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### cURL Example

Source: https://docs.tokenware.ai/docs/quick-started

Example of how to call the Chat Completions API using cURL.

```APIDOC
## cURL Example
```bash
curl https://open.vidau.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-your-api-key" \
  -d '{ \
    "model": "gpt-4o", \
    "messages": [ \
      {"role": "system", "content": "You are a helpful assistant."}, \
      {"role": "user", "content": "Hello!"} \
    ] \
  }'
```
```

--------------------------------

### Python (OpenAI SDK)

Source: https://docs.tokenware.ai/docs/quick-started

Example of how to use the OpenAI Python SDK to interact with the Chat Completions API.

```APIDOC
## Python (OpenAI SDK)
```python
from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://open.vidau.ai/v1"
)

response = client.chat.completions.create(
   model="gpt-4o",
   messages=[
       {"role": "system", "content": "You are a helpful assistant."},
       {"role": "user", "content": "Hello!"}
   ]
)

print(response.choices[0].message.content)
```
```

--------------------------------

### Python Function Calling Example

Source: https://docs.tokenware.ai/docs/quick-started

Demonstrates how to use the client library to enable function calling with a model. This is useful for integrating external tools or APIs.

```python
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "What's the weather in Tokyo?"}
    ],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get current weather for a city",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "city": {
                            "type": "string",
                            "description": "City name"
                        }
                    },
                    "required": ["city"]
                }
            }
        }
    ],
    tool_choice="auto"
)
```

--------------------------------

### Node.js

Source: https://docs.tokenware.ai/docs/quick-started

Example of how to use the OpenAI Node.js library to interact with the Chat Completions API.

```APIDOC
## Node.js
```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-your-api-key',
  baseURL: 'https://open.vidau.ai/v1',
});

const response = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    { role: 'user', content: 'Hello!' },
  ],
});

console.log(response.choices[0].message.content);
```
```

--------------------------------

### Python (Streaming)

Source: https://docs.tokenware.ai/docs/quick-started

Example of how to use the OpenAI Python SDK for streaming responses from the Chat Completions API.

```APIDOC
## Python (Streaming)
```python
from openai import OpenAI

client = OpenAI(
   api_key="sk-your-api-key",
   base_url="https://open.vidau.ai/v1"
)

stream = client.chat.completions.create(
   model="gpt-4o",
   messages=[
       {"role": "user", "content": "Write a short poem about coding."}
   ],
   stream=True
)

for chunk in stream:
   if chunk.choices[0].delta.content:
       print(chunk.choices[0].delta.content, end="")
```
```

--------------------------------

### Chat Completion with Python (OpenAI SDK)

Source: https://docs.tokenware.ai/docs/quick-started

This Python example demonstrates how to use the OpenAI SDK to make a chat completion request. Configure the client with your API key and the Vidau base URL.

```python
from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://open.vidau.ai/v1"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)
```

--------------------------------

### Chat Completion with Node.js

Source: https://docs.tokenware.ai/docs/quick-started

This Node.js example demonstrates how to make a chat completion request using the OpenAI SDK. Configure the client with your API key and the Vidau base URL.

```javascript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-your-api-key',
  baseURL: 'https://open.vidau.ai/v1',
});

const response = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    { role: 'user', content: 'Hello!' },
  ],
});

console.log(response.choices[0].message.content);
```

--------------------------------

### Streaming Chat Completion with Python

Source: https://docs.tokenware.ai/docs/quick-started

This Python example shows how to receive chat completion responses as a stream using the OpenAI SDK. This is useful for real-time applications.

```python
from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://open.vidau.ai/v1"
)

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "Write a short poem about coding."}
    ],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")
```

--------------------------------

### Python Chat Completion with Streaming

Source: https://docs.tokenware.ai/

Use the OpenAI Python SDK to interact with the unified API. Set the base URL to Tokenware's endpoint and authenticate with your API key. This example demonstrates streaming responses for chat completions.

```python
from openai import OpenAI

client = OpenAI(
    base_url="https://open.vidau.ai/v1",
    api_key="tw-your-api-key"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True
)

for chunk in response:
    print(chunk.choices[0].delta.content, end="")
```

