A comprehensive collection of official system prompts and AI models from leading AI development platforms.

This repository contains detailed insights into the system prompts and internal tools used by various AI platforms, providing over 5,500+ lines of code and documentation. This collection serves as a valuable resource for developers, researchers, and AI enthusiasts interested in understanding the inner workings of these platforms.

1. Clone the repository:

   git clone https://github.com/yourusername/ai-system-prompts.git
   cd ai-system-prompts

2. Explore the collections:

   • Navigate through different platform folders
   • Review the documentation in each section
   • Check out example implementations

• Comprehensive Collection: Access to multiple AI platform implementations
• Detailed Documentation: In-depth explanations of system architectures
• Code Examples: Practical implementations and usage patterns
• Regular Updates: New platforms and features added periodically
• Community Driven: Contributions from AI enthusiasts worldwide
• Advanced AI Tools: Integration with popular AI frameworks and libraries
• Custom Models: Pre-trained models for specific use cases
• API Integrations: Ready-to-use API wrappers for various AI services

• GPT-4 Integration: Implementation examples and best practices
• Claude Integration: System prompts and usage patterns
• LLaMA Integration: Custom implementations and optimizations

• DALL-E Integration: Image generation and manipulation
• Stable Diffusion: Custom model implementations
• Vision Models: Object detection and recognition

• BERT Implementations: Custom fine-tuning examples
• Transformer Models: Architecture and implementation details
• Text Classification: Pre-trained models and examples

• Whisper Integration: Speech-to-text implementations
• Audio Generation: Text-to-speech models and examples

• OpenAI API: Complete integration examples
• Hugging Face: Model deployment and usage
• TensorFlow: Custom model implementations
• PyTorch: Advanced model architectures
• LangChain: Chain of thought implementations
• AutoGPT: Autonomous agent examples

Each platform folder contains:

• System prompt analysis
• Implementation details
• Best practices
• Usage examples
• Architecture diagrams
• Performance considerations
• API documentation
• Integration guides
• Troubleshooting guides
• Performance benchmarks

• v0/ - System prompts and tools from v0
• Manus/ - Manus platform implementation details
• Same.dev/ - Same.dev platform components
• Lovable/ - Lovable AI system architecture
• Cursor/ - Cursor IDE AI integration
  • cursor_ask.txt (coming soon)
  • cursor_edit.txt (coming soon)
• Tools/ - Additional AI tools and implementations
  • language_models/ - Language model implementations
  • vision_models/ - Computer vision implementations
  • audio_models/ - Audio processing implementations
  • nlp_models/ - NLP model implementations
  • awesome_dev_tools.md - Comprehensive list of free developer tools
  • awesome_ai_tools.md - Comprehensive list of free AI tools for developers

• Study and understand AI system architectures
• Learn from production-grade AI implementations
• Research AI prompt engineering techniques
• Compare different AI platform approaches
• Build custom AI solutions
• Integrate AI into existing applications
• Develop autonomous AI agents
• Create AI-powered applications

• Awesome Free Developer Tools - A curated list of free tools that every developer should use to improve productivity, code quality, and development workflow.
• Awesome Free AI Tools - A comprehensive collection of free AI tools, frameworks, libraries, and resources for developers working with artificial intelligence.

We welcome contributions! If you have suggestions for improvements or want to add new content:

1. Fork the repository
2. Create a new branch
3. Submit a pull request
4. Open an issue for discussions

Q: How can I use these system prompts in my project?
A: Review the documentation in each platform folder for specific implementation guidelines and best practices.

Q: Are there any usage restrictions?
A: This repository is for educational and research purposes. Please respect the intellectual property rights of the original platforms.

Q: How often is the repository updated?
A: We aim to update the repository monthly with new platforms and improvements.

Q: Can I contribute my own AI tools?
A: Yes! We welcome contributions of new AI tools and implementations. Please follow our contribution guidelines.

• Twitter: Kishan Patel
• LinkedIn: Kishan Patel
• GitHub: Kishan Patel

If you find this repository useful, please consider:

• Starring the repository
• Sharing it with your network
• Contributing to its growth
• Following for updates

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

Note: This repository is for educational and research purposes only. Please respect the intellectual property rights of the original platforms.