Build a WordPress RAG chatbot with OpenAI, Qdrant or MongoDB Atlas

Description

Quick overview
Build a WordPress chatbot that answers questions from your site content using Retrieval-Augmented Generation. n8n handles indexing and chat orchestration, while Qdrant or MongoDB Atlas provides vector search and OpenAI generates context-grounded responses.

How it works
Content indexing — WordPress content is retrieved, cleaned, chunked, embedded, and stored in the selected vector database.
Intent routing — Incoming questions are classified so conversational requests, content searches, and optional profile/skills queries can follow different paths.
Semantic retrieval — Relevant chunks are retrieved by meaning rather than exact keyword matching.
Reranking — Cohere can rerank retrieved documents before response generation to improve relevance.
Response generation — OpenAI generates an answer using the retrieved context and configured assistant behavior.
WordPress delivery — The supplied WordPress integration exposes the chatbot through a responsive frontend and shortcode.
Security and logging — The architecture includes webhook authentication, input handling, server-side secrets, and privacy-oriented logging controls.

Setup
Purchase the complete package — Obtain the workflows, WordPress plugin, test frontend, supporting scripts, and complete documentation.
Choose a vector backend — Configure either the Qdrant path or the MongoDB Atlas path according to the included deployment guide.
Configure AI credentials — Connect OpenAI and any optional reranking services used by your selected setup.
Import and configure workflows — Configure the indexing workflow first, then the real-time chatbot workflow and their required credentials.
Index WordPress content — Run the indexing process and verify that embeddings and document metadata are available in the vector store.
Deploy the frontend — Install/configure the WordPress integration, set the webhook and authentication values, and place the chatbot shortcode where required.
Test retrieval and security — Validate normal conversation, RAG queries, unavailable answers, authentication, and frontend behavior before production deployment.
Cohere API credentials for reranking (optional)
MongoDB-based profile/skills knowledge path (optional)
Standalone test micro-website (optional)
Additional content sources or vector collections (optional)

Requirements
WordPress site with REST API access
n8n instance
OpenAI API credentials
Qdrant or MongoDB Atlas vector database
HTTPS for production deployments
Ability to install/configure the supplied WordPress integration

Customization
Knowledge sources — Extend indexing beyond WordPress posts or add separate collections for specialized data.
Retrieval — Adjust chunking, top-K retrieval, metadata filters, vector backend, and reranking behavior.
Assistant behavior — Modify intent classification, prompts, response style, language handling, and fallback behavior.
Frontend — Customize WordPress styling, labels, placement, responsive behavior, and shortcode integration.
Security — Adapt authentication, request validation, rate limiting, logging, and privacy controls to your deployment.
Models and providers — Change supported LLM, embedding, or reranking components where the workflow architecture allows it.

Additional info
The complete purchased package includes two n8n workflows, WordPress integration, test frontend, setup/customization documentation, and supporting tools.
The public repository preserves promotional images and frontend screenshots under assets/; the paid workflow package itself is distributed through the purchase channels.