--------------------------------

### GET /v1/models

Source: https://docs.tokenware.ai/docs/api-reference

Lists all available models supported by the API. This is useful for determining which models can be used for chat completions or embeddings.

```APIDOC
## GET /v1/models

### Description
List all available models.

### Method
GET

### Endpoint
/v1/models

### Parameters
None

### Request Example
```bash
curl https://open.vidau.ai/v1/models \
  -H "Authorization: Bearer sk-your-api-key"
```

### Response
#### Success Response (200)
- **object** (string) - Type of the response, "list".
- **data** (array) - An array of model objects.
  - **id** (string) - The unique identifier for the model.
  - **object** (string) - The type of the object, "model".
  - **created** (integer) - Timestamp of model creation.
  - **owned_by** (string) - The entity that owns the model.

#### Response Example
```json
{
  "object": "list",
  "data": [
    {
      "id": "gpt-4o",
      "object": "model",
      "created": 1714200000,
      "owned_by": "openai"
    },
    {
      "id": "gemini-2.5-flash",
      "object": "model",
      "created": 1714200000,
      "owned_by": "google"
    }
  ]
}
```
```

--------------------------------

### Get Video Generation Status

Source: https://docs.tokenware.ai/docs/api-reference

Use this endpoint to check the status of a video generation task. Polling every 5 seconds is recommended.

```bash
curl https://open.vidau.ai/v1/video/generations/vgen_abc123-def456 \
  -H "Authorization: Bearer sk-your-api-key"
```

--------------------------------

### GET /v1/video/generations/{id}

Source: https://docs.tokenware.ai/docs/api-reference

Polls the status of a video generation task using its ID.

```APIDOC
## GET /v1/video/generations/{id}

### Description
Poll the status of a video generation task.

### Method
GET

### Endpoint
/v1/video/generations/{id}

### Parameters
#### Path Parameters
- **id** (string) - Task ID returned from the POST endpoint

### Response — Processing
#### Success Response
- **id** (string) - The task ID.
- **status** (string) - The current status of the task (`processing`).
- **model** (string) - The video model used.
- **created_at** (integer) - Timestamp of task creation.

### Response Example (Processing)
```json
{
  "id": "vgen_abc123-def456",
  "status": "processing",
  "model": "veo-3",
  "created_at": 1714200000
}
```

### Response — Completed
#### Success Response
- **id** (string) - The task ID.
- **status** (string) - The current status of the task (`completed`).
- **model** (string) - The video model used.
- **created_at** (integer) - Timestamp of task creation.
- **completed_at** (integer) - Timestamp of task completion.
- **video** (object) - Details about the generated video.
  - **url** (string) - URL of the generated video.
  - **duration_seconds** (integer) - Duration of the video in seconds.
  - **resolution** (string) - Resolution of the video.

### Response Example (Completed)
```json
{
  "id": "vgen_abc123-def456",
  "status": "completed",
  "model": "veo-3",
  "created_at": 1714200000,
  "completed_at": 1714200120,
  "video": {
    "url": "https://static.vidau.ai/generated/task_vgen_abc123/video.mp4",
    "duration_seconds": 8,
    "resolution": "720p"
  }
}
```

### Response — Failed
#### Success Response
- **id** (string) - The task ID.
- **status** (string) - The current status of the task (`failed`).
- **model** (string) - The video model used.
- **created_at** (integer) - Timestamp of task creation.
- **error** (object) - Error details.
  - **message** (string) - Description of the error.

### Response Example (Failed)
```json
{
  "id": "vgen_abc123-def456",
  "status": "failed",
  "model": "veo-3",
  "created_at": 1714200000,
  "error": {
    "message": "Video generation timeout"
  }
}
```
```

--------------------------------

### List Available Models

Source: https://docs.tokenware.ai/docs/api-reference

Use this endpoint to retrieve a list of all models available through the Vidau API. Requires an API Key in the Authorization header.

```bash
curl https://open.vidau.ai/v1/models \
  -H "Authorization: Bearer sk-your-api-key"
```

--------------------------------

### Make a Chat Completion Request with cURL

Source: https://docs.tokenware.ai/docs/quick-started

Use this cURL command to send a basic chat completion request to the Vidau Open AI Gateway. Ensure you replace 'sk-your-api-key' with your actual API key.

```bash
curl https://open.vidau.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-your-api-key" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello!"}
    ]
  }'
```

--------------------------------

### Configure Webhook for Video Generation

Source: https://docs.tokenware.ai/docs/api-reference

Configure webhook notifications for video generation by including `webhook_url` and optionally `webhook_secret` in the POST request.

```json
{
  "model": "veo-3",
  "prompt": "...",
  "webhook_url": "https://your-server.com/hooks/video",
  "webhook_secret": "your-hmac-secret"
}
```

