Block 1 - OpenAI Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
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 a...
@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.toolcalculator, @n8n/n8n-nodes-langchain.vectorstoreqdrant, @n8n/n8n-nodes-langchain.embeddingsopenai, n8n-nodes-base.respondtowebhook, n8n-nodes-base.webhook, n8n-nodes-base.stickynote
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Davide.
Original n8n.io sourceThis 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.
✅ Complete Voice AI Pipeline** The workflow handles:
✅ Safe and Policy-Compliant Thanks to the Guardrails module, the system automatically:
✅ Contextual and Memory-Based Conversations The Window Buffer Memory tied to unique session IDs enables:
✅ Company-Specific Knowledge via RAG By integrating Qdrant as a vector store, the system can:
✅ Modular and Extensible Architecture Because everything is modular inside n8n, you can:
✅ **Easy WordPress Integration The workflow connects directly to a WordPress Voicebot plugin, meaning:
✅ Automatic Indexing of Documents The second workflow section:
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:
Audio Processing Pipeline:
AI Agent with Contextual Memory:
Response Generation:
Vector Database Preparation:
Document Processing Pipeline:
System Configuration:
WordPress Integration:
The workflow handles both real-time voice queries and background document processing, creating a comprehensive voice assistant solution with business-specific knowledge retrieval capabilities.
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This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 34 workflow blocks. Download the JSON for the full node graph.
| Workflow | Voice AI chatbot with OpenAI, RAG (Qdrant) & Guardrails for WordPress |
|---|---|
| Complexity | advanced |
| Nodes | 34 |
| Categories | Support Chatbot, AI Chatbot |
| Author | Davide |
| Published | 17 Nov 2025 |
Use the JSON export at /data/workflows/10924/10924.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
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 a...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI Chatbot use case.