# Luma Ray 3.2 Text to Video API

> Ray 3.2 टेक्स्ट-टू-वीडियो, जिसमें 5s या 10s की क्लिप्स, छह आस्पेक्ट रेशियो, लूपिंग और EXR एक्सपोर्ट के साथ वैकल्पिक HDR है

अधिकतम 6000 वर्णों वाले `prompt` से वीडियो बनाता है। `aspect_ratio` 3:4 से 21:9 तक, रिज़ॉल्यूशन 540p, 720p या 1080p और `duration` 5s या 10s होता है। `loop` केवल 5s standard-range क्लिप के लिए काम करता है, जबकि `hdr` के लिए 720p या 1080p आवश्यक है और यह 10s तथा loop को बाहर रखता है। HDR चालू होने पर `exr_export` एक EXR फ़ाइल जोड़ता है।

- Model id: `luma/agent/ray/v3.2/text-to-video`
- Made by: Luma AI
- Category: Text to Video
- Output: video
- Price: from $0.10 / second (5 s ≈ $0.50) (cheapest run $0.50 (500 API credits))
- Run: `POST https://api.doitong.ru/v1/run/luma/agent/ray/v3.2/text-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/luma/agent/ray/v3.2/text-to-video`
- Docs page: https://doitong.com/hi/developers/models/luma/agent/ray/v3.2/text-to-video

## Pricing

Price: **from $0.10 / second (5 s ≈ $0.50)** (the lowest tier; the quote prices your exact input). Billed per second of output (`duration`, default 10).

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `exr_export` = true and `hdr` = true and `resolution` = 1080p: $1.20 (1200 API credits) / second
- When `exr_export` = true and `hdr` = true: $0.60 (600 API credits) / second
- When `hdr` = true and `resolution` = 1080p: $0.80 (800 API credits) / second
- When `hdr` = true: $0.40 (400 API credits) / second
- When `resolution` = 1080p: $0.40 (400 API credits) / second
- When `resolution` = 720p: $0.20 (200 API credits) / second

The full example input below costs $0.50 = 500 API credits (5 s × 100 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/luma/agent/ray/v3.2/text-to-video` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | 1 – 6000 characters | बनाए जाने वाले वीडियो का text description। |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `3:4`, `4:3`, `1:1`, `9:16`, `16:9`, `21:9` | परिणामी वीडियो का आस्पेक्ट रेशियो। |
| `resolution` |  | enum (string) | no | `540p` | `540p`, `720p`, `1080p` | आउटपुट वीडियो का रिज़ॉल्यूशन। |
| `duration` |  | enum (string) | no | `5s` | `5s`, `10s` | बनाए जा रहे वीडियो की लंबाई। |
| `loop` |  | boolean | no | `false` |  | Seamless-loop विकल्प, जिसके लिए ये सभी आवश्यक हैं: 5s duration, standard dynamic range और no end फ़्रेम। |
| `hdr` |  | boolean | no | `false` |  | 720p या 1080p पर MP4 आउटपुट के लिए HDR encoding, जो केवल HDR पहुँच वाले accounts के लिए उपलब्ध है। HDR का उपयोग 10s duration या looping के साथ नहीं किया जा सकता। |
| `exr_export` |  | boolean | no | `false` |  | MP4 के साथ अतिरिक्त EXR export, जो केवल HDR पहुँच और hdr=true दोनों के साथ उपलब्ध है। |
| `enable_safety_checker` |  | boolean | no | `true` |  | यदि कॉलर अधिकृत है, तो false सेट करके स्क्रीनिंग में ढील दी जा सकती है। |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/luma/agent/ray/v3.2/text-to-video?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/luma/agent/ray/v3.2/text-to-video?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/luma/agent/ray/v3.2/text-to-video", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.ru/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "luma/agent/ray/v3.2/text-to-video",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "luma/agent/ray/v3.2/text-to-video",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 500,
    "usd": "0.50",
    "charged": 500,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "exr_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | मॉडल द्वारा बनाया गया वीडियो। |
| `exr_file` | object {url, content_type, file_name, file_size} \| null | Luma के exports के रूप में EXR sidecar: या तो एक EXR फ़ाइल या ZIP archive। यह exr_export के true होने पर बनाया जाता है। |

## Related models

- [Luma Ray 3.2 Image to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/image-to-video.md) (`luma/agent/ray/v3.2/image-to-video`): from $0.03 / second
- [Luma Ray 3.2 Reframe](https://doitong.com/developers/models/luma/agent/ray/v3.2/reframe.md) (`luma/agent/ray/v3.2/reframe`): from $0.06 / second of input video
- [Luma Ray 3.2 Video to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/video-to-video.md) (`luma/agent/ray/v3.2/video-to-video`): from $0.144 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second

## Links

- HTML page: https://doitong.com/developers/models/luma/agent/ray/v3.2/text-to-video
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=luma/agent/ray/v3.2/text-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/luma/agent/ray/v3.2/text-to-video