Build a Perplexity-Inspired Answer Engine Using Groq, Mixtral, Langchain, Brave & OpenAI in 10 Min

Video Description

In this video, I walk you through the step-by-step process of creating your own answer engine, much like Perplexity, but utilizing cutting-edge technologies including Groq, Mistral AI's Mixtral 8X7B, LangChain, OpenAI Embeddings & the Brave Search API. This tutorial is designed for those interested in implementing such a system within a JavaScript or Node.js framework. I show you how to configure the engine to deliver not just answers but also sources and potential follow-up questions in response to queries. The journey begins with the initial setup of our project, where I guide you through managing API keys from OpenAI, Groq, and the Brave Search API. From there, we move on to initializing an express server to handle incoming requests effectively. I place a strong emphasis on the importance of speed in our inference processes and share insights on optimizing various components like the embeddings model, how we handle search engine requests, the method of text chunking, and the intricacies of processing queries. As we progress, I demonstrate how to curate response content meticulously, introduce streaming for more dynamic answers, and how we can automate the generation of insightful follow-up questions. The tutorial rounds off with the final touches needed to get our server up and running smoothly. For those eager to dive in and start experimenting on your own, I'll be providing a link to download the entire repository from the video description soon. This is your chance to get hands-on experience and truly understand the ins and outs of building an advanced answer engine. And if you find this video helpful, don't forget to support the channel by subscribing and sharing it with others who might benefit from this tutorial. Stay tuned for more updates and happy coding!