# Tripo P2 Text to 3D API

> PBR، کواڈ میش، منتخب ٹیکسچر ورژن اور منفی پرامپٹ کے ساتھ متن سے 3D، P2 کی متنی قسم

1024 حروف تک کے ایک پرامپٹ سے 3D ماڈل تیار کرتا ہے، جس میں 255 حروف تک کا `negative_prompt` شامل ہے۔ میشز 50,000 فیسز تک جاتے ہیں، یا جب `quad` آن ہو تو 25,000 تک۔ ٹیکسچر کوالٹی فاسٹ سے ایکسٹریم تک ہوتی ہے، جس میں قابل انتخاب `texture_version`، اختیاری PBR، ڈی لائٹنگ اور UV ایکسپورٹ شامل ہیں۔ امیج اسٹیپ، جیومیٹری اور ٹیکسچرز کے لیے سیڈز دستیاب ہیں۔

- Model id: `tripo3d/p2/text-to-3d`
- Made by: Tripo
- Category: Text to 3D
- Output: 3d
- Price per run: from $1.00 / run (cheapest run $1.00 (1000 API credits))
- Run: `POST https://api.doitong.com/v1/run/tripo3d/p2/text-to-3d`
- Quote: `POST https://api.doitong.com/v1/quote/tripo3d/p2/text-to-3d`
- Docs page: https://doitong.com/ur/developers/models/tripo3d/p2/text-to-3d

## Pricing

Price: **from $1.00 / 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.

Price by tier:

- base rate: $1.00 / run
- fast: $1.10 / run
- standard: $1.10 / run
- detailed: $1.20 / run
- extreme: $1.30 / run

The full example input below costs $1.10 = 1100 API credits (1 run × $1.10 (standard)).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/tripo3d/p2/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 |  | 1 – 1024 characters | مطلوبہ 3D آبجیکٹ کی متنی وضاحت، زیادہ سے زیادہ 1024 حروف۔ |
| `negative_prompt` |  | string \| null | no |  | ≤ 255 characters | ان خصوصیات کی وضاحت جنہیں تخلیق شدہ ماڈل سے خارج کرنا چاہیے۔ |
| `image_seed` |  | integer \| null | no |  |  | اندرونی text-to-image مرحلے کے دوران استعمال ہونے والا seed۔ |
| `model_seed` |  | integer \| null | no |  |  | جیومیٹری کی تخلیق کو قابلِ تکرار بنانے کے لیے استعمال ہونے والا seed۔ |
| `face_limit` |  | integer \| null | no |  | 48 – 50,000 | mesh faces کی بالائی حد؛ quad topology کے لیے الگ حد 25,000 ہے۔ |
| `texture` |  | boolean | no | `true` |  | کنٹرول کرتا ہے کہ ماڈل کو تخلیق کردہ textures موصول ہوں یا نہیں۔ |
| `pbr` |  | boolean | no | `true` |  | PBR مواد کے maps کی تخلیق کو کنٹرول کرتا ہے۔ PBR فعال کرنے سے ٹیکسچرز بھی فعال ہو جاتے ہیں۔ |
| `texture_seed` |  | integer \| null | no |  |  | ٹیکسچر کی تخلیق کو قابلِ تکرار بنانے کے لیے استعمال ہونے والا seed۔ |
| `texture_quality` |  | enum (string) | no | `standard` | `fast`, `standard`, `detailed`, `extreme` | ٹیکسچرز کے معیار کی ترتیب۔ |
| `texture_version` |  | enum (string) \| null | no |  | `v3.5-20260815`, `v3.0-20250812`, `v2.5-20250123` | ٹیکسچر modeling کے لیے استعمال ہونے والا ورژن۔ تیز معیار کے لیے v3.5-20260815 منتخب کریں؛ اس معیار کے لیے دیگر ورژنز معاونت یافتہ نہیں۔ |
| `delight` |  | boolean | no | `true` |  | v3.5-20260815 کے ذریعے texturing سے پہلے baked-in lighting ہٹانا۔ |
| `auto_size` |  | boolean | no | `false` |  | ماڈل کو میٹر میں ناپی گئی حقیقی دنیا کی پیمائش دینے کے لیے خودکار scaling۔ |
| `export_uv` |  | boolean | no | `true` |  | یہ کنٹرول کرتا ہے کہ ماڈل کو تخلیق شدہ UV coordinates ملیں یا نہیں۔ |
| `export_orientation` |  | enum (string) \| null | no |  | `+x`, `-x`, `-y`, `+y` | مخصوص ہونے کی صورت میں ماڈل export کے لیے forward-axis کی ترتیب۔ |
| `quad` |  | boolean | no | `false` |  | مثلثوں کے بجائے quads استعمال کرنے والی mesh topology۔ |
| `enable_safety_checker` |  | boolean | no | `true` |  | false سیٹ کر کے اسکریننگ نرم کی جا سکتی ہے، بشرطیکہ کال کرنے والا مجاز ہو۔ |

## 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.com/v1/run/tripo3d/p2/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.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/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/p2/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.com/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/p2/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.com/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/p2/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/p2/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": 1100,
    "usd": "1.10",
    "charged": 1100,
    "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `model_mesh` | object {url, content_type, file_name, file_size} | تخلیق شدہ 3D ماڈل پر مشتمل GLB یا FBX فائل؛ فارمیٹ Tripo کے تیار کردہ ڈیٹا سے متعین ہوتا ہے۔ |
| `model_urls` | object {glb, fbx, base_model, pbr_model} | 3D ماڈل کے متبادل ورژنز کی طرف اشارہ کرنے والے URLs۔ |
| `rendered_image` | object {url, content_type, file_name, file_size} \| null | تخلیق شدہ 3D ماڈل کا رینڈر شدہ پیش منظر۔ |
| `task_id` | string \| null | تخلیق شدہ ماڈل کی شناخت کرنے والی قابلِ دوبارہ استعمال Tripo task ID، جو دوبارہ ماڈل اپ لوڈ کیے بغیر rig یا rig-check آپریشنز کی اجازت دیتی ہے۔ |

## Related models

- [Tripo P2 Image to 3D](https://doitong.com/developers/models/tripo3d/p2/image-to-3d.md) (`tripo3d/p2/image-to-3d`): from $1.00 / run
- [Tripo H3.1 Text to 3D](https://doitong.com/developers/models/tripo3d/h3.1/text-to-3d.md) (`tripo3d/h3.1/text-to-3d`): from $0.10 / 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
- [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
- [Hunyuan3d V3 · Text to 3D](https://doitong.com/developers/models/hunyuan3d-v3/text-to-3d.md) (`hunyuan3d-v3/text-to-3d`): from $0.225 / run

## Links

- HTML page: https://doitong.com/developers/models/tripo3d/p2/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/p2/text-to-3d
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/tripo3d/p2/text-to-3d