Building a Chatbot with Next.js, LangChain, OpenAI, and Supabase Vector
Chatbots have become increasingly popular as a way to automate customer service and provide instant assistance to users. With the advancements in natural language processing and artificial intelligence, building a chatbot has become more accessible than ever. In this article, we will explore how to build a chatbot using Next.js, LangChain, OpenAI, and Supabase Vector.
Next.js
Next.js is a popular open-source JavaScript framework that allows you to build static and dynamic web applications. It provides a fast and efficient way to create web experiences, making it an ideal choice for building a chatbot interface.
LangChain
LangChain is a platform that provides language understanding and processing capabilities for chatbot development. It offers pre-trained models and tools to build and deploy multilingual chatbots with ease.
OpenAI
OpenAI is a research organization that aims to ensure artificial general intelligence benefits all of humanity. It offers powerful natural language processing models, such as GPT-3, which can be leveraged to enhance the conversational capabilities of our chatbot.
Supabase Vector
Supabase Vector is a tool that allows you to create and deploy chatbots with minimal effort. It provides a set of pre-built conversational components and integrates seamlessly with Next.js and other technologies to deliver a fully functional chatbot experience.
Building the Chatbot
First, we will create a Next.js application to serve as the foundation for our chatbot interface. We will then integrate LangChain to handle language processing and understanding, and OpenAI to enhance the conversational capabilities of our chatbot. Finally, we will use Supabase Vector to create and deploy our chatbot with ease.
Conclusion
By combining the power of Next.js, LangChain, OpenAI, and Supabase Vector, we can create a robust and feature-rich chatbot that can handle complex conversations and provide valuable assistance to users. The seamless integration of these technologies allows for a streamlined development process, making it easier than ever to build and deploy advanced chatbot experiences.
Why does he need realtime database? The answers are coming from a server on demand, it's not like we have to subscribe and wait for ai to start typing after dinner.
configuring this is a pain..
This project only works locally. Do not attempt to use it in prod as I have seen no evidence of it being deployable
Great video thanks for sharing this.
Please make a video about embedding PDF files, supabase and next js!!
Great job! I've rebuilt it successfully on my local windows machine. Why the chat response takes VERY LONG time( 2+ minutes) ?
this doesn't work when deployed to vercel? The AI doesn't respond and the entry on supabase is just NULL… it still charges my openAI account too so it looks like somethings happening?
can we have a Sveltekit tutorial at some point? 🙂
Wow a video about Nextjs again! Always Nextjs. Supabase can only be used with Nextjs guys. You can't use it with anything else. It looks like so from the videos posted here. Nextjs only.
Is supabase vector different from pgvector?