--------------------------------

### POST /v1/video/generations

Source: https://docs.tokenware.ai/docs/api-reference

Submits a video generation task. This is an asynchronous endpoint that returns immediately with a task ID.

```APIDOC
## POST /v1/video/generations

### Description
Submit a video generation task. Returns immediately with a task ID.

### Method
POST

### Endpoint
/v1/video/generations

### Parameters
#### Request Body
- **model** (string) - Yes - Video model name (e.g. `veo-3`)
- **prompt** (string) - Yes - Text description of the desired video
- **duration** (integer) - No - Video duration in seconds (default: `8`)
- **resolution** (string) - No - Video resolution: `"480p"`, `"720p"` (default), `"1080p"`
- **aspect_ratio** (string) - No - Aspect ratio (default: `"16:9"`)
- **reference_images** (array) - No - Reference images `[{ "data": "base64...", "mime_type": "image/png" }]`
- **first_frame** (object) - No - First frame image `{ "data": "base64...", "mime_type": "image/png" }`
- **last_frame** (object) - No - Last frame image
- **webhook_url** (string) - No - URL to receive completion/failure notifications
- **webhook_secret** (string) - No - HMAC-SHA256 secret for webhook signature verification

### Response (HTTP `202 Accepted`)
#### Success Response
- **id** (string) - The task ID.
- **status** (string) - The current status of the task (`processing`).
- **model** (string) - The video model used.
- **created_at** (integer) - Timestamp of task creation.

### Response Example
```json
{
  "id": "vgen_abc123-def456",
  "status": "processing",
  "model": "veo-3",
  "created_at": 1714200000
}
```

### Request Example
```bash
curl -X POST https://open.vidau.ai/v1/video/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{ \
    "model": "veo-3", \
    "prompt": "A cat playing piano in a jazz club", \
    "duration": 8, \
    "resolution": "720p" \
  }'
```
```

--------------------------------

### Video Generation with Extra Parameters

Source: https://docs.tokenware.ai/docs/quick-started

When using video models, pass specific video parameters like duration, resolution, and aspect ratio via the `extra_body` argument. The video URL is returned in the content, prefixed with `__VIDEO__:`.

```python
response = client.chat.completions.create(
    model="veo-2.0-generate",
    messages=[
        {"role": "user", "content": "A cinematic shot of a sunset over the ocean"}
    ],
    extra_body={
        "videoParams": {
            "durationSeconds": 8,
            "resolution": "720p",
            "aspectRatio": "16:9"
        }
    }
)

# The video URL is in the returned content
# Format: __VIDEO__:https://...
video_url = response.choices[0].message.content.replace("__VIDEO__:", "")
```

--------------------------------

### Submit Video Generation Task

Source: https://docs.tokenware.ai/docs/api-reference

Submit a request to generate a video from a text prompt. This is an asynchronous endpoint that returns a task ID immediately. You can specify model, duration, resolution, and aspect ratio.

```bash
curl -X POST https://open.vidau.ai/v1/video/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "veo-3",
    "prompt": "A cat playing piano in a jazz club",
    "duration": 8,
    "resolution": "720p"
  }'
```

--------------------------------

### Webhook Configuration

Source: https://docs.tokenware.ai/docs/api-reference

Configure webhook notifications for video generation status updates. Supports specifying a webhook URL and an optional secret for signature verification.

```APIDOC
### Webhook Configuration

Include `webhook_url` and optionally `webhook_secret` in the POST request:

```json
{
  "model": "veo-3",
  "prompt": "...",
  "webhook_url": "https://your-server.com/hooks/video",
  "webhook_secret": "your-hmac-secret"
}
```

### Notification Format

POST https://your-server.com/hooks/video
Content-Type: application/json
X-Webhook-Event: video.generation.completed
X-Webhook-Signature: sha256=abc123...

