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RAG & Knowledge Bases

Answer WhatsApp Customers with OpenAI and MongoDB Search

When a WhatsApp message arrives, an OpenAI agent searches a MongoDB Atlas knowledge base built from Google Docs and replies to the customer.

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What it does

Search Index Example { "mappings": { "dynamic": false, "fields": { "_id": { "type": "string" }, "text": { "type": "string" }, "embedding": { "type": "knnVector", "dimensions": 1536, "similarity": "cosine" }, "source": { "type": "string" }, "doc_id": { "type": "string" } } } }

The steps

  1. Knowledge Base Agent
  2. OpenAI Chat Model
  3. Embeddings OpenAI
  4. When clicking "Execute Workflow"
  5. Simple Memory
  6. MongoDB Vector Search
  7. Document Section Loader
  8. Document Chunker
  9. MongoDB Vector Store Inserter
  10. OpenAI Embeddings Generator
  11. Google Docs Importer
  12. WhatsApp Trigger
  13. OpenAI
  14. OpenAI1

32 steps in total.

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