This repository contains a comprehensive collection of n8n workflows implementing Retrieval-Augmented Generation (RAG) for creating AI-powered workflow automation. The repository serves as both a reference implementation and ready-to-deploy solution for n8n workflow generation. Most of these workflows are scraped from the n8n official template, Gumroad, or self-made.
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├── documentation-for-RAG/ # Documentation datasets for RAG systems
│ └── n8n_documentation_index/ # Indexed n8n documentation
├── n8n.io-templates/ # Reference workflow templates
├── n8n-blog-maker/ # Blog generation workflow system
├── Real Case Example (Credit to @imgroup)/ # Production-ready workflow implementations
├── Categorized/ # Categorized workflow examples from various source
├── *.json # Individual workflow files
└── *.pdf, *.py # Utility files and guides
The repository includes a complete n8n documentation corpus scraped using crawl4ai, providing:
- Node documentation with parameter specifications
- Workflow execution details
- Integration configuration requirements
- Error handling patterns and best practices
The RAG system is implemented with the following components:
- Vector Database Integration: Compatible with Qdrant, Pinecone, and Supabase Vector
- Embedding Models: Supports OpenAI, Cohere, and Jina embeddings
- Retrieval Mechanisms: Implements semantic search with customizable relevance thresholds
- Context Assembly: Dynamic prompt construction with retrieved documentation fragments
- Generation: Compatible with various LLM providers (OpenAI, Anthropic, Google, etc.)
- Webhook endpoints for external triggers
- HTTP Request nodes for external service communication
- Database connectors (PostgreSQL, MongoDB, MySQL)
- File storage integrations (S3, Google Drive, Local)
| Category | Count | Description |
|---|---|---|
| Content Generation | 35+ | Automated content creation workflows |
| Customer Interaction | 25+ | CRM and customer service automation |
| Data Processing | 20+ | ETL and data transformation pipelines |
| Media Production | 15+ | Video and image generation workflows |
| Miscellaneous | 5+ | Utility and specialized workflows |
The following credentials are required for full functionality:
- OpenAI API key or equivalent LLM provider
- Vector database API credentials
- Service-specific API keys (YouTube, Twitter, etc. as needed)
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Configure environment variables in your n8n instance:
N8N_ENCRYPTION_KEY=your-encryption-key N8N_VECTOR_DB_URL=your-vector-db-url N8N_LLM_API_KEY=your-llm-api-key -
Set up vector database collections:
N8N_DOC_COLLECTION=n8n_documentation N8N_WORKFLOW_COLLECTION=workflow_examples -
Install additional dependencies if required by specific workflows
Workflows can be executed via:
- Webhook triggers
- Scheduled executions
- Manual activation
- API calls to n8n endpoints
- RAG queries typically complete in 2-5 seconds depending on complexity
- Workflow generation may take 10-30 seconds for complex implementations
- Consider batch processing for high-volume operations
Full basic - No prerequisites
Overall guide - No prerequisites
Webhook guide if you want to self host
Neat tricks
MOST IMPORTANT
- @imgroup: Real-world business implementations
- n8n.io community contributors