```json
{
  "event": "video.generation.completed",
  "task_id": "vgen_abc123-def456",
  "status": "completed",
  "model": "veo-3",
  "created_at": 1714200000,
  "completed_at": 1714200120,
  "video": {
    "url": "https://static.vidau.ai/generated/task_vgen_abc123/video.mp4",
    "duration_seconds": 8,
    "resolution": "720p"
  }
}
```
```

--------------------------------

### Generate Images with DALL-E 3

Source: https://docs.tokenware.ai/docs/api-reference

Use this endpoint to generate images from text prompts using the DALL-E 3 model. Ensure your API key is valid and included in the Authorization header.

```bash
curl https://open.vidau.ai/v1/images/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "dall-e-3",
    "prompt": "A cute cat wearing a space helmet",
    "size": "1024x1024"
  }'
```

--------------------------------

### Enable JSON Mode Output

Source: https://docs.tokenware.ai/docs/quick-started

Use the `response_format` parameter to ensure the model outputs valid JSON. This is useful for structured data retrieval.

```python
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "List 3 countries with capitals in JSON"}
    ],
    response_format={"type": "json_object"}
)
```

--------------------------------

### POST /v1/chat/completions

Source: https://docs.tokenware.ai/docs/quick-started

Generates a completion for a chat conversation. Supports various parameters for controlling model behavior, sampling, and output format. Can also handle multimodal inputs with vision-capable models.

```APIDOC
## POST /v1/chat/completions

### Description
Generates a completion for a chat conversation. Supports various parameters for controlling model behavior, sampling, and output format. Can also handle multimodal inputs with vision-capable models.

### Method
POST

### Endpoint
/v1/chat/completions

### Parameters
#### Request Body
- **model** (string) - Required - Model name, e.g. `gpt-4o`, `claude-3-5-sonnet`, `gemini-2.0-flash`
- **messages** (array) - Required - Array of conversation messages (at least one)
- **stream** (boolean) - Optional - Whether to use streaming output (SSE)
- **temperature** (number) - Optional - Sampling temperature, range 0–2
- **top_p** (number) - Optional - Nucleus sampling parameter
- **max_tokens** (integer) - Optional - Maximum number of tokens to generate
- **max_completion_tokens** (integer) - Optional - Maximum completion tokens (supported by some models)
- **frequency_penalty** (number) - Optional - Frequency penalty, range -2 to 2
- **presence_penalty** (number) - Optional - Presence penalty, range -2 to 2
- **stop** (string | string[]) - Optional - Stop sequences
- **tools** (array) - Optional - Tool/function definition list
- **tool_choice** (string | object) - Optional - Tool calling strategy: `"none"` / `"auto"` / `"required"`
- **response_format** (object) - Optional - Output format: `{"type": "json_object"}` or `{"type": "json_schema", ...}`
- **n** (integer) - Optional - Number of completions to generate
- **seed** (integer) - Optional - Random seed (for reproducible results)
- **user** (string) - Optional - End-user identifier

### Message Format (`messages`)
```json
[
  {
    "role": "system",
    "content": "You are a helpful assistant."
  },
  {
    "role": "user",
    "content": "What is the capital of France?"
  },
  {
    "role": "assistant",
    "content": "The capital of France is Paris."
  },
  {
    "role": "user",
    "content": "Thanks!"
  }
]
```

**Supported Roles:**
- **system**: System instructions to define AI behavior
- **user**: User messages
- **assistant**: AI replies (include history for multi-turn conversations)
- **tool**: Tool call return results

### Multimodal Support (Vision)
Supports image understanding (requires Vision-capable models such as `gpt-4o`, `gemini-2.0-flash`):
```json
{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": [
        { "type": "text", "text": "What is in this image?" },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://example.com/image.jpg",
            "detail": "auto"
          }
        }
      ]
    }
  ]
}
```
```

--------------------------------

### Create Chat Completion

Source: https://docs.tokenware.ai/docs/api-reference

Generate a chat completion using a specified model. Supports streaming responses. Ensure your API Key is included in the Authorization header and content type is set to application/json.

```bash
curl https://open.vidau.ai/v1/chat/completions \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{ \
    "model": "gpt-4o", \
    "messages": [ \
      {"role": "user", "content": "Hello!"} \
    ] \
  }'
```

