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Conclusion

Congratulations on completing this in-depth tutorial!

You’ve successfully designed, built, and served a RAG LangChain chatbot that answers questions about a fake hospital system. There are certainly many ways you can improve the chatbot you built in this tutorial, but you now have a sound understanding of how to integrate LangChain with your own data, giving you the creative freedom to build all kinds of custom chatbots.

In this tutorial, you’ve learned how to:

  • Use LangChain to build personalized chatbots.
  • Create a chatbot for a fake hospital system by aligning with business requirements and leveraging available data.
  • Consider the implementation of graph databases in your chatbot design.
  • Set up a Neo4j AuraDB instance for your project.
  • Develop a RAG chatbot capable of fetching both structured and unstructured data from Neo4j.
  • Deploy your chatbot using FastAPI and Streamlit.