Fetch and summarize the latest three Paul Graham essays with GPT
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Workflow Description
An automated workflow that loads documents, splits them into text chunks, and uses OpenAI's advanced language models to generate concise summaries efficiently. Ideal for processing large volumes of content while maintaining accuracy and relevance of extracted information.
How it works
- 1.Trigger the workflow via HTTP request and specify the document to process
- 2.Load document data and split it into manageable text segments
- 3.Send segments to OpenAI language model for intelligent summarization
- 4.Merge individual summaries into a cohesive unified summary
Use cases
- Quickly summarize lengthy business reports and documentation
- Automatically process large batches of text files in bulk operations
- Extract key information from contracts and legal documents
Requirements
- Valid OpenAI API key with appropriate access permissions
- Compatible document formats (PDF, plain text, formatted documents)
- Configured text processing parameters tailored to content type
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 (13)
When clicking "Execute Workflow"
Manual Trigger
Fetch essay list
HTTP Request
Extract essay names
HTML Page
Fetch essay texts
HTTP Request
Extract title
HTML Page
Clean up
Set
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Split out into items
Split Out
Limit to first 3
Limit
Default Data Loader
Document Default Data Loader
Recursive Character Text Splitter
Text Splitter Recursive Character Text Splitter
OpenAI Chat Model1
OpenAI
Merge
Merge
Summarization Chain
Chain Summarization
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