# ModelRunner Docs

## Docs

- [API keys](https://modelrunner.ai/docs/api-keys.md): Create, name, copy, and delete API keys from your ModelRunner profile
- [Cancel Request](https://modelrunner.ai/docs/api-reference/cancel-request.md): Attempt to cancel an in-queue or in-progress request. Returns the current status payload.
- [Create Request](https://modelrunner.ai/docs/api-reference/create-request.md): Enqueue a new inference job for the specified model. Request body must match the model's PredictionRequest schema.
- [Errors](https://modelrunner.ai/docs/api-reference/errors.md): Error response shape, status codes, and how to handle each class of failure.
- [Get Request Result](https://modelrunner.ai/docs/api-reference/get-request-result.md): Retrieve the final output and metadata for a completed request.
- [Get Request Status](https://modelrunner.ai/docs/api-reference/get-request-status.md): Check the current status of an inference request.
- [Authorization](https://modelrunner.ai/docs/api-reference/introduction.md): Use API keys in the Authorization header to access ModelRunner APIs.
- [JavaScript Client](https://modelrunner.ai/docs/clients/js-client.md): Install, configure, and use the ModelRunner JavaScript/TypeScript SDK.
- [Python Client](https://modelrunner.ai/docs/clients/python-client.md): Install, configure, and use the ModelRunner Python SDK.
- [FAQ](https://modelrunner.ai/docs/faq.md): Common questions about authentication, billing, supported file types, and platform limits.
- [File uploads](https://modelrunner.ai/docs/guides/file-uploads.md): Upload images, audio, video, and other binary inputs to ModelRunner storage and pass the resulting URLs to model inputs.
- [MCP server](https://modelrunner.ai/docs/guides/mcp-server.md): Connect Claude Desktop, Claude Code, Cursor, and other MCP clients directly to ModelRunner — run models, manage files, and inspect requests from your AI assistant.
- [Request lifecycle](https://modelrunner.ai/docs/guides/request-lifecycle.md): How an inference request moves from submission to terminal state, and the platform guarantees around finalization.
- [Build a wrapper](https://modelrunner.ai/docs/guides/wrappers/authoring.md): Design, preview, and publish a wrapper end to end — guided by your AI assistant over the MCP server.
- [Wrappers](https://modelrunner.ai/docs/guides/wrappers/overview.md): Turn a raw model into a purpose-built product — your own inputs and a baked-in prompt recipe — callable at a single endpoint.
- [Prompt templates](https://modelrunner.ai/docs/guides/wrappers/prompt-templates.md): The Handlebars template that turns your wrapper's inputs into the prompt the base model receives — variables, lookup maps, helpers, and the rules to follow.
- [Switching base models](https://modelrunner.ai/docs/guides/wrappers/switching-base-models.md): Put one stable interface in front of several models — pick a default, let callers choose at request time, and bridge schema differences with per-model mappings.
- [Introduction](https://modelrunner.ai/docs/index.md): Explore our guides and examples to start running AI models with ModelRunner
- [Next.js App Router](https://modelrunner.ai/docs/recipes-nextjs-app.md): Create a Next.js app (App Router) with a simple form that calls a ModelRunner model using the JavaScript client.

## OpenAPI Specs

- [openapi](https://modelrunner.ai/docs/openapi.json)