Full-stack AI SaaS Development with Next.js, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind

📚 The video is about building a chat with PDF SAS product that uses OpenAI to interact with PDF files.

💻 The video covers topics such as deploying on the edge runtime, using DrizzleORM for database interaction, integrating Stripe for subscriptions, and uploading files to AWS S3.

🔒 The video also discusses setting up authentication with Clerk and protecting routes using middleware.

🎥 The video is about building and deploying a full stack AI SaaS using Next JS, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind.

💻 The video covers creating sign-in and sign-up pages using Clerk, setting up a database using NeonDB, and configuring the DrizzleORM for database interaction.

☁️ The video also explains how to set up AWS S3 for file upload, including creating a bucket and configuring access keys.

📚 The video tutorial demonstrates how to build and deploy a full stack AI SaaS application using Next JS 13, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind CSS.

🖥️ The tutorial covers topics like configuring the AWS S3 bucket, uploading files to AWS S3, creating vector embeddings using OpenAI, and using PineconeDB for storing vector embeddings.

🔍 The tutorial also explains how to search for documents by embedding text into vectors, finding similar vectors, and retrieving metadata for generating context.

📌 The video demonstrates how to build and deploy a full-stack AI SaaS using Next.js, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind.

🧠 The transcription covers the process of creating an account on Pinecone, creating an index, obtaining and splitting a PDF file, segmenting the PDF into smaller documents, and embedding the documents using OpenAI.

🚀 The goal is to enable students to understand how to build and deploy a full-stack AI SaaS by following the steps and using the mentioned technologies.

📜 The transcription discusses the process of building and deploying a full stack AI SaaS using Next JS, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind.

🔧 The video demonstrates how to access and manipulate metadata, vectorize and embed documents, and upload vector embeddings to PineconeDB.

💬 The chat component is implemented using the Versa AI SDK, allowing users to ask questions and receive responses in a streaming chat interface.

📝 The video is about building and deploying a full stack AI SaaS using Next JS, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind.

💻 The demonstration includes creating a chat component using the useChat function, mapping through messages, and styling the messages based on the user or AI response.

🔍 The video also covers retrieving relevant context from a PDF document and incorporating it into the chat response using OpenAI's prompt feature.

💡 The video is about building and deploying a full-stack AI SaaS using Next JS, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind CSS.

🔑 The main functionality of the chat-to-PDF project, including saving chat blocks, rendering initial messages, and implementing a loading effect, has been completed.

💰 The last part of the project focuses on integrating Stripe to create a software as a service (SaaS) and implementing subscription features.

💡 The video demonstrates the process of building and deploying a full-stack AI SaaS using Next JS, DrizzleORM, OpenAI, Stripe, TypeScript, and Tailwind CSS.

🏗️ The presenter explains the steps involved in checking if a user ID exists and setting the first chat for a user. They also show how to display a button that leads to the chat page and add an icon to make it visually appealing.

🔒 They discuss managing subscriptions and demonstrate how to fix an error related to enabling the building portal. They show how to create a customer portal session and activate the test mode for billing.

🚀 The video concludes by showing how to deploy the project on Versa and configure environmental variables for Stripe and the base URL. They demonstrate the functionality of the deployed application, including logging in, creating and viewing chats, and interacting with the chatbot.