Chat Completions API - Unbound Security

Overview

The Unbound Security AI Gateway provides a RESTful API that allows you to integrate AI capabilities into your applications while maintaining enterprise-grade security, cost control, and compliance. The API is compatible with OpenAI’s Chat Completions API format, making it easy to migrate existing integrations.

Base URL

All API requests should be made to:

https://api.getunbound.ai/v1

Authentication

The Unbound API uses Bearer token authentication. Include your API key in the Authorization header:

Authorization: Bearer YOUR_API_KEY

Get your API key at gateway.getunbound.ai/connect.

Chat Completions

Create a completion for the provided chat messages.

Endpoint

POST /v1/chat/completions

Request Headers

Header	Type	Required	Description
`Authorization`	string	Yes	Bearer token with your API key
`Content-Type`	string	Yes	Must be `application/json`

Request Body

Parameter	Type	Required	Description
`model`	string	Yes	The model to use for completion. Accepts either `provider/model` (e.g. `anthropic/claude-sonnet-4-20250514`) or the bare model id (e.g. `claude-sonnet-4-20250514`).
`messages`	array	Yes	Array of message objects
`max_tokens`	integer	No	Maximum tokens to generate (default: 1000)
`temperature`	number	No	Sampling temperature (0.0 to 2.0, default: 1.0)
`stream`	boolean	No	Whether to stream the response (default: false)

The model field in the response is always the bare model id without the provider prefix, regardless of which form you sent. The original provider is returned separately as the top-level provider field (see Response Body).

Message Object

Parameter	Type	Required	Description
`role`	string	Yes	Role of the message sender (`user`, `assistant`, `system`)
`content`	string	Yes	Content of the message

Response Body

Field	Type	Description
`id`	string	Unique identifier for the completion
`object`	string	Object type. Anthropic, Google, Vertex AI, Cohere, and Workers AI return `"chat_completion"`; OpenAI and Bedrock return `"chat.completion"`.
`created`	integer	Unix timestamp (seconds) when the response was generated
`model`	string	The bare model id (provider prefix stripped)
`provider`	string	The upstream provider that served the request (e.g. `"anthropic"`, `"openai"`, `"google"`)
`choices`	array	Array of completion choices — see below
`usage`	object	Token usage — `prompt_tokens`, `completion_tokens`, `total_tokens`, plus optional `cache_read_input_tokens` / `cache_creation_input_tokens`
`hook_results`	object	Present only when guardrail hooks ran for this request. Contains `before_request_hooks` and `after_request_hooks` arrays describing each hook’s verdict.

Each entry in choices has:

Field	Type	Description
`index`	integer	Position of this choice in the array
`message.role`	string	Always `"assistant"` for completion responses
`message.content`	string \| array	Plain string for text-only replies; an array of content blocks (e.g. `[{"type": "text", "text": "..."}]`) when the upstream returns structured content such as text + tool use
`message.tool_calls`	array	Present when the model invoked tools
`finish_reason`	string	`"stop"` (natural completion), `"length"` (hit `max_tokens`), `"tool_calls"` (model invoked a tool), or a provider-specific passthrough value for less common stop reasons
`logprobs`	object \| null	Log probabilities, when requested by the provider

Example Request

curl -X POST 'https://api.getunbound.ai/v1/chat/completions' \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "messages": [
      {
        "role": "user",
        "content": "Help me plan meals for the week."
      }
    ]
  }'

Example Response

{
  "id": "msg_01ABCdefGHIJkLMnopQRStu",
  "object": "chat_completion",
  "created": 1677652288,
  "model": "claude-sonnet-4-20250514",
  "provider": "anthropic",
  "choices": [
    {
      "index": 0,
      "logprobs": null,
      "message": {
        "role": "assistant",
        "content": [
          {
            "type": "text",
            "text": "Here's a balanced meal plan for the week..."
          }
        ]
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 15,
    "completion_tokens": 245,
    "total_tokens": 260
  }
}

For plain text-only completions some providers return message.content as a string instead of a content-block array. Clients should accept both shapes — check Array.isArray(content) before iterating.

Multi-turn Conversation

curl -X POST 'https://api.getunbound.ai/v1/chat/completions' \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful coding assistant."
      },
      {
        "role": "user",
        "content": "How do I create a REST API in Python?"
      },
      {
        "role": "assistant",
        "content": "I can help you create a REST API in Python using Flask or FastAPI. Which framework would you prefer?"
      },
      {
        "role": "user",
        "content": "Let's use FastAPI"
      }
    ],
    "max_tokens": 1000,
    "temperature": 0.7
  }'

The response shape is identical to the single-turn case:

{
  "id": "msg_01XYZabc456",
  "object": "chat_completion",
  "created": 1677652290,
  "model": "claude-sonnet-4-20250514",
  "provider": "anthropic",
  "choices": [
    {
      "index": 0,
      "logprobs": null,
      "message": {
        "role": "assistant",
        "content": [
          {
            "type": "text",
            "text": "Great — let's set up a basic FastAPI app..."
          }
        ]
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 84,
    "completion_tokens": 312,
    "total_tokens": 396
  }
}

Streaming Response

Pass --no-buffer so curl flushes each chunk as it arrives instead of waiting for the full response:

curl --no-buffer -X POST 'https://api.getunbound.ai/v1/chat/completions' \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "messages": [
      {
        "role": "user",
        "content": "Write a Python function to calculate fibonacci numbers"
      }
    ],
    "stream": true
  }'

Streaming responses are always normalized to OpenAI’s Server-Sent Events shape, regardless of the upstream provider. Every chunk uses "object": "chat.completion.chunk" (dot notation) — including chunks served by Anthropic, Google, Vertex AI, Cohere, and Workers AI, whose non-streaming object value is "chat_completion" (underscore). Build clients that branch on object accordingly. The stream ends with data: [DONE]:

data: {"id":"msg_01ABC","object":"chat.completion.chunk","created":1677652288,"model":"claude-sonnet-4-20250514","provider":"anthropic","choices":[{"index":0,"delta":{"role":"assistant","content":"def "},"finish_reason":null}]}

data: {"id":"msg_01ABC","object":"chat.completion.chunk","created":1677652288,"model":"claude-sonnet-4-20250514","provider":"anthropic","choices":[{"index":0,"delta":{"content":"fib(n):"},"finish_reason":null}]}

...

data: {"id":"msg_01ABC","object":"chat.completion.chunk","created":1677652288,"model":"claude-sonnet-4-20250514","provider":"anthropic","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":18,"completion_tokens":62}}

data: [DONE]

The final usage block on streaming responses contains prompt_tokens and completion_tokens only — total_tokens is not emitted on the stream. Sum the two client-side if you need it.

List Models

Retrieve available models and their pricing from the gateway

Python SDK

Use the Unbound Python SDK for drop-in OpenAI compatibility

​Overview

​Base URL

​Authentication

​Chat Completions

​Endpoint

​Request Headers

​Request Body

​Message Object

​Response Body

​Example Request

​Example Response

​Multi-turn Conversation

​Streaming Response

List Models

Python SDK

Overview

Base URL

Authentication

Chat Completions

Endpoint

Request Headers

Request Body

Message Object

Response Body

Example Request

Example Response

Multi-turn Conversation

Streaming Response