# Tripo H3.1 Text to 3D API

> مولد مش تبدیل متن به سه‌بعدی با پرامپت منفی، سطوح جداگانه کیفیت هندسه و بافت و سقف بسیار بالای وجه

از توضیح متنی حداکثر 1024 نویسه‌ای مدل سه‌بعدی می‌سازد و `negative_prompt` اختیاری برای ویژگی‌های ناخواسته دارد. `face_limit` از 1,000 تا 2,000,000 وجه را می‌پذیرد. `geometry_quality` و `texture_quality` هرکدام می‌توانند standard یا detailed باشند. گزینه‌ها شامل مواد PBR، توپولوژی quad، مقیاس‌دهی خودکار به اندازه واقعی و seedهای جداگانه برای هندسه، مرحله text-to-image و بافت هستند.

- Model id: `tripo3d/h3.1/text-to-3d`
- Made by: Tripo
- Category: Text to 3D
- Output: 3d
- Price per run: from $0.10 / run (cheapest run $0.10 (100 API credits))
- Run: `POST https://api.doitong.ru/v1/run/tripo3d/h3.1/text-to-3d`
- Quote: `POST https://api.doitong.ru/v1/quote/tripo3d/h3.1/text-to-3d`
- Docs page: https://doitong.com/fa/developers/models/tripo3d/h3.1/text-to-3d

## Pricing

Price: **from $0.10 / run** (the lowest tier; the quote prices your exact input). Price per run: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.20 = 200 API credits (1 run × $0.20).

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/tripo3d/h3.1/text-to-3d` 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 |  | ≤ 1024 characters | توضیح متنی شیء سه‌بعدی موردنظر، حداکثر 1024 نویسه. |
| `negative_prompt` |  | string \| null | no |  | ≤ 1024 characters | توضیح ویژگی‌هایی که باید از مدل تولیدشده حذف شوند. |
| `face_limit` |  | integer \| null | no |  | 1,000 – 2,000,000 | هدف صریح تعداد وجه برای تولید مش که در صورت ارائه، انتخاب تطبیقی تعداد توسط مدل را لغو می‌کند. |
| `texture` |  | boolean | no | `true` |  | مشخص می‌کند مدل بافت‌های تولیدشده را دریافت کند یا نه. |
| `pbr` |  | boolean | no | `true` |  | مواد PBR (رندر مبتنی بر فیزیک) را فعال می‌کند؛ در صورت true، تولید بافت نیز فعال می‌شود. |
| `model_seed` |  | integer \| null | no |  |  | Seed مورد استفاده برای بازتولیدپذیر کردن تولید هندسه. |
| `image_seed` |  | integer \| null | no |  |  | Seed مورد استفاده در مرحله text-to-image. |
| `texture_seed` |  | integer \| null | no |  |  | Seed مورد استفاده برای بازتولیدپذیر کردن تولید بافت. |
| `texture_quality` |  | enum (string) | no | `standard` | `standard`, `detailed` | تنظیم کیفیت بافت؛ انتخاب 'detailed' وضوح بافت را افزایش می‌دهد. |
| `geometry_quality` |  | enum (string) | no | `standard` | `standard`, `detailed` | تنظیم کیفیت هندسه. |
| `auto_size` |  | boolean | no | `false` |  | مقیاس‌بندی خودکار برای دادن ابعاد واقعی برحسب متر به مدل. |
| `quad` |  | boolean | no | `false` |  | با فعال‌کردن توپولوژی چهارضلعی، بین وجه‌های مثلثی و چهارضلعی‌های 4 ضلعی انتخاب کنید. برای خروجی چهارضلعی، هرگاه Tripo داده را به‌صورت بایت‌های FBX ارائه کند، فایل FBX برگردانده می‌شود. |
| `enable_safety_checker` |  | boolean | no | `true` |  | با تنظیم false، در صورت مجاز بودن فراخواننده، می‌توان بررسی را آسان‌گیرانه‌تر کرد. |

## 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/tripo3d/h3.1/text-to-3d?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/tripo3d/h3.1/text-to-3d?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/tripo3d/h3.1/text-to-3d", 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": "tripo3d/h3.1/text-to-3d",
      "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": "tripo3d/h3.1/text-to-3d",
  "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": 200,
    "usd": "0.20",
    "charged": 200,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "model_mesh": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "model_urls": {
      "glb": {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200
      },
      "fbx": {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200
      },
      "base_model": {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200
      },
      "pbr_model": {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200
      }
    },
    "rendered_image": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "task_id": "string"
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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 |
|---|---|---|
| `model_mesh` | object {url, content_type, file_name, file_size} | فایل GLB یا FBX شامل مدل سه‌بعدی تولیدشده؛ قالب بر اساس خروجی Tripo تعیین می‌شود. |
| `model_urls` | object {glb, fbx, base_model, pbr_model} | URLهای اشاره‌کننده به نسخه‌های جایگزین مدل سه‌بعدی. |
| `rendered_image` | object {url, content_type, file_name, file_size} \| null | پیش‌نمایش رندرشده از مدل سه‌بعدی تولیدشده. |
| `task_id` | string \| null | شناسه وظیفه قابل‌استفاده مجدد Tripo که مدل تولیدشده را برای rig یا rig-check مشخص می‌کند و امکان انجام این عملیات را بدون بارگذاری دوباره مدل فراهم می‌سازد. |

## Related models

- [Tripo H3.1 Image to 3D](https://doitong.com/developers/models/tripo3d/h3.1/image-to-3d.md) (`tripo3d/h3.1/image-to-3d`): from $0.20 / run
- [Tripo H3.1 Multiview to 3D](https://doitong.com/developers/models/tripo3d/h3.1/multiview-to-3d.md) (`tripo3d/h3.1/multiview-to-3d`): from $0.20 / run
- [Tripo P1 Text to 3D](https://doitong.com/developers/models/tripo3d/p1/text-to-3d.md) (`tripo3d/p1/text-to-3d`): $1.10 / run
- [Tripo P2 Text to 3D](https://doitong.com/developers/models/tripo3d/p2/text-to-3d.md) (`tripo3d/p2/text-to-3d`): from $1.00 / run
- [Hunyuan 3d](https://doitong.com/developers/models/hunyuan-3d/v3.1/rapid/text-to-3d.md) (`hunyuan-3d/v3.1/rapid/text-to-3d`): from $0.225 / request
- [Hunyuan 3D Pro Text to 3D](https://doitong.com/developers/models/hunyuan-3d/v3.1/pro/text-to-3d.md) (`hunyuan-3d/v3.1/pro/text-to-3d`): $0.375 / run
- [Hunyuan Motion \[0.46B\]](https://doitong.com/developers/models/hunyuan-motion/fast.md) (`hunyuan-motion/fast`): $0.06 / request
- [Hunyuan Motion \[1B\]](https://doitong.com/developers/models/hunyuan-motion.md) (`hunyuan-motion`): $0.08 / request

## Links

- HTML page: https://doitong.com/developers/models/tripo3d/h3.1/text-to-3d
- 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=tripo3d/h3.1/text-to-3d
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/tripo3d/h3.1/text-to-3d