Kütüphane / RAG ve Bilgi Bankaları
RAG ve Bilgi Bankaları
Vektör deposuna belge ekleme ve geri getirme
Elle çalıştırdığınızda deneme belgelerini OpenAI gömmeleriyle bir vektör deposuna yükler ve soru yanıtlama için geri getirir.
Ne yapar
# Insert and retrieve documents ## Overview Automated workflow: Insert and retrieve documents. This workflow integrates 16 different services: stickyNote, httpRequest, textSplitterRecursiveCharacterTextSplitter, code, splitOut. It contains 32 nodes and follows best practices for error handling and security. ## Workflow Details - Total Nodes: 32 - Node Types: 16 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - When clicking "Execute Workflow": manualTrigger - Fetch Essay List: httpRequest - Extract essay names: html - Split out into items: splitOut - Fetch essay texts: httpRequest - Limit to first 3: limit - Extract Text Only: html - Sticky Note3: stickyNote - Sticky Note5: stickyNote - Recursive Character Text Splitter1: textSplitterRecursiveCharacterTextSplitter - ... and 22 more nodes ## Usage Instructions 1. Configure Credentials: Set up all required API keys and credentials 2. Update Variables: Replace any placeholder values with actual data 3. Test Workflow: Run in test mode to verify functionality 4. Deploy: Activate the workflow for production use ## Security Notes - All sensitive data has been removed or replaced with placeholders - Error handling is implemented for reliability - Follow security best practices when configuring credentials ## Troubleshooting - Check error logs if workflow fails - Verify all credentials are properly configured - Ensure all required services are accessible
Adımlar
- When clicking "Execute Workflow"
- Fetch Essay List
- Extract essay names
- Split out into items
- Fetch essay texts
- Limit to first 3
- Extract Text Only
- Recursive Character Text Splitter1
- Generate response
- Compose citations
- Answer the query based on chunks
- Prepare chunks
- Set max chunks to send to model
- Embeddings OpenAI2
Toplam 42 adım.