--------------------------------

### POST /v1/audio/speech

Source: https://docs.tokenware.ai/docs/api-reference

Converts text to spoken audio. This endpoint is compatible with the OpenAI Audio Speech API.

```APIDOC
## POST /v1/audio/speech

### Description
Convert text to spoken audio. Compatible with the OpenAI Audio Speech API.

### Method
POST

### Endpoint
/v1/audio/speech

### Parameters
#### Request Body
- **model** (string) - Yes - TTS model name (e.g. `tts-1`, `tts-1-hd`)
- **input** (string) - Yes - Text to convert to speech (max 4096 characters)
- **voice** (string) - Yes - Voice preset: `alloy`, `echo`, `fable`, `onyx`, `nova`, `shimmer`
- **response_format** (string) - No - Audio format: `mp3` (default), `opus`, `aac`, `flac`, `wav`, `pcm`
- **speed** (number) - No - Speed factor: `0.25` - `4.0` (default: `1.0`)

### Response
Binary audio stream with appropriate `Content-Type` header.

### Request Example
```bash
curl https://open.vidau.ai/v1/audio/speech \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{ \
    "model": "tts-1", \
    "input": "Hello, welcome to Vidau!", \
    "voice": "alloy" \
  }' \
  --output speech.mp3
```
```

--------------------------------

### Authenticate with API Key

Source: https://docs.tokenware.ai/docs/quick-started

Include your API Key in the Authorization header for all requests. API Keys are managed in the Vidau Console and offer security features like IP allowlisting and expiration.

```text
Authorization: Bearer sk-xxxxxxxxxxxxxxxxxxxxxxxx
```

--------------------------------

### POST /v1/images/generations

Source: https://docs.tokenware.ai/docs/api-reference

Generates images from text prompts. This API is compatible with the OpenAI Images API.

```APIDOC
## POST /v1/images/generations

### Description
Generate images from text prompts. Compatible with the OpenAI Images API.

### Method
POST

### Endpoint
/v1/images/generations

### Parameters
#### Request Body
- **model** (string) - Required - Image model name (e.g. `dall-e-3`, `gemini-2.0-flash-exp`)
- **prompt** (string) - Required - Text description of the desired image.
- **n** (integer) - Optional - Number of images to generate (default: `1`).
- **size** (string) - Optional - Image size. Supported values: `"256x256"`, `"512x512"`, `"1024x1024"`, `"1024x1792"`, `"1792x1024"`.
- **quality** (string) - Optional - Image quality, either `"standard"` or `"hd"`.
- **response_format** (string) - Optional - Response format, either `"url"` (default) or `"b64_json"`.
- **style** (string) - Optional - Image style, either `"natural"` or `"vivid"`.

### Request Example
```bash
curl https://open.vidau.ai/v1/images/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d 
    {
    "model": "dall-e-3",
    "prompt": "A cute baby sea otter floating on its back",
    "n": 1,
    "size": "1024x1024"
  }
```

### Response
#### Success Response (200)
- **created** (integer) - Timestamp of image creation.
- **data** (array) - An array of image objects.
  - **url** (string) - The URL of the generated image (if `response_format` is `"url"`).
  - **b64_json** (string) - The base64 encoded image (if `response_format` is `"b64_json"`).
  - **revised_prompt** (string) - The revised prompt used for generation (optional).

#### Response Example
```json
{
  "created": 1714200000,
  "data": [
    {
      "url": "https://...",
      "revised_prompt": "A detailed description..."
    }
  ]
}
```
```

--------------------------------

### POST /v1/audio/transcriptions

Source: https://docs.tokenware.ai/docs/api-reference

Transcribes audio to text. This endpoint is compatible with the OpenAI Audio Transcriptions API.

```APIDOC
## POST /v1/audio/transcriptions

### Description
Transcribe audio to text. Compatible with the OpenAI Audio Transcriptions API.

### Method
POST

### Endpoint
/v1/audio/transcriptions

### Parameters
#### Request Body (`multipart/form-data`)
- **file** (file) - Yes - Audio file (mp3, mp4, mpeg, mpga, m4a, wav, webm)
- **model** (string) - Yes - STT model name (e.g. `whisper-1`)
- **language** (string) - No - Language code (ISO-639-1, e.g. `en`, `zh`)
- **prompt** (string) - No - Hint text to guide transcription
- **response_format** (string) - No - `json` (default), `text`, `srt`, `verbose_json`, `vtt`
- **temperature** (number) - No - Sampling temperature (0-1)

### Response (JSON format)
#### Success Response
- **text** (string) - The transcribed text.

### Response Example
```json
{
  "text": "Hello, this is a transcription test."
}
```

### Request Example
```bash
curl https://open.vidau.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer sk-your-api-key" \
  -F file=@audio.mp3 \
  -F model=whisper-1 \
  -F language=en
```
```

