Tripo H3.1 Text to 3D
集成
模型 id
tripo3d/h3.1/text-to-3d
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/tripo3d/h3.1/text-to-3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
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"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/zh/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"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"
}
}
通过 Doitong API 调用 Tripo H3.1 Text to 3D 模型(tripo3d/h3.1/text-to-3d)。智能体文档:https://doitong.com/zh/developers/models/tripo3d/h3.1/text-to-3d.md
POST https://api.doitong.ru/v1/run/tripo3d/h3.1/text-to-3d?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
如果响应状态为 "queued" 或 "running",请轮询 GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20,直到状态变为 "succeeded";文件位于 outputs[].url。使用相同请求体 POST https://api.doitong.ru/v1/quote/tripo3d/h3.1/text-to-3d,可在运行前返回确切价格。
与示例类似的文件: $0.20 200 API 积分 · ≈ ₽21.52 运行前会测量你的文件 在此页面运行
你的新 API 密钥。 它仅在此时显示,并且已填入下方的代码和 API 密钥字段中。请妥善保密:切勿将其放入在浏览器中运行的代码。
构建请求
控件根据模型架构生成。更改控件时,代码和价格会同步更新。
POST
/run/tripo3d/h3.1/text-to-3d?wait=20
报价 → $0.20
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/tripo3d/h3.1/text-to-3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
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"])
{
"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
}
}
}
关于 Tripo H3.1 Text to 3D
根据最长 1024 个字符的文本描述构建 3D 模型,并可选提供用于排除特征的 `negative_prompt`。`face_limit` 接受 1,000 到 2,000,000 个面。`geometry_quality` 和 `texture_quality` 均可设置为 standard 或 detailed。选项包括 PBR 材质、四边形拓扑、自动缩放到真实世界尺寸,以及分别用于几何体、文本到图像步骤和纹理的独立种子。
参数
名称类型
默认值允许值
描述
prompt必填
类型string
≤ 1,024 个字符
所需 3D 对象的文字描述,最多 1024 个字符。
negative_prompt可选
类型string | null
≤ 1,024 个字符
应从生成模型中排除的特征描述。
face_limit可选
类型integer | null
1,000 – 2,000,000
网格生成的明确面数目标;提供此值时会覆盖模型的自适应面数选择。
texture可选
类型boolean
默认值true
控制模型是否接收生成的纹理。
pbr可选
类型boolean
默认值true
启用 PBR 材质(基于物理的渲染);设为 true 时也会启用纹理生成。
model_seed可选
类型integer | null
用于使几何体生成可复现的种子。
image_seed可选
类型integer | null
文本到图像阶段使用的种子。
texture_seed可选
类型integer | null
用于使纹理生成可复现的种子。
texture_quality可选
类型enum
默认值standard
standarddetailed
纹理质量设置;选择 'detailed' 会提高纹理分辨率。
geometry_quality可选
类型enum
默认值standard
standarddetailed
几何体的质量设置。
auto_size可选
类型boolean
默认值false
自动缩放,使模型获得以米为单位测量的真实世界尺寸。
quad可选
类型boolean
默认值false
启用四边形拓扑,在三角形面和 4 边四边形之间选择。对于四边形结果,只要 Tripo 以 FBX 字节提供数据,就会返回 FBX 文件。
enable_safety_checker可选
类型boolean
默认值true
调用方获得授权后,可将其设置为 false 以放宽审核。
必填
输出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"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"
}
}
你的文件,由你选择每个 outputs[].url 都是存储中的副本:可永久保存(按 GB-月付费),也可免费保存 7 天,由账户设置或 ?storage= 决定。
每个模型的结构相同图像、视频和音频均包含 type、url、content_type、width、height 和 duration。output 是模型自身的结果对象。
输出字段
- model_mesh
- object {url, content_type, file_name, file_size}包含生成的 3D 模型的 GLB 或 FBX 文件,格式取决于 Tripo 生成的内容。
- model_urls
- object {glb, fbx, base_model, pbr_model}指向 3D 模型其他版本的 URL。
- rendered_image
- object {url, content_type, file_name, file_size} | null显示生成的 3D 模型的渲染预览。
- task_id
- string | null用于标识生成模型的可复用 Tripo 任务 ID,可在不再次上传模型的情况下执行 rig 或 rig-check 操作。
其他 Tripo H3.1 变体
更多模型:文本转 3D
对于 AI 代理:此页面的 Markdown 版本位于 https://doitong.com/zh/developers/models/tripo3d/h3.1/text-to-3d.md. 所有模型和指南: https://doitong.com/developers/llms.txt