In this course, you'll be using LangChain.js to build a chatbot that can answer questions on a specific text you give it. This is one of the holy grails of AI - a true superpower.
In the first part of the project, we learn about using LangChain to split text into chunks, convert the chunks to vectors using an OpenAI embeddings model, and store them together in a Supabase vector store.
Next, we study chains, which are the building blocks of LangChain. And we do this using LangChain Expression Language. This makes the process of coding in LangChain much smoother and easier to grasp.
Finally, we tackle retrieval: using vector matching to select the text chunks from our vector store which are most likely to hold the answer to a user’s query. This enables the chatbot to answer questions specific to your data - a critical skill when working with AI and one of the most common use-cases for AI in web dev.
By the end of this course, you'll be able to use LangChain to build real-world, scalable applications. And as this is a Scrimba course, there will be challenges for you to solve throughout the course, allowing you to put your new skills to the test and gain the muscle memory you need to become a rock star developer.