--------------------------------

### Streaming Response Format (SSE)

Source: https://docs.tokenware.ai/docs/quick-started

When `stream: true` is enabled, responses are delivered incrementally as Server-Sent Events (SSE). Each event is prefixed with 'data:' and the stream concludes with 'data: [DONE]'.

```text
data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":"!"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":10,"completion_tokens":2,"total_tokens":12}}

data: [DONE]
```

--------------------------------

### Video Generation Task Status (Failed)

Source: https://docs.tokenware.ai/docs/api-reference

Check the status of a video generation task that has failed. This response includes an error message detailing the reason for failure.

```json
{
  "id": "vgen_abc123-def456",
  "status": "failed",
  "model": "veo-3",
  "created_at": 1714200000,
  "error": {
    "message": "Video generation timeout"
  }
}
```

--------------------------------

### Convert Text to Speech (TTS)

Source: https://docs.tokenware.ai/docs/api-reference

Convert text into spoken audio using compatible TTS models. Specify the model, input text, and desired voice. The response is a binary audio stream.

```bash
curl https://open.vidau.ai/v1/audio/speech \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "Hello, welcome to Vidau!",
    "voice": "alloy"
  }' \
  --output speech.mp3
```

--------------------------------

### Generate Images from Text

Source: https://docs.tokenware.ai/docs/api-reference

Generate images based on a text prompt. This API is compatible with OpenAI's Image generation endpoints. You can specify the model, prompt, number of images, size, quality, response format, and style.

```bash
curl https://open.vidau.ai/v1/images/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{ \
    "model": "dall-e-3", \
    "prompt": "A cute baby sea otter wearing a tiny hat", \
    "n": 1, \
    "size": "1024x1024" \
  }'
```

--------------------------------

### Video Generation Task Status (Completed)

Source: https://docs.tokenware.ai/docs/api-reference

Retrieve the status of a completed video generation task. This response includes details about the generated video, such as its URL, duration, and resolution.

```json
{
  "id": "vgen_abc123-def456",
  "status": "completed",
  "model": "veo-3",
  "created_at": 1714200000,
  "completed_at": 1714200120,
  "video": {
    "url": "https://static.vidau.ai/generated/task_vgen_abc123/video.mp4",
    "duration_seconds": 8,
    "resolution": "720p"
  }
}
```

--------------------------------

### Generate Embeddings

Source: https://docs.tokenware.ai/docs/api-reference

Create vector embeddings for input text. This endpoint is compatible with the OpenAI Embeddings API. Specify the model and input text, and include your API Key for authentication.

```bash
curl https://open.vidau.ai/v1/embeddings \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{ \
    "model": "text-embedding-3-small", \
    "input": "The food was delicious" \
  }'
```

--------------------------------

### Streaming Response (SSE)

Source: https://docs.tokenware.ai/docs/quick-started

When `stream: true`, responses are returned incrementally via Server-Sent Events (SSE). Each event is prefixed with `data: ` and the stream ends with `data: [DONE]`.

```APIDOC
## Streaming Response (SSE)

When `stream: true`, responses are returned incrementally via Server-Sent Events (SSE). Each event is prefixed with `data: ` and the stream ends with `data: [DONE]`.

### Response Example
```
data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":"!"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","created":1714000000,"model":"gpt-4o","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":10,"completion_tokens":2,"total_tokens":12}}

data: [DONE]
```
```

--------------------------------

### Chat Completions API Endpoint

Source: https://docs.tokenware.ai/docs/quick-started

This section details the Chat Completions API endpoint, including its method, URL, authentication requirements, and response format. It is fully compatible with the OpenAI Chat Completions API.

```APIDOC
## POST /v1/chat/completions

### Description
Provides an OpenAI-compatible Chat Completions API that serves as a unified gateway, supporting multiple upstream LLM providers.

### Method
POST

### Endpoint
https://open.vidau.ai/v1/chat/completions

### Authentication
Bearer Token (API Key) in the `Authorization` header.

### Response Format
JSON / SSE (Server-Sent Events streaming)
```

