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Prompt Engineering Research

A comprehensive research project on prompt engineering and interaction with AI language models.

Introduction

This project explores advanced techniques in prompt engineering, focusing on structured prompts, role-playing, and various formats for effective AI interaction. It aims to help users better understand and utilize AI language models.

Features

  • Structured prompt formats (JSON, YAML, XML, etc.)
  • Role-playing techniques with emotional and scenario-based approaches
  • Advanced thinking frameworks and dimensional analysis
  • Industry-specific applications and case studies
  • Multi-modal interactions (text, image, code)
  • Training methodologies and best practices
  • System prompts for various AI models
  • Agile development integration

Getting Started

Prerequisites

  • Basic understanding of AI language models
  • Familiarity with common markup languages
  • Interest in prompt engineering
  • Basic knowledge of software development (optional)
  • TeXstudio (for compiling LaTeX documents)

Installation

No installation required. This is a research document that can be accessed directly.

For LaTeX document compilation:

  1. Download and install TeXstudio
  2. Open .tex source files
  3. Use TeXstudio's built-in compiler
  4. Export to PDF format

Quick Start Guide

  1. Start with the Introduction chapter
  2. Follow the structured learning path
  3. Practice with provided examples
  4. Explore advanced topics

Documentation Structure

  1. Introduction

    • Background
    • Common Platforms
    • AI Library Resources
    • Writing Origins

  2. Structured Prompt Formats

    • Pseudo Instructions
    • Markdown Format
    • JSON/YAML/XML Formats
    • Natural Language

  3. Role-Playing Techniques

    • Basic Principles
    • Advanced Scenarios
    • Emotional Intelligence
    • Professional Roles

  4. Advanced Frameworks

    • Thinking Dimensions
    • Problem-Solving Methods
    • Creative Approaches
    • Industry Standards

  5. Industry Applications

    • Business Solutions
    • Technical Implementation
    • Case Studies
    • Best Practices

  6. System Prompts

    • ChatGPT
    • Claude
    • Llama2
    • Other Models

  7. Training Guidelines

    • Data Preparation
    • Model Selection
    • Fine-tuning Strategies
    • Evaluation Methods

Development Guidelines

Code Style

  • Follow defensive programming principles
  • Maintain modular design
  • Ensure code readability
  • Include necessary comments

Testing

  • Unit testing for components
  • Integration testing
  • Performance testing
  • User acceptance testing

Contributing

We welcome contributions! Please follow these steps:

  1. Fork the repository
  2. Create your feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

Contribution Guidelines

  • Follow the existing code style
  • Add tests for new features
  • Update documentation
  • Respect the code of conduct

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

Contact

Resources

  • Project Wiki
  • API Documentation
  • Example Collection
  • Community Forum

Acknowledgments

  • Homebrew AI Club
  • All contributors and researchers
  • Open source community
  • AI research institutions

Version History

  • v3.7 (Current) - Added advanced frameworks
  • v3.6 - Enhanced role-playing scenarios
  • v3.5 - Added industry applications
  • v3.0 - Initial release