The Official LangChain.js Course

Put yourself on the bleeding edge of AI by harnessing the power of LangChain Expression Language to build a chatbot that has deep knowledge of a provided document.

• Splitting with a LangChain textSplitter tool
• Vectorising text chunks
• Using embeddings models
• Supabase vector store
• Templates with input_variables
• Prompts from templates
• LangChain Expression Language
• Basic chains with the .Pipe() method
• Retrieval from a vector store
• Complex chains with RunnableSequence()
• The StringOutputParser() class
• Troubleshooting performance issues

• The Official LangChain.js Course
• 1. What you'll learn and build
• 2. Introduction to LangChain from Jacob Lee (Lead Maintainer of LangChain.js)
• 3. App Flow Diagrams
• 4. What are embeddings?
• 5. Supabase Setup
• 6. Split the text
• 7. Split the text II
• 8. Upload to supabase
• 9. Starter code
• 10. Explainer: The Standalone Question
• 11. Aside: Prompt Templates
• 12. Aside: Prompt Templates II
• 13. Adding the first chain
• 14. Retrieval
• 15. Add StringOutputParser
• 16. Fetching the answer: the template
• 17. Serialize the docs
• 18. Aside: RunnableSequence
• 19. Aside: RunnableSequence 2
• 20. Aside: RunnableSequence 3: RunnablePassthrough
• 21. Super Challenge - add the RunnableSequence
• 22. Super Challenge - solution
• 23. Wire up the UI
• 24. Setting up the memory
• 25. Super Challenge: Wire up the memory
• 26. Performance Issues Check-list
• 27. LangChain Outro