--------------------------------

### POST /v1/embeddings

Source: https://docs.tokenware.ai/docs/api-reference

Generates vector embeddings for input text. This API is compatible with the OpenAI Embeddings API.

```APIDOC
## POST /v1/embeddings

### Description
Generate vector embeddings for input text. Compatible with the OpenAI Embeddings API.

### Method
POST

### Endpoint
/v1/embeddings

### Parameters
#### Request Body
- **model** (string) - Required - Embedding model name (e.g. `text-embedding-3-small`)
- **input** (string | string[]) - Required - Text to embed. Can be a single string or array of strings.
- **encoding_format** (string) - Optional - Encoding format, either `"float"` (default) or `"base64"`.
- **dimensions** (integer) - Optional - Output dimensions (model-dependent).

### Request Example
```bash
curl https://open.vidau.ai/v1/embeddings \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d 
    {
    "model": "text-embedding-3-small",
    "input": "The food was delicious"
  }
```

### Response
#### Success Response (200)
- **object** (string) - Type of the response, "list".
- **data** (array) - An array of embedding objects.
  - **object** (string) - The type of the object, "embedding".
  - **embedding** (array) - The generated embedding vector.
  - **index** (integer) - The index corresponding to the input text.
- **model** (string) - The embedding model used.
- **usage** (object) - Usage statistics for the request.
  - **prompt_tokens** (integer) - Number of tokens in the prompt.
  - **total_tokens** (integer) - Total tokens used.

#### Response Example
```json
{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [0.0023, -0.0091, 0.0152, ...],
      "index": 0
    }
  ],
  "model": "text-embedding-3-small",
  "usage": {
    "prompt_tokens": 5,
    "total_tokens": 5
  }
}
```
```

--------------------------------

### Multimodal Chat Completion Request

Source: https://docs.tokenware.ai/docs/quick-started

Send multimodal requests by including image URLs within the content array for Vision-capable models. The 'detail' parameter can be set to 'auto', 'low', or 'high'.

```json
{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": [
        { "type": "text", "text": "What is in this image?" },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://example.com/image.jpg",
            "detail": "auto"
          }
        }
      ]
    }
  ]
}
```

--------------------------------

### Common Request Headers

Source: https://docs.tokenware.ai/docs/api-reference

Details on the common headers required for making requests to the Vidau API.

```APIDOC
## Common Headers

### Request Headers

Header| Required| Description  
---|---|---  
`Authorization`| Yes| `Bearer sk-your-api-key`  
`Content-Type`| Yes| `application/json` (or `multipart/form-data` for file uploads)
```

--------------------------------

### Video Generation Task Status (Processing)

Source: https://docs.tokenware.ai/docs/api-reference

Poll the status of an ongoing video generation task using its ID. This response indicates the task is still being processed.

```json
{
  "id": "vgen_abc123-def456",
  "status": "processing",
  "model": "veo-3",
  "created_at": 1714200000
}
```

--------------------------------

### Common Response Headers

Source: https://docs.tokenware.ai/docs/api-reference

Details on the common headers returned in responses from the Vidau API.

```APIDOC
### Response Headers

Header| Description  
---|---  
`X-Request-Id`| Unique request identifier for debugging
```

--------------------------------

### Response Headers

Source: https://docs.tokenware.ai/docs/quick-started

Common headers returned with API responses, useful for tracking and debugging.

```APIDOC
## Response Headers

Common headers returned with API responses, useful for tracking and debugging.

| Header      | Description                                  |
|-------------|----------------------------------------------|
| `X-Request-Id` | Unique request identifier for troubleshooting |

```

--------------------------------

### Chat Completion Message Format

Source: https://docs.tokenware.ai/docs/quick-started

Use this JSON array format for messages in chat completion requests. Include system, user, and assistant roles to maintain conversation history. The 'tool' role is for tool call results.

```json
[
  {
    "role": "system",
    "content": "You are a helpful assistant."
  },
  {
    "role": "user",
    "content": "What is the capital of France?"
  },
  {
    "role": "assistant",
    "content": "The capital of France is Paris."
  },
  {
    "role": "user",
    "content": "Thanks!"
  }
]
```

--------------------------------

### Standard OpenAI API Error Response Format

Source: https://docs.tokenware.ai/docs/quick-started

Illustrates the JSON structure for error responses from the API. This format helps in parsing and handling different types of API errors.

```json
{
  "error": {
    "message": "Error description",
    "type": "error_type",
    "code": "error_code",
    "param": null
  }
}
```

--------------------------------

### Rerank Documents by Query

Source: https://docs.tokenware.ai/docs/api-reference

Rerank a list of documents based on their relevance to a given query. Specify the model, query, and documents to rerank. The `top_n` parameter limits the number of results returned.

```bash
curl https://vidau.open.ai/v1/rerank \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "rerank-v3",
    "query": "What is machine learning?",
    "documents": [
      "Machine learning is a subset of AI...",
      "The weather forecast for tomorrow...",
      "Deep learning uses neural networks..."
    ],
    "top_n": 2
  }'
```

