by-step instructions:

  1. Obtain Your API Key:

    • Visit the RunPod Settings page to retrieve your API key.
    • If you haven't created an account yet, you'll need to sign up before obtaining the key.
  2. Install Mods:

    • Refer to the different installation methods for Mods based on your preferred approach.
  3. Configure RunPod:

    • Update the config_template.yml file to use your RunPod configuration. Here's an example:

      api-key-env: RUNPOD_API_KEY
      # Add your model name
      aliases: ["openchat"]
      max-input-chars: 8192

    • base-url: Update your base-url with your specific endpoint.

    • api-key-env: Add your RunPod API key.

    • openchat/openchat-3.5-1210: Replace with the name of the model you want to use.

    • aliases: ["openchat"]: Replace with your preferred model alias.

    • max-input-chars: Update the maximum input characters allowed for your model.

  4. Verify Your Setup:

    • To ensure everything is set up correctly, pipe any command line output and pass it to mods.

    • Specify the RunPod API and model you want to use.

      ls ~/Downloads | mods --api runpod --model openchat -f "tell my fortune based on these files" | glow

    • This command will list the files in your ~/Downloads directory, pass them to Mods using the RunPod API and the specified model, and format the response as a fortune based on the files. The output will then be piped to glow for a visually appealing display.