LLM In-Context Learning Masterclass feat My (r/reddit) AI Agent

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AI Summary

Summary: Building a Reddit AI Agent’s Brain

• Objective: To create an AI agent that can respond to specific topics on Reddit with knowledge and rules provided.

• Process:

  • Selected topics for the AI to have knowledge about (e.g., CLA 3, AI agent, MROL 7B).
  • Created “brain content” including:
    • Knowledge base.
    • Rules for the agent to follow.
    • Example comment-response pairs.
    • Bad examples to avoid.
  • Integrated this content into the AI’s prompt, resulting in large prompts handled by a capable model.

• Example Content:

  • Detailed information on AI models (e.g., CL Opus, Google Gemini 1.5 Pro).
  • Information on Nvidia hardware and AI-related topics.
  • Example comments that the AI should emulate.
  • Rules for subtle promotion of a YouTube channel.

• Agent Functionality:

  • Searches for Reddit posts based on selected keywords.
  • If a post contains a URL or image, it scrapes or analyzes them for content.
  • Combines the fetched data with the AI brain to construct comments.

• Code and Testing:

  • Keywords and subreddits are predefined for targeting specific discussions.
  • The prompt includes a large context to guide the AI’s responses.
  • Random wait times are implemented between comments to avoid spamming.
  • The system tracks which posts have been replied to avoid duplicate comments.
  • The code is available for members on a community GitHub.

• Results:

  • Demonstrated successful comments on Reddit with user engagement.
  • The AI agent can subtly promote the YouTube channel within its comments.

• Conclusion:

  • The project was educational in data handling and structuring.
  • It serves as a good beginner’s project for those interested in data collection and AI interaction.
  • Encourages community engagement through likes and comments on the YouTube channel.