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Build a Credit Payment System in Streamlit for Gen AI Apps

Ready to turn your Streamlit app into a pay-per-use service? In this series, we’ll build a credit-based payment system that’s perfect for generative AI apps. You’ll learn how to set up user logins, connect to a database, and integrate Stripe payments in Streamlit — all while creating a smooth credit-based pricing system. We’ll also dive into LLM API integration and wrap it up with tips on Streamlit production deployment. It’s a straightforward, step-by-step guide to launching your pay-per-use Streamlit app in no time.

Want to see an example? FastPrompt uses a credit system for monetisation - it generates high quality LLM system prompts from a simple description of inputs outputs. You can refine it with AI suggestions and iterate quickly.

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Setting Up User Login

User authentication is the first step in building any app that needs to track who’s who — like one with user credits 👀 — and with Streamlit’s new native authentication features, it’s easier than ever!

Connecting To A Database

Need to store user credits securely? In this post, we’ll show you how to hook your Streamlit app up to a database — with row-level security, secret-handling best practices, and a quick table setup walkthrough.

Integrating Stripe Checkouts

Ready to start charging for your app? In this post we will learn how to set up a pay-per-use system — from creating Stripe Checkout sessions to listening to webhooks.

Calling LLM APIs

Ready for your app to do something? In this post learn how to query an LLM API — including measuring costs and removing credits from users.

Deploying Your App

You’ve built something awesome — now it’s time to share it with the world! Learn the ins and outs of deploying your Streamlit app on Streamlit Cloud, it’s (almost) as simple as a single click.