AI SDK with Flask

Flask + Vercel is a boilerplate example that pairs a Flask API with the AI SDK and deploys it on Vercel using Serverless Functions and the Python Runtime. It shows how to run a Python web server (WSGI) on Vercel's serverless platform and expose an AI generation endpoint.

What is Flask + Vercel?

Flask + Vercel is a GitHub template maintained by Vercel Labs that demonstrates running a Flask application as a Vercel Serverless Function. The application uses the Web Server Gateway Interface (WSGI) to handle HTTP requests, and it integrates the AI SDK to provide an AI text generation endpoint. The template is designed to be cloned and deployed directly to Vercel with the provided Deploy button. Users can run it locally with gunicorn, and it is hosted on Vercel's Python Runtime.

Key Features

• Flask framework — a minimal Python web server using Flask, configured as a WSGI application for Vercel Serverless Functions.
• AI SDK integration — the template includes an /api/generate endpoint that accepts a prompt query parameter and returns AI-generated text.
• Vercel deployment — one-click deploy via the Vercel button, using the Python Runtime for serverless execution.
• Local development — instructions for running the app locally with gunicorn on port 3000.
• Dependency management — uses uv sync or pip to install Flask and gunicorn.
• Demo endpoint — a live example at https://ai-sdk-preview-flask.vercel.app/api/generate?prompt="hey!" shows the AI SDK in action.

Who is it for?

• Python developers who want to deploy Flask apps on Vercel's serverless platform with minimal configuration.
• AI engineers looking for a starting point to integrate AI SDK capabilities into a Python backend.
• Full-stack developers who need a quick way to prototype an AI-powered API endpoint with Flask.

What can you do with Flask + Vercel?

• Prototype AI endpoints: quickly create a serverless API that generates text from prompts using the AI SDK.
• Learn Vercel Python deployment: understand how WSGI apps run as serverless functions and adapt the setup for custom Flask routes.
• Build on a minimal base: extend the template with additional Flask routes, middleware, or AI model integrations.

How does Flask + Vercel work?

The template uses Flask to handle incoming HTTP requests via WSGI, which Vercel's Serverless Functions invoke. The /api/generate route extracts a prompt from the query string and passes it to the AI SDK, which returns generated text as the response. Deploying to Vercel automatically configures the Python Runtime to run the Flask app.

FAQ

Is Flask + Vercel free to use?

Yes, the template is open-source and free to clone and deploy on Vercel. However, usage of Vercel's Serverless Functions may be subject to Vercel's pricing plans and limits.

What does Flask + Vercel do?

It provides a ready-to-use Flask application that runs on Vercel's serverless platform and includes an AI SDK endpoint for generating text from prompts. It serves as a starting point for building Python-based AI APIs on Vercel.

How do I run Flask + Vercel locally?

After cloning the repository, install Vercel CLI globally, create a Python virtual environment, install dependencies with uv sync or pip, and start the server with gunicorn main:app. The app will be available at http://localhost:3000.

What is the AI SDK used for in this template?

The AI SDK is used in the /api/generate endpoint to process a prompt parameter and return AI-generated text. This demonstrates how to integrate AI capabilities into a serverless Flask API.