The AI revolution is here. As developers, we’ve all seen it transform the way we work on a daily basis and, with the ability to integrate generative AI services into applications, we’re seeing it transform the products we build.
In the near term, it will become the user’s default expectation to have AI-powered features integrated into the products they use. More than ever, it’s important to understand how you can amplify your projects with the power of AI.
In this course, we’ll explore using a stack comprised of Hasura, a vectordb service, and Next.js paired with Tailwind to quickly create an engaging and helpful tool to support HR managers. This tool will leverage the power of near-text queries from vectorized data and even allow querying of a large language model (LLM) to return human-like responses on our data.
Key topics and takeaways
- Vectorizing relational data
- Writing LLM queries
- Using the new App Router in Next.js
- Developing a UI with Tailwind
By the end of this course, you’ll be able to…
- Shape relational data for vectorization.
- Vectorize relational data.
- Create an API for handling Event Triggers and Actions with Hasura.
- Integrate OpenAI with vectorized data.
- Create a Next.js application using the new App Router.
- Style an application with Tailwind.
- Manage state with React's Context API.
What will we be building?
We'll build a fullstack HR tool that allows HR managers to search through resumes of open positions. A user can ask questions using natural language and choose to either get an array of applications that match the query or get a response from an LLM.
Will this course teach Next.js concepts as well?
In part, yes. We expect you to have a basic understanding of React and Next.js, but we'll be using the new App Router and we'll build the UI with Tailwind. We'll cover these topics in detail, but we won't be covering the basics of React or Next.js.
What do I need to take this tutorial?
At present, we support ARM64 and amd64 architectures for the Hasura image used with this tutorial.
Please note, we recommend a paid OpenAI account for this tutorial. The free account has a limited number of tokens and the rate-limiting will prevent you from completing the tutorial.
How long will this tutorial take?
After installing everything above, you can have a functioning, fullstack AI-powered application in less than 90 minutes.
- Build apps and APIs 10x faster
- Built-in authorization and caching
- 8x more performant than hand-rolled APIs