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Library / RAG & Knowledge Bases

RAG & Knowledge Bases

Build a Voice RAG Chatbot with ElevenLabs and Qdrant

When a voice agent from ElevenLabs calls the webhook, an OpenAI agent searches Google Drive documents stored in Qdrant and returns spoken answers.

What it does

# STEP 1 ## Create an Agent on ElevenLabs - Create an agent on ElevenLabs (eg. test_n8n) - Add "First message" (eg. Hi, Can I help you?) - Add the "System Prompt" message... eg: 'You are the waiter of "Pizzeria da Michele" in Verona. If you are asked a question, use the tool "test_chatbot_elevenlabs". When you receive the answer from "test_chatbot_elevenlabs" answer the user clearly and precisely.' - In Tools add a Webhook called eg. "test_chatbot_elevenlabs" and add the following description: 'You are the waiter. Answer the questions asked and store them in the question field.' - Add the n8n webhook URL (method POST) - Enable "Body Parameters" and insert in the description "Ask the user the question to ask the place.", then in the "Properties" add a data type string called "question", value type "LLM Prompt" and description "user question"

The steps

  1. AI Agent
  2. Vector Store Tool
  3. Qdrant Vector Store
  4. Embeddings OpenAI
  5. When clicking ‘Test workflow’
  6. Create collection
  7. Refresh collection
  8. Get folder
  9. Download Files
  10. Default Data Loader
  11. Token Splitter
  12. Qdrant Vector Store1
  13. Embeddings OpenAI1
  14. Respond to ElevenLabs

18 steps in total.

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