Enterprise-grade 3D model generation using Hyper3D Rodin Gen-2.5 API. Enables production-quality Image-to-3D and Text-to-3D conversion with advanced geometry and texture controls.
Enterprise-grade 3D model generation using Hyper3D Rodin Gen-2.5 API. Enables production-quality Image-to-3D and Text-to-3D conversion with advanced geometry and texture controls.
metadata
{"author":"HyperHuman","version":"2.0.0","tags":"3D Asset, Hyper3D, Rodin, Rodin Gen-2.5, API, 3D Model, Image-to-3D, Text-to-3D, AI Generation","documentation":"https://developer.hyper3d.ai/api-specification/rodin-gen2.5"}
Hyper3D Rodin Gen-2.5 Skill Documentation
Overview
This skill provides a comprehensive integration with the Hyper3D Rodin Gen-2.5 API, enabling developers to generate production-ready 3D models from images or text prompts. The skill handles API authentication, task submission, status polling, and result retrieval with enterprise-grade reliability.
Key Capabilities:
Image-to-3D reconstruction (up to 5 input images)
Text-to-3D generation
Advanced geometry and texture controls
Multi-format output support (glb, usdz, fbx, obj, stl)
Asynchronous task management with automatic polling
Quick Start
Prerequisites
API Key:
Free Test Key: vibecoding (automatically used when no key is provided)
# Quick start with free test key (no API key required)
# Generate from image with your API key
$HYPER3D_API_KEY
# Generate from text
"A detailed 3D model of a vintage camera"
Core Concepts
API Endpoints
Endpoint
Method
Purpose
/api/v2/rodin
POST
Submit generation task
/api/v2/status
POST
Check task status
/api/v2/download
POST
Retrieve download links
Task Lifecycle
Submit: POST to /api/v2/rodin → Returns subscription_key and task_uuid
Poll: POST to /api/v2/status with subscription_key → Check job status
Download: POST to /api/v2/download with task_uuid → Get result URLs (expire in 10 minutes)
Parameter Reference
Tier Selection
Tier
Description
Credit Cost
Recommended Use Case
Gen-2.5-Extreme-Low
Rapid generation for simple assets
0.5
Prototyping, quick iterations
Gen-2.5-Low
Clean assets, small hardsurface props
0.5
Basic models, low-poly assets
Gen-2.5-Medium
Balanced structure and detail
0.5
Default - general purpose
Gen-