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Grok Mixture of Agents Setup Guide

Jul 28, 2024

Mixture of Agents in Grok

Overview

  • Grok released Mixture of Agents natively, enabling models previously deemed less capable to operate at near GPT-4.0 levels.
  • A video detailing the functionality of Mixture of Agents is available, with a link provided in the description.

Setup Requirements

  • Necessary Tools:
    • VS Code
    • Grok API Key

Getting Start with VS Code

  1. Launch VS Code.
  2. Navigate to Project Directory:
    • Use cd to access the directory where the project will be stored (e.g., desktop).
  3. Clone the Repository:
    • Use git clone and the provided GitHub URL.
    • Open the project folder by clicking the Explorer button and selecting the newly downloaded folder.
  4. Open Terminal:
    • Create a new conda environment: conda create -n grok-moa python=3.11
    • Confirm with enter and activate it with the displayed command.

Installing Dependencies

  • Install all dependencies using: pip install -r requirements.txt
  • A Docker file is available for alternative setup.

Environment Variables

  1. Create a new file in the project directory named .env.
  2. Add your Grok API key:

grok_API_key=YOUR_GROK_API_KEY

3. If you don't have a Grok account, sign up at console.grok.com, create an API key, and replace `YOUR_GROK_API_KEY` with the generated key. ## Running the Application - To run the application, input: ```bash streamlit run app.py
  • This will open a local interface in the browser.

Interface Overview

  • Main Controls:
    • Select the main model (e.g., Lama 370B), modify the number of layers (e.g., default set to 3), and adjust the temperature settings.
    • Experiment with different agent configurations for each layer (Agent One, Agent Two, Agent Three).

Demo Experiment

  • Conduct a test by asking the application to generate output:
    • Example prompt: "Write 10 sentences that end with the word apple."
  • Agent Outputs:
    • Review layer-wise outputs and assess performance.
    • Observe agent responses in detail (e.g., layer one agent responses and evaluations).

Final Thoughts

  • Positive feedback on the speed and effectiveness of Mixture of Agents.
  • Encouragement for further integration of these features in Grok’s main interface and among inference companies.
  • Highlights of the additional features in the interface:
    • Deploy options via Streamlit.
    • Ability to rerun processes and manage settings.
    • Options for screencasting and cache management.

Resources

  • Links to all mentioned resources and the setup guide will be provided in the description.

Call to Action

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