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RAG & Knowledge Bases

Basic RAG Chat with Cohere Embeddings and Groq

When you run it or a chat message arrives, this splits and embeds documents with Cohere and answers questions with a Groq model.

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What it does

### Chat with database Embed the incoming chat message and use it retrieve relevant chunks from the vector store. These are passed to the model to formulate an answer

The steps

  1. Recursive Character Text Splitter
  2. Default Data Loader
  3. Question and Answer Chain
  4. Vector Store Retriever
  5. When clicking 'Test Workflow' button
  6. When clicking 'Chat' button below
  7. Read/Write Files from Disk
  8. In-Memory Vector Store1
  9. In-Memory Vector Store
  10. Embeddings Cohere
  11. Groq Chat Model
  12. Embeddings Cohere1

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