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Tripo Auto Rig

Tripo auto rigging for 3D models. Bipeds, quadrupeds and other creatures, Mixamo, Unity, Unreal or VRM bone naming, and up to five preset animations. GLB or FBX out.

3d rigging
run in browser →run via APIrun with your agent
maker
tripo
category
3d
runs via
api, javascript and python sdk, belt cli, mcp
updated
2026-10-28
price
$0.01/credit (rig check free, auto rig 25 credits, retarget 10 credits/animation)

api reference

about

tripo auto rigging for 3d models. bipeds, quadrupeds and other creatures, mixamo, unity, unreal or vrm bone naming, and up to five preset animations. glb or fbx out.

get an api key

create one in settings → api keys. the examples read it from INFERENCE_API_KEY.

bash
1export INFERENCE_API_KEY="inf_your_key"

1. calling the api

install the client

nothing to install. any http client works; the examples use curl, and jq to read responses. every response wraps its result in a data field.

run and get result

send "wait": true to hold the connection until the task finishes. without it the call returns right away with the task still running.

bash
12# "wait": true holds the connection until the task finishes.3# the response is {"data": {"id", "status", "status_text", "output", ...}}4curl -X POST https://api.inference.sh/apps/run \5  -H "Authorization: Bearer $INFERENCE_API_KEY" \6  -H "Content-Type: application/json" \7  -d '{8    "app": "tripo/tripo-rig",9    "input": {10      "model": "https://example.com/file.png"11    },12    "wait": true13  }'

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks. send "stream": true and the response is a server-sent event stream that ends when the task does.

bash
12# "stream": true answers with server-sent events until the task finishes3curl -N -X POST https://api.inference.sh/apps/run \4  -H "Authorization: Bearer $INFERENCE_API_KEY" \5  -H "Content-Type: application/json" \6  -d '{7    "app": "tripo/tripo-rig",8    "input": {9      "model": "https://example.com/file.png"10    },11    "stream": true12  }'

run in the background

start the task and get its id back right away, then check on it later. for long tasks, or when you'd rather be called back, see webhooks.

bash
1# without "wait" the call returns the task right away (status 1, "received")2TASK_ID=$(curl -s -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "tripo/tripo-rig",7    "input": {8      "model": "https://example.com/file.png"9    }10  }' | jq -r '.data.id')1112# later: read its state. done when status is 10 (completed), 11 (failed) or 12 (cancelled)13curl -s https://api.inference.sh/tasks/$TASK_ID \14  -H "Authorization: Bearer $INFERENCE_API_KEY" | jq '.data | {status, status_text, output}'

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

pass urls directly or use data uris for inline content.

bash
1# pass URLs or data URIs as input values2curl -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "tripo/tripo-rig",7    "input": {8      "image": "https://example.com/image.png",9      "audio": "data:audio/mp3;base64,..."10    },11    "wait": true12  }'

manual upload

you can also upload files manually and use the returned url.

bash
1# 1. create the file: the response has an upload_url and the file's uri2FILE=$(curl -s -X POST https://api.inference.sh/files \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{"files": [{"filename": "image.png", "content_type": "image/png"}]}')67# 2. PUT the bytes to upload_url8curl -X PUT "$(echo "$FILE" | jq -r '.data[0].upload_url')" \9  -H "Content-Type: image/png" \10  --data-binary @image.png1112# 3. pass the uri as an input value13echo "$FILE" | jq -r '.data[0].uri'

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

bash
1curl -X POST https://api.inference.sh/apps/run \2  -H "Authorization: Bearer $INFERENCE_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "app": "tripo/tripo-rig",6    "input": {7        "model": "https://example.com/file.png"8    },9    "webhook": "https://your-server.com/webhook"10  }'

webhook payload

your endpoint receives a JSON POST with the task result:

json
1{2  "event": "task.completed",3  "timestamp": "2024-01-15T10:30:05Z",4  "data": {5    "id": "task_abc123",6    "short_id": "abc123",7    "status": 10,8    "status_text": "completed",9    "output": { ... },10    "created_at": "2024-01-15T10:30:00Z",11    "updated_at": "2024-01-15T10:30:05Z"12  }13}
eventstringtask.completed, task.failed or task.cancelled
timestampstringiso timestamp of the delivery
data.idstringtask id
data.short_idstringshort task id
data.statusnumberterminal status (10=completed, 11=failed, 12=cancelled, 13=rejected)
data.status_textstringthe status as a word: completed, failed or cancelled
data.outputobjecttask output (when completed)
data.errorstringerror message (when failed, omitted otherwise)
data.session_idstringsession id (when the task ran in a session, omitted otherwise)
data.created_atstringiso timestamp
data.updated_atstringiso timestamp

5. schema

input

modelstring(file)*

the 3d model to rig: glb, fbx, obj or stl, up to 150 mb.

rig_typestring

the kind of body. empty: tripo's rig check decides, and refuses a model it cannot rig.

options:"biped""quadruped""hexapod""octopod""avian""serpentine""aquatic""others"
specstring

bone naming for a biped: tripo's own, or that of mixamo, actorcore, unity, unreal or vrm.

default: "tripo"
options:"tripo""mixamo""actorcore""unity""unreal""vrm"
out_formatstring

file format of the rigged model.

default: "glb"
options:"glb""fbx"
animationsarray

preset animations to put on the rig, up to five (10 credits each). plain presets are for bipeds; the others name their rig type.

animate_in_placeboolean

keep animations in place instead of moving through the scene.

default: false

output

animatedstring(file)

the rigged model with the animations, when any were asked for.

modelstring(file)*

the rigged model.

rig_typestring*

the rig type used.

other 3d apps

Hunyuan 3D Auto Rigging

tencent/hunyuan-3d-auto-rigging

$0.02/credit, 10 credits/call ($0.20/call)

Hunyuan 3D 3.1

tencent/hunyuan-3d-3-1

$0.02/credit; Geometry 15cr, Normal 25cr, +10cr views/PBR/face-count

Rodin Gen-2.5

hyper3d/rodin-gen-2-5

$0.58/credit; Extreme-High tier +0.5 credits, texture extreme-high +2 credits

Meshy 7.1

meshy/meshy-7-1

$0.0127/Meshy credit (20 base + 10-15 texture + 5 hi-res geo)

Tripo 3.1

tripo/tripo-3-1

$0.01/credit, $0.10-$0.50/run (text: 10-40 credits, image/multiview: 20-50 credits)

more from tripo

Tripo 3.1

tripo/tripo-3-1

$0.01/credit, $0.10-$0.50/run (text: 10-40 credits, image/multiview: 20-50 credits)

new models

  1. Hunyuan 3D Auto Rigging

    tencent/hunyuan-3d-auto-rigging

    3d$0.02/credit, 10 credits/call ($0.20/call)

  2. Hunyuan 3D 3.1

    tencent/hunyuan-3d-3-1

    3d$0.02/credit; Geometry 15cr, Normal 25cr, +10cr views/PBR/face-count

  3. Rodin Gen-2.5

    hyper3d/rodin-gen-2-5

    3d$0.58/credit; Extreme-High tier +0.5 credits, texture extreme-high +2 credits

  4. Meshy 7.1

    meshy/meshy-7-1

    3d$0.0127/Meshy credit (20 base + 10-15 texture + 5 hi-res geo)

  5. Tripo 3.1

    tripo/tripo-3-1

    3d$0.01/credit, $0.10-$0.50/run (text: 10-40 credits, image/multiview: 20-50 credits)

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