Chat Completions

Create chat completion responses. Supports text generation, multimodal input, Function Calling, streaming, and more.

Endpoint


POST https://api.ofox.ai/v1/chat/completions

Request Parameters

Parameter	Type	Required	Description
`model`	string	✅	Model identifier, e.g. `openai/gpt-4o`
`messages`	array	✅	Message array
`temperature`	number	—	Sampling temperature 0-2, default 1
`max_tokens`	number	—	Maximum tokens to generate
`stream`	boolean	—	Enable streaming response
`top_p`	number	—	Nucleus sampling parameter
`frequency_penalty`	number	—	Frequency penalty -2 to 2
`presence_penalty`	number	—	Presence penalty -2 to 2
`tools`	array	—	Tool definitions (Function Calling)
`tool_choice`	string/object	—	Tool selection strategy
`response_format`	object	—	Response format (JSON Mode)
`provider`	object	—	OfoxAI extension: routing and fallback config

Message Format


interface Message {
  role: 'system' | 'user' | 'assistant' | 'tool'
  content: string | ContentPart[]  // Text or multimodal content
  name?: string
  tool_calls?: ToolCall[]          // Tool calls in assistant messages
  tool_call_id?: string            // Call ID in tool messages
}
 
// Multimodal content
type ContentPart =
  | { type: 'text'; text: string }
  | { type: 'image_url'; image_url: { url: string; detail?: 'auto' | 'low' | 'high' } }

Request Examples

cURL

Terminal


curl https://api.ofox.ai/v1/chat/completions \
  -H "Authorization: Bearer $OFOX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-4o",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Explain what an API Gateway is"}
    ],
    "temperature": 0.7
  }'

Python

chat.py


from openai import OpenAI
 
client = OpenAI(
    base_url="https://api.ofox.ai/v1",
    api_key="<your OFOXAI_API_KEY>"
)
 
response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain what an API Gateway is"}
    ],
    temperature=0.7
)
 
print(response.choices[0].message.content)

TypeScript

chat.ts


import OpenAI from 'openai'
 
const client = new OpenAI({
  baseURL: 'https://api.ofox.ai/v1',
  apiKey: '<your OFOXAI_API_KEY>'
})
 
const response = await client.chat.completions.create({
  model: 'openai/gpt-4o',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Explain what an API Gateway is' }
  ],
  temperature: 0.7
})
 
console.log(response.choices[0].message.content)

Response Format


{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1703123456,
  "model": "openai/gpt-4o",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "An API Gateway is a..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 150,
    "total_tokens": 175
  }
}

Streaming

Set stream: true to enable SSE streaming responses:

Python

stream.py


stream = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True
)
 
for chunk in stream:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="", flush=True)

Streaming Response Format

Each chunk is sent via SSE:


data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":" there"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]

Multimodal Input (Vision)

Send images for model analysis:


response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What's in this image?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}}
        ]
    }]
)

Models with vision capabilities include openai/gpt-4o, anthropic/claude-sonnet-4.5, google/gemini-3-flash-preview, and more. See the Vision guide for details.

Function Calling

See the Function Calling guide for details.