Build Your Own Voice RAG Chatbot with AI
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Empower your business with an intelligent voice-activated chatbot that leverages Retrieval Augmented Generation (RAG) to access and answer questions from your internal knowledge base. This workflow integrates OpenAI for AI processing and ElevenLabs for realistic voice interaction.
About This Workflow
This n8n workflow enables you to construct a sophisticated Voice RAG (Retrieval Augmented Generation) chatbot. It seamlessly connects with ElevenLabs to convert spoken queries into text, processes them using OpenAI's powerful AI models, and retrieves relevant information from your custom knowledge base stored in Qdrant. The AI agent then synthesizes this information to provide accurate and context-aware responses, which are finally converted back into speech by ElevenLabs. This workflow is ideal for creating intelligent voice assistants for customer support, internal knowledge bases, or any application requiring interactive, data-driven voice responses.
Key Features
- Voice Input & Output: Interact naturally with your chatbot using voice, powered by ElevenLabs.
- Intelligent RAG System: Enhances LLM responses by grounding them in your specific data via Qdrant vector storage.
- Customizable Knowledge Base: Easily integrate your company's documentation or FAQs into the chatbot's knowledge pool.
- AI-Powered Agent: Utilizes OpenAI's advanced language models for natural language understanding and response generation.
- Automated Workflow: Orchestrates data retrieval, processing, and voice synthesis with minimal manual intervention.
How To Use
- ElevenLabs Agent Setup: Create an agent on ElevenLabs, define a 'First message', and configure the 'System Prompt' to direct queries to your n8n webhook. Add a webhook tool with a description and point it to your n8n webhook URL, enabling 'Body Parameters' with a 'question' field.
- n8n Workflow Configuration: Set up your Qdrant Vector Store and OpenAI Embeddings credentials within n8n.
- Data Ingestion: Use the Google Drive nodes to fetch your documentation, process it with the Default Data Loader, and store it in your Qdrant collection.
- RAG System Integration: Connect the AI Agent node to your Qdrant Vector Store and OpenAI Embeddings. Configure the 'Vector Store Tool' to query your 'company' data.
- Workflow Triggering: When a user interacts with your ElevenLabs agent, the webhook will be activated, sending the question to n8n. The workflow will then execute the RAG process, and the response will be sent back to ElevenLabs for voice output.
Apps Used
Workflow JSON
{
"id": "c9f7070d-ebc9-4343-a477-e582f3edfbbc",
"name": "Build Your Own Voice RAG Chatbot with AI",
"nodes": 5,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: c9f7070d-ebc9...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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