OpenAI citation generation for RAG file retrieval
Workflow Description
An automation workflow that leverages OpenAI to generate accurate citations from retrieved RAG files. The system combines memory and chat triggers to ensure responses are properly attributed to original sources.
How it works
- 1.Capture user query via chat trigger and store in memory buffer
- 2.Retrieve relevant files and documents from RAG repository
- 3.Send retrieved content to OpenAI for response generation with citations
- 4.Process text and citations through data processing nodes
- 5.Return final response with citations attributed to user
Use cases
- Automate document-based Q&A systems with guaranteed accurate citations
- Accelerate repository search processes by generating reliable citations automatically
Requirements
- Valid OpenAI API key for accessing text generation models
- Access to RAG repository or centralized document retrieval system
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (19)
Aggregate
Aggregate
Window Buffer Memory
Memory Buffer Window
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Create a simple Trigger to have the Chat button within N8N
Chat Trigger
OpenAI Assistant with Vector Store
OpenAI
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Get ALL Thread Content
HTTP Request
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Sticky Note
Split all message iterations from a thread
Split Out
Split all content from a single message
Split Out
Split all citations from a single message
Split Out
Retrieve file name from a file ID
HTTP Request
Regularize output
Set
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Sticky Note
Optional Markdown to HTML
Markdown
Finnaly format the output
Code