--------------------------------

### Transcribe Audio to Text (STT)

Source: https://docs.tokenware.ai/docs/api-reference

Transcribe audio files into text using the Whisper model. This endpoint supports various audio formats and allows specifying the language for transcription. The response format can be JSON, text, SRT, verbose JSON, or VTT.

```bash
curl https://open.vidau.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer sk-your-api-key" \
  -F file=@audio.mp3 \
  -F model=whisper-1 \
  -F language=en
```

--------------------------------

### Moderations

Source: https://docs.tokenware.ai/docs/api-reference

Classifies text for potentially harmful content. This endpoint is compatible with the OpenAI Moderations API.

```APIDOC
## POST /v1/moderations

### Description
Classify text for potentially harmful content. Compatible with the OpenAI Moderations API.

### Method
POST

### Endpoint
/v1/moderations

### Parameters
#### Request Body
- **model** (string) - No - Moderation model name (default: `omni-moderation-latest`)
- **input** (string | string[]) - Yes - Text to classify

### Response
#### Success Response (200)
- **id** (string) - Unique ID for the moderation request.
- **model** (string) - The moderation model used.
- **results** (array) - An array of results, one for each input.
  - **flagged** (boolean) - Whether the content was flagged.
  - **categories** (object) - Flags for specific content categories.
  - **category_scores** (object) - Confidence scores for each category.

### Request Example
```json
{
  "input": "I want to help people learn programming"
}
```

### Response Example
```json
{
  "id": "modr-abc123",
  "model": "omni-moderation-latest",
  "results": [
    {
      "flagged": false,
      "categories": {
        "sexual": false,
        "hate": false,
        "harassment": false,
        "self-harm": false,
        "violence": false
      },
      "category_scores": {
        "sexual": 0.0001,
        "hate": 0.0002,
        "harassment": 0.0003,
        "self-harm": 0.0001,
        "violence": 0.0002
      }
    }
  ]
}
```
```

--------------------------------

### Verify Webhook Signature

Source: https://docs.tokenware.ai/docs/api-reference

Use this function to verify the HMAC-SHA256 signature of incoming webhooks. Ensure your webhook secret is kept secure.

```javascript
const crypto = require("crypto");

function verifyWebhook(body, signature, secret) {
  const expected = "sha256=" +
    crypto.createHmac("sha256", secret).update(body).digest("hex");
  return signature === expected;
}

// In your webhook handler:
const signature = req.headers["x-webhook-signature"];
const isValid = verifyWebhook(req.body, signature, "your-hmac-secret");
```

--------------------------------

### Non-Streaming Response

Source: https://docs.tokenware.ai/docs/quick-started

This is the standard JSON response format for a single, complete API reply.

```APIDOC
## Non-Streaming Response

This is the standard JSON response format for a single, complete API reply.

### Response Example
```json
{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1714000000,
  "model": "gpt-4o",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The capital of France is Paris."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 20,
    "completion_tokens": 8,
    "total_tokens": 28
  }
}
```
```

--------------------------------

### Error Response Format

Source: https://docs.tokenware.ai/docs/api-reference

All API endpoints return errors in a consistent JSON format, including a message, type, and code.

```json
{
  "error": {
    "message": "Error description",
    "type": "error_type",
    "code": "error_code"
  }
}
```

--------------------------------

### Webhook Signature Verification

Source: https://docs.tokenware.ai/docs/api-reference

Verifies the HMAC-SHA256 signature of incoming webhook payloads to ensure authenticity and integrity.

```APIDOC
## Webhook Signature Verification

If `webhook_secret` is provided, the webhook payload is signed with HMAC-SHA256.

### Code Example

```javascript
const crypto = require("crypto");

function verifyWebhook(body, signature, secret) {
  const expected = "sha256=" +
    crypto.createHmac("sha256", secret).update(body).digest("hex");
  return signature === expected;
}

// In your webhook handler:
const signature = req.headers["x-webhook-signature"];
const isValid = verifyWebhook(req.body, signature, "your-hmac-secret");
```

### Parameters

- **body** (string) - The raw request body of the webhook.
- **signature** (string) - The `x-webhook-signature` header value.
- **secret** (string) - Your webhook secret key.

### Response

- **isValid** (boolean) - `true` if the signature is valid, `false` otherwise.
```
Tokens:
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