> ## Documentation Index
> Fetch the complete documentation index at: https://docs.magnitude.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Endpoints

> OpenAI-compatible and Anthropic-compatible routes with examples.

All paths are relative to `http://127.0.0.1:10100`. From another device, use the server's network address and API key; see [Network access](/api/network-access).

| Method | Path | Purpose |
| - | - | - |
| `GET` | `/health` | Returns `200` when the service is ready. |
| `GET` | `/inference/v1/models` | List models available for inference. |
| `POST` | `/inference/v1/chat/completions` | OpenAI Chat Completions, JSON or streaming. |
| `POST` | `/inference/v1/responses` | OpenAI Responses, JSON or streaming. |
| `POST` | `/inference/anthropic/v1/messages` | Anthropic Messages. `max_tokens` is required. |
| `POST` | `/inference/anthropic/v1/messages/count_tokens` | Count input tokens for an Anthropic-format request. |

Supported inputs and features depend on the model. Your application keeps the conversation history and executes any tools the model requests.

## Chat completion

Replace `MODEL_ID` with an ID from the models endpoint:

```sh theme={"theme":{"light":"github-light","dark":"github-dark"}}
curl http://127.0.0.1:10100/inference/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "MODEL_ID",
    "messages": [{"role": "user", "content": "Explain prompt caching in one paragraph."}],
    "max_tokens": 256
  }'
```

The generated text is in `choices[0].message.content`.

## Streaming

Add `"stream": true` to the request body. Responses arrive as server-sent events. With curl, add `-N` to print events as they arrive.

## Anthropic Messages

```sh theme={"theme":{"light":"github-light","dark":"github-dark"}}
curl http://127.0.0.1:10100/inference/anthropic/v1/messages \
  -H 'Content-Type: application/json' \
  -H 'anthropic-version: 2023-06-01' \
  -d '{
    "model": "MODEL_ID",
    "max_tokens": 256,
    "messages": [{"role": "user", "content": "Explain prompt caching in one paragraph."}]
  }'
```

The generated text is in `content[0].text`.

These examples use macOS and Linux quoting. On Windows, use `curl.exe` with quoting appropriate for your shell, or send the same JSON from your application.


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