Advanced Prompt Engineering Principles
AI Nuggets
Detailed Instructions, CLI Commands, Website URLs, and Tips from Video Transcript
Introduction to Prompt Engineering
- Importance of creating better prompts:
- Achieve better results
- Reduce costs
- Increase accuracy in software and automations
Resources for Prompt Engineering
- Resource provided by the Tropic team (creators of CLA)
- Examples, resources, and guides for prompt engineering
- Documentation can be found at the Tropic team’s docs (URL not provided in the transcript)
Prompt Engineering Topics Covered
- Using multimodels like Vision models
- Writing better prompts
- Best practices
Prompt Engineering Principles
- Understanding that different LMs may require different prompts
- A prompt is the text given to an LM to elicit a relevant output
- Importance of the context window in LMs
Prompt Development Lifecycle
- Develop test cases
- Engineer a preliminary prompt
- Test prompts against cases
- Refine prompts
- Share or launch polished prompts
Techniques and Guidelines for Better Prompts
- Be clear and direct
- Provide clear instructions and context
- Include examples
- Assign roles to guide the LM’s response
- Use XML tags
- Chain prompts for complex tasks
- Let the LM “think” step by step
- Prefill responses to guide output
- Control output format
- Request rewrites if necessary
- Test different orders of prompts and focus on aspects of the text
Anthropics’ Resources
- Google spreadsheet for practicing prompt engineering (requires connecting your CLA API)
- Prompt Library with structured and detailed prompts (URL provided in the video description)
Best Practices for Using Vision with CLA
- Apply traditional techniques to multimodel prompts
- Use images as input and ask text questions about them
- Embed questions in images
- Highlight specific parts of images
- Add examples to prompts for accuracy with visual tasks
- Use multiple images as input
- Transcribe documents, handwritten text, and forms
- Assist with complicated document QA
- Convert unstructured information into JSON format
Working with Charts, Graphs, and Slide Decks
- Use Vision capabilities to pass charts and graphs
- Convert PDF pages to images for slide decks
Combining CLA with Stable Diffusion API
- Generate images based on prompts
- Use system prompts to guide image generation
Building Evaluations
- Importance of offline evaluation for continuous improvement
- Components of an evaluation: input prompt, model output, golden answer, and score
- Types of grading: code-based, human, and model-based
Moderation Filters
- Create filters to allow or disallow certain outputs
- Define categories for filtering
Meta Prompt
- A long, multi-shot prompt with examples of good prompts for various tasks
- Helps write a good prompt for your task
- Can be found in a Google Colab provided by Anthropics
Additional Tips
- Use the LM to assist in writing better prompts
- Save detailed prompts for future use
Video Description URL
- Video description with additional info on URLs: https://youtu.be/ctXB9q2hLWY?si=f7S5SsETUkwnZ-VR