This workflow implements a complete Voice AI Chatbot system for Wordress that integrates speech recognition, guardrails for safety, retrieval-augmented generation (RAG), Qdrant vector search, and audio responses. It is designed to be connected to a WordPress Voicebot AI plugin through a webhook endpoint.

---

Key Advantages

• ✅ Complete Voice AI Pipeline** The workflow handles:

  • audio input
  • STT
  • intelligent processing
  • TTS output All within a single automated process.

• ✅ Safe and Policy-Compliant Thanks to the Guardrails module, the system automatically:

  • detects harmful or disallowed requests
  • blocks them
  • responds safely This protects both the user and the business.

• ✅ Contextual and Memory-Based Conversations The Window Buffer Memory tied to unique session IDs enables:

  • continuous conversation flow
  • natural dialogue
  • better understanding of context

• ✅ Company-Specific Knowledge via RAG By integrating Qdrant as a vector store, the system can:

  • retrieve business documentation
  • give accurate and up-to-date answers
  • support personalized content This makes the chatbot far more powerful than a standard LLM.

• ✅ Modular and Extensible Architecture Because everything is modular inside n8n, you can:

  • swap OpenAI with other models
  • add new tools or knowledge sources
  • change prompts or capabilities without redesigning the entire workflow.

• ✅ **Easy WordPress Integration The workflow connects directly to a WordPress Voicebot plugin, meaning:

  • no custom backend development
  • simple deployment
  • fast integration for websites

• ✅ Automatic Indexing of Documents The second workflow section:

  • fetches Google Drive files
  • converts them into embeddings
  • indexes them into Qdrant This lets you maintain your knowledge base with almost no manual work.

---

How It Works

This workflow creates a Wordpress voice-enabled AI chatbot that processes audio inputs and provides contextual responses using RAG (Retrieval-Augmented Generation) from a Qdrant vector database. The system operates as follows:

1. Audio Processing Pipeline:

   • Receives audio input via webhook and converts speech to text using OpenAI's STT (Speech-to-Text)
   • Applies guardrails to detect inappropriate content or jailbreak attempts using a separate GPT-4.1-mini model
   • Routes safe queries to the AI agent and blocks unsafe content with a default response

2. AI Agent with Contextual Memory:

   • Uses OpenAI Chat Model with window buffer memory to maintain conversation context
   • Equips the agent with two tools: Calculator for computations and RAG tool for business knowledge retrieval
   • The RAG system queries Qdrant vector store containing company documents using OpenAI embeddings

3. Response Generation:

   • Generates appropriate text responses based on query type and available knowledge
   • Converts approved responses to audio using OpenAI's TTS (Text-to-Speech) with "onyx" voice
   • Returns binary audio responses to the webhook caller

---

Set Up Steps

1. Vector Database Preparation:

   • Create Qdrant collection via HTTP request with specified vector configuration
   • Clear existing collection data before adding new documents
   • Set up Google Drive integration to source documents from specific folders

2. Document Processing Pipeline:

   • Search and retrieve files from Google Drive folder "Test Negozio"
   • Process documents through recursive text splitting (500 chunk size, 50 overlap)
   • Generate embeddings using OpenAI and store in Qdrant vector store
   • Implement batch processing with 5-second delays between operations

3. System Configuration:

   • Configure webhook endpoint for receiving audio inputs
   • Set up multiple OpenAI accounts for different functions (STT, TTS, guardrails, main agent)
   • Establish Qdrant API connections for vector storage and retrieval
   • Implement session-based memory management using session IDs from webhook headers

4. WordPress Integration:

   • Install the provided Voicebot AI Agent WordPress plugin
   • Configure the plugin with the webhook URL to connect to this n8n workflow
   • The system is now ready to receive audio queries and respond with voice answers

The workflow handles both real-time voice queries and background document processing, creating a comprehensive voice assistant solution with business-specific knowledge retrieval capabilities.

---

Need help customizing?

Contact me for consulting and support or add me on Linkedin.