fal-ai/fal

What it solves

It removes the need for infrastructure management when running and scaling Python code in the cloud. It allows developers to build pipelines and serve ML models that can scale up to many users and automatically scale down to zero when not in use.

How it works

The project provides two primary Python packages:

• fal: A SDK and CLI used to define, test, and deploy serverless applications. Developers can create apps using a class-based structure and deploy them to persistent endpoints.
• fal-client: A client library used to call model APIs or custom deployed endpoints from Python code.

Who it’s for

Developers and ML engineers who want to deploy ML models and pipelines as serverless endpoints without managing servers or infrastructure.

Highlights

• Serverless Runtime: Scales automatically from zero to many users.
• Simplified Deployment: Includes a CLI for testing with temporary URLs and deploying to production.
• fal-client Integration: Easy way to trigger model APIs (like Flux) or custom apps via Python.
• No Infra Management: Focuses on code rather than server configuration.