Cut.ProDocs
Generate with AI: chat and embeddings

Turn text into embeddings

OpenAI's embeddings request, for every model with endpoint: embeddings in GET /models. Billed by the tokens read; usage.credits reports what it cost.

Authorization

apiKey
X-Api-Key<token>

In: header

Request Body

TypeScript Definitions

Use the request body type in TypeScript.

Response Body

application/json

application/json

application/json

application/json

POST
/embeddings
curl -X POST "https://example.com/embeddings" \  -H "Content-Type: application/json" \  -d '{    "model": "string",    "input": "string",    "property1": null,    "property2": null  }'
{  "code": "REQUEST_INVALID"}

Chat with a language model POST

OpenAI's Chat Completions, for every chat model in `GET /models` (Claude, GPT, Gemini, Grok, DeepSeek, Qwen, Llama, Mistral and more): point any OpenAI SDK at `https://api.cut.pro/api/v1` with your API key. Streaming, tools, images in the messages and structured answers work where the model supports them. Billed by the tokens read and written at the prices of `GET /models`; fractions of a credit add up and leave the balance as whole credits. A plain answer reports what it cost in `usage.credits`. The balance must cover what the call can cost, counting the answer's `max_tokens`.