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
- AI Agent
- Vector Store Tool
- Qdrant Vector Store
- Embeddings OpenAI
- When clicking ‘Test workflow’
- Create collection
- Refresh collection
- Get folder
- Download Files
- Default Data Loader
- Token Splitter
- Qdrant Vector Store1
- Embeddings OpenAI1
- Respond to ElevenLabs
18 steps in total.
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