Chat Completions API

Reasoning

Reasoning models think before they answer. The reasoning arrives in reasoning_content next to content and its tokens are billed as output, reported in usage.completion_tokens_details.reasoning_tokens. Reasoning is on by default. Control it with the reasoning object or OpenAI's reasoning_effort:

GLM 5.3 Flash always reasons: with reasoning turned off it still thinks briefly, the reasoning is left out of the reply, and those tokens are billed as output. It has two effort levels, low and high; medium runs as high.

Streaming

With stream: true the reply arrives as Server-Sent Events, and the final chunk before data: [DONE] always carries usage, whether or not you set stream_options. While a long prompt is being read, the stream sends : ping comment lines to keep the connection open; SSE clients ignore them. If the request fails after the stream has started, it ends with one data: {"error": {...}} event in the error shape below.

Endpoint

• Create a chat completion: POST https://api.openscale.so/v1/chat/completions

Create a chat completion

POST https://api.openscale.so/v1/chat/completions

Send a conversation and receive the next assistant message. Set stream: true for Server-Sent Events. Models that reason return their reasoning in reasoning_content alongside content; when replaying a tool-calling conversation, send reasoning_content back on the assistant messages.

Request body

Simple request

curl https://api.openscale.so/v1/chat/completions \
  -H "Authorization: Bearer $OPENSCALE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek/deepseek-v4.1-flash",
  "messages": [
    {
      "role": "user",
      "content": "Hello from OpenScale"
    }
  ]
}'

Streamed, reasoning off

curl https://api.openscale.so/v1/chat/completions \
  -H "Authorization: Bearer $OPENSCALE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek/deepseek-v4.1-flash",
  "stream": true,
  "reasoning": {
    "enabled": false
  },
  "messages": [
    {
      "role": "user",
      "content": "Hello from OpenScale"
    }
  ]
}'

Response

200: The completion, or an SSE stream when stream is true.

{
  "id": "chatcmpl-ucOlCLBJhTr5ahpQzgJaeiK8",
  "object": "chat.completion",
  "created": 1790078324,
  "model": "deepseek/deepseek-v4.1-flash",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I help you today?",
        "reasoning_content": "The user is greeting me."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 17,
    "completion_tokens": 42,
    "total_tokens": 59,
    "prompt_tokens_details": {
      "cached_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 31
    }
  }
}

data: {"id":"chatcmpl-y3nR30I9R87biSC5oz4gHeF5","object":"chat.completion.chunk","model":"deepseek/deepseek-v4.1-flash","choices":[{"index":0,"delta":{"role":"assistant","content":"Hel"},"finish_reason":null}]}

data: {"id":"chatcmpl-y3nR30I9R87biSC5oz4gHeF5","object":"chat.completion.chunk","model":"deepseek/deepseek-v4.1-flash","choices":[{"index":0,"delta":{"content":"lo"},"finish_reason":"stop"}]}

data: {"id":"chatcmpl-y3nR30I9R87biSC5oz4gHeF5","object":"chat.completion.chunk","model":"deepseek/deepseek-v4.1-flash","choices":[],"usage":{"prompt_tokens":17,"completion_tokens":2,"total_tokens":19}}

data: [DONE]

Errors

Objects

The Message object

The ToolCall object

The Usage object

The ChatCompletionChunk object

One Server-Sent Event data: payload. The stream ends with data: [DONE].

More of the API reference

• API reference: base URLs, authentication and a first request.
• Responses: POST /v1/responses: the OpenAI Responses format with stored state, background runs and enforced tool rules.
• Conversations: Keep the turns of a Responses conversation on our side and continue it by id.
• Prompts: Save instructions, messages and settings once, then use them by id in the Responses API.
• Anthropic Messages: POST /anthropic/v1/messages: the Anthropic Messages format, for Claude Code and Anthropic SDKs.
• Models and pricing: Model ids, prices per 1M tokens, context windows, output limits, versions and the live catalog endpoint.
• Batch: Upload a JSONL file of chat completions, create a batch and collect the results when it finishes.
• Errors: The error shape, every status code and code, and which ones to retry.
• Rate limits: Requests and tokens per minute, how a 429 tells you when to retry, and how to get more.
• Data retention: What is stored, for how long, how to delete it, and zero data retention.
• Interactive reference: try every endpoint in the browser.
• OpenAPI document: the whole API as OpenAPI 3.1.