Build a Production RAG Chatbot with Django + pgvector + OpenAI (Full Guide)

📰 Dev.to · Kirill Strelnikov

Learn to build a production-ready RAG chatbot using Django, pgvector, and OpenAI in this step-by-step guide

intermediate Published 9 Mar 2026
Action Steps
  1. Install Django and required packages using pip
  2. Configure pgvector for vector database management
  3. Set up OpenAI API for LLM integration
  4. Build a RAG chatbot model using OpenAI's API
  5. Deploy the chatbot to a production environment using Django
Who Needs to Know This

AI engineers, software engineers, and product managers can benefit from this guide to build and deploy a RAG chatbot

Key Insight

💡 Combine Django, pgvector, and OpenAI to create a scalable and efficient RAG chatbot

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🤖 Build a production-ready RAG chatbot with Django + pgvector + OpenAI! 🚀

Key Takeaways

Learn to build a production-ready RAG chatbot using Django, pgvector, and OpenAI in this step-by-step guide

Full Article

I'm Kirill Strelnikov, a freelance AI/Django developer in Barcelona. I've built RAG chatbots that...
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