Chat Completions


POST https://api.devotel.com/v1/chat/completions

The one endpoint you need. Request and response shapes match the OpenAI Chat Completions API.

Request parameters

These are validated by the gateway:

Parameter	Type	Notes
`model`	string, required	`kimi-k3`. See Models.
`messages`	array, required	At least one message. Roles below.
`stream`	boolean	`true` for SSE. See Streaming.
`stream_options`	object	`{ "include_usage": true }` is forced on for every stream.
`temperature`	number	0–2.
`top_p`	number	0–1.
`max_tokens`	integer	Positive. Read the warning below before setting it.
`stop`	string \| string[]	At most 4 strings.
`tools`	array	Function definitions. See Tool Calling.
`tool_choice`	string \| object	`auto`, `none`, `required`, or a named function.

Unlisted parameters are forwarded unchanged. seed, presence_penalty, frequency_penalty, response_format, parallel_tool_calls, user and anything else the provider accepts pass straight through — the gateway validates what it knows and does not strip the rest, so SDK features keep working without waiting on us.

Message roles

Role	Use
`system`	Instructions that frame the conversation
`user`	Input from the person
`assistant`	A previous model reply, including one carrying `tool_calls`
`tool`	The result of a tool call; needs `tool_call_id`

content may be a string, null (on assistant turns that only call tools), or an array of parts for image input:


{
  "role": "user",
  "content": [
    { "type": "text", "text": "What is in this image?" },
    { "type": "image_url", "image_url": { "url": "data:image/png;base64,iVBORw0..." } }
  ]
}

Response


{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "created": 1787058728,
  "model": "kimi-k3",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The weather in Izmir right now is 31°C and sunny.",
        "reasoning_content": "The tool returned 31°C and sunny, so I will report that."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 200,
    "completion_tokens": 115,
    "total_tokens": 315
  }
}

finish_reason is stop when the model finished, tool_calls when it wants a tool run, or length if it hit a token cap.

Reasoning content

Kimi K3 thinks before it answers, and returns that thinking separately.


"message": {
  "content": "Hello there, how are you?",
  "reasoning_content": "The user asked for exactly five words. Let me count: Hello(1) there(2)..."
}

content is the answer. Show it to users.
reasoning_content is the thinking. It is not addressed to the user. Hide it, or put it behind a “Thinking” toggle the way the Devotel chat app does.
Do not send reasoning_content back in later turns. Send role and content only.

Reasoning tokens are output tokens

Reasoning is counted inside completion_tokens and billed at the output rate. Some responses also break it out:


"usage": {
  "prompt_tokens": 94,
  "completion_tokens": 799,
  "total_tokens": 893,
  "completion_tokens_details": { "reasoning_tokens": 782 }
}

That is a real measurement: a “write a haiku about proxies” request spent 782 reasoning tokens to produce a 72-character poem. Budget accordingly — short answers are not cheap answers with this model.

Be careful with max_tokens. The cap covers reasoning and the answer. Set it too low and the model spends the budget thinking, then gets cut off with finish_reason: "length" and an empty content. If you do not have a specific reason to cap output, leave max_tokens unset — that is what the Devotel chat app does.

Cached prompt tokens

The provider reports prompt-cache activity when it applies. These fields pass through untouched and vary by request:


"usage": {
  "prompt_tokens": 200,
  "prompt_tokens_details": { "cached_tokens": 12 },
  "cache_read_input_tokens": 0,
  "cache_created_input_tokens": 0
}

Treat them as informational — prompt_tokens and completion_tokens are what Devotel meters.

Request size

Request bodies are capped at 2 MB. Larger requests get 413.

Not available yet

/v1/embeddings, /v1/completions (the legacy endpoint) and image generation are not implemented. Unknown paths return 404 with code unknown_url.