Building an AI Chatbot trained on custom content with LangChain, Faiss and Next.js
Blog post from Upstash
The project outlines the development of a custom content AI chatbot using Upstash, Next.js, LangChain, and Fly.io, focusing on implementing features such as model training scheduling, rate limiting, and caching of OpenAI responses. Upstash is employed for scheduling training via QStash, enforcing rate limits with Redis, and caching responses, which enhances the scalability and efficiency of the chatbot interactions. The setup involves creating and configuring a Redis database and QStash keys, cloning the project repository, and adjusting environment variables to integrate these components seamlessly. The chatbot processes involve setting up API routes in Next.js to handle chat requests with CORS enabled, scheduling content training, and implementing rate limiting to manage user queries effectively. The deployment is facilitated through Fly.io, with the repository being pre-configured for easy deployment, showcasing how these technologies work together to create a scalable and efficient AI chatbot solution.