Next Level Prompts? - 10 mins into advanced prompting

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AI Summary

Summary: Advanced Prompt Engineering Techniques

• Challenges of Prompt Engineering:
  • Difficult to achieve consistent, scalable results.
  • Aim to control prompts for specific output structures.
• Guidance Framework:
  • Open-source, introduced by Microsoft.
  • Over 12,000 GitHub stars.
  • Programs prompts for specific outputs.
  • Features loops, conditional statements, and candidate answers.
  • Visual Studio Code and Jupyter Notebooks are used for setup.
  • Compatible with various AI models (GPT-3.5, GPT-4, LLaMA).
  • Allows for structured outputs and restricted answer sets.
• Advanced Logic with Guidance:
  • If conditions can trigger different responses based on input.
  • Hidden logic blocks for internal processing.
  • Can be used for customer service, email responses, and prioritizing tasks.
• Real-Time Data Visualization:
  • Guidance can integrate with QuickChart for chart generation.
  • Custom functions within prompts can create data visualizations.
• Image Generation:
  • Guidance can work with Pollinations API for on-the-fly AI image creation.
  • Enables story and illustration generation from a single prompt.
• Community Resources:
  • Flow GPT: A large prompt library and community.
  • GPT Prompt Engineer: Uses GPT to generate and evaluate prompts.
  • Prompts Royal: A frontend for evaluating prompt performance.
• Conclusion:
  • Guidance is powerful but requires fine-tuning.
  • Community projects can accelerate the prompt engineering process.
  • The author shares example codes and encourages community input.

Additional Notes:

• The author emphasizes the iterative nature of prompt engineering.
• They suggest using community tools as starting points and for prompt evaluation.
• The video description contains example codes for experimentation.