LLMs.txt

Enhance your visual programming experience with AI tools that understand Rete.js node editor patterns, dataflow concepts, and plugin architecture.

What is LLMs.txt?

Building node editors and visual programming interfaces involves unique patterns and concepts that differ from traditional application development. Our AI integration through LLMs.txt helps coding assistants understand:

• Node-based architecture and connection patterns
• Dataflow vs Control flow processing paradigms
• Plugin composition for extensible editors
• Multi-framework rendering (React, Vue, Angular, Svelte)
• Graph processing and manipulation techniques

This enables AI tools to provide contextually accurate suggestions for your visual programming projects.

Resources

Our documentation is optimized for AI consumption through specialized endpoints that understand visual programming workflows:

• llms.txt - Essential node editor concepts, core APIs, and quick reference patterns
• llms-full.txt - Complete visual programming knowledge base including advanced patterns, plugin architecture, and processing engines

These endpoints are continuously updated to reflect the latest in node editor development practices and framework capabilities.

How to Use

You can integrate Rete.js documentation with any AI coding assistant by providing the LLMs.txt URLs as context. This gives the AI comprehensive knowledge about node editor development patterns and best practices.

Basic integration steps

1. Copy the LLMs.txt URL: https://retejs.org/llms.txt (or llms-full.txt for complete docs)
2. Reference it in your AI tool's context or conversation
3. Ask questions about Rete.js development, node editor patterns, or get code suggestions

VS Code GitHub Copilot

Add the LLMs.txt URL to your workspace for enhanced context-aware suggestions:

1. Create a .copilot-instructions.md file in your project root
2. Add the reference:

   markdown
   # Copilot Instructions
   
   For Rete.js development, reference the documentation at:
   https://retejs.org/llms-full.txt
   
   Focus on node editor patterns, dataflow programming, and plugin architecture.
   

3. Copilot will now understand Rete.js concepts when providing code completions and suggestions

Google Gemini Chat

Reference the documentation directly in your conversation:

text
I'm building a node editor with Rete.js. Please review the documentation at https://retejs.org/llms-full.txt and help me create a custom node that processes image data through multiple transformation steps.

Model Context Protocol (MCP)

MCP-compatible tools like Context7 automatically discover and fetch the Rete.js documentation as context to AI models:

1. The complete Rete.js documentation is automatically loaded as context for AI conversations
2. AI models have persistent access to node editor patterns, plugin architecture, and best practices
3. No manual setup required - the context is always available

This approach ensures every AI interaction has comprehensive Rete.js knowledge without any configuration.