Build with SimpleLLM

Your first request, practical guides, and the complete HTTP reference.

↗QuickstartFrom API key to a first response with cURL, Python, or TypeScript.↗OpenCodeConfigure the SimpleLLM provider and refresh discovered models.↗Streaming & cancellationRead SSE events, handle partial responses, and cancel generation.↗Models & pricingModel IDs, context windows, input, cache and output prices.↗Create a chat completionPOST /v1/chat/completions ↗Compatibility & AI docsSupported V1 surface, machine-readable documentation, and boundaries.

Connect your application to the SimpleLLM inference API using familiar OpenAI-compatible requests. Start with a single chat completion, add streaming or tools, then integrate usage and error handling before shipping.

Start here

New integration? Follow the Quickstart to create a key, select a model, and receive your first response. Already using a coding tool? The OpenCode and OpenClaw setup guides configure the provider for you. For Zed, copy the sample provider configuration and add your API key in the editor.

The API base URL is https://api.simplellm.eu/v1. For chat, use POST /v1/chat/completions; the website and dashboard are not inference endpoints.

Guides and API reference

Guides explain how to build a working integration, including the parts your application must handle. The HTTP reference describes individual endpoints, request fields, response fields, content types, and errors.

Chat completions: messages, system instructions, and conversation history.
Streaming: incremental output, usage events, cancellation, and partial results.
Tool calling: a complete function-call round trip with argument validation.
Vision: URL and inline image requests for compatible models.
Reasoning and JSON: output budgets and model-dependent structured responses.
Speech and images: separate media endpoints and response handling.

Before going live

Use rate limits and bounded retries, decide how to handle an interrupted response, and understand token and cache billing. Monitor usage per API key and keep credentials out of browser code.

Model-specific capabilities are not interchangeable: an OpenAI-compatible request format does not make every model support images, tools, or JSON schemas.

For coding assistants

Every guide and reference page has a Markdown version linked at the top. llms.txt indexes individual pages; llms-full.txt contains the full text, and OpenAPI JSON contains the HTTP contract.

The HTML content is generated ahead of time and remains readable without JavaScript. Search, copying, and theme controls are optional conveniences.