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modal

Execute Python code on the Modal serverless compute platform.

27|2|Updated Mar 27, 2026
Search Tags:#deployment#serverless#python#gpu#modal#endpoints#sandbox
One-click install
npx skills add https://github.com/maragudk/fabrik --skill modal-maragudk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: modal
Source: https://github.com/maragudk/fabrik/tree/main/skills/modal
Command: npx skills add https://github.com/maragudk/fabrik --skill modal-maragudk

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Modal provides a streamlined way to run Python code using a serverless compute platform, simplifying deployment and experimentation for AI workloads.

Core Features & Use Cases

  • Run AI inference, training, and sandboxes on demand with automatic scaling and per-second billing.
  • Build HTTP endpoints and background workers using Python decorators like @app.function and @modal.fastapi_endpoint.
  • Rapidly iterate from development to deployment with modal run, modal serve, and modal deploy workflows.

Quick Start

Install Modal, define an App with decorated functions, and deploy to run remotely.

Frequently Asked Questions about modal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy Python code to a serverless compute platform?▼

Deploy Python code to serverless compute by installing the Modal CLI, defining an App with decorated functions like @app.function, and using the modal deploy workflow to run it remotely.

Can I run AI inference and training workloads with GPU support?▼

Run AI inference and training workloads with GPU support by configuring GPU resources within your Modal App definitions, enabling automatic scaling and per-second billing for on-demand execution.

What is the best way to create HTTP endpoints and web APIs in Python?▼

Create HTTP endpoints and web APIs in Python by using the @modal.fastapi_endpoint decorator on your App functions, allowing you to build and serve web endpoints directly from your serverless compute code.

How do I set up sandbox environments for remote code execution?▼

Set up sandbox environments for remote code execution by configuring sandbox settings within your Modal App, utilizing custom images, volumes, and secrets to isolate and manage dependencies securely.

Does Modal support scheduled batch jobs and background workers?▼

Modal supports scheduled batch jobs and background workers by applying Python decorators and schedule configurations to your functions, enabling automated task execution alongside your serverless applications.

What are the limitations of using serverless compute for AI workloads?▼

Serverless compute for AI workloads provides automatic scaling and per-second billing but requires configuring images, volumes, and secrets, meaning local state is lost between executions without persistent storage.

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