Unlock Intelligent Insights with Real-Time RAG Workflows
detail.loadingPreview
Automate knowledge retrieval and question answering from your dynamic data sources. This workflow leverages RAG (Retrieval-Augmented Generation) to provide context-aware answers powered by your living data.
About This Workflow
This n8n workflow empowers you to build sophisticated Retrieval-Augmented Generation (RAG) systems that continuously learn from your live data. It seamlessly integrates with OpenAI for embedding and language models, while utilizing Notion and Supabase for data storage and retrieval. The workflow can be triggered by chat messages or scheduled updates, ensuring your AI always has access to the most current information. It intelligently chunks and embeds data, stores it in a vector database, and then uses this enriched context to answer user queries with remarkable accuracy. This is ideal for building dynamic knowledge bases, intelligent chatbots, and automated content analysis tools.
Key Features
- Real-time Data Integration: Connects to Notion for live content updates.
- Intelligent Data Processing: Utilizes LangChain for text splitting and embedding.
- Vector Database Storage: Leverages Supabase for efficient vector storage and retrieval.
- Context-Aware Q&A: Employs LangChain's QA chain for accurate, contextually relevant answers.
- Flexible Triggering: Supports both chat message triggers and scheduled updates.
How To Use
- Configure Triggers: Set up either the
Chat TriggerorSchedule Triggerto initiate the workflow. For cloud users, consider theNotion Trigger Node. - Input Reference: Ensure your input data (e.g., Notion page ID and name) is correctly passed to the
Input Referencenode. - Data Fetching & Deletion: Use the
Notionnode (Get page blocks) to fetch your live content. TheSupabasenode (Delete old embeddings if exist) is crucial for removing outdated data. - Data Loading & Embedding: The
Default Data Loadernode prepares your data, and theEmbeddings OpenAInode generates vector embeddings. - Text Splitting: Configure the
Token Splitterto define how your text is chunked for efficient processing (adjustchunkSizeand consider overlap). - Vector Store Retrieval & Q&A: Connect the
Vector Store RetrieverandOpenAI Chat Modelto theQuestion and Answer Chainto enable intelligent querying. - Credentials Setup: Ensure all credentials (OpenAI, Notion, Supabase) are correctly configured in n8n.
Apps Used
Workflow JSON
{
"id": "d0707e47-68c0-40e2-82b6-c1f5adf06aef",
"name": "Unlock Intelligent Insights with Real-Time RAG Workflows",
"nodes": 19,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: d0707e47-68c0...
About the Author
Free n8n Workflows Official
System Admin
The official repository for verified enterprise-grade workflows.
Statistics
Related Workflows
Discover more workflows you might like
Automated PR Merged QA Notifications
Streamline your QA process with this automated workflow that notifies your team upon successful Pull Request merges. Leverage AI and vector stores to enrich notifications and ensure seamless integration into your development pipeline.
Visualize Your n8n Workflows: Interactive Dashboard with Mermaid.js
Gain unparalleled visibility into your n8n automation landscape. This workflow transforms your n8n instance into a dynamic, interactive dashboard, leveraging Mermaid.js to visualize all your workflows in one accessible place.
Effortless Bug Reporting: Slack Slash Command to Linear Issue
Streamline your bug reporting process by instantly creating Linear issues directly from Slack using a simple slash command. This workflow enhances team collaboration by providing immediate feedback and a structured approach to logging defects, saving valuable time for development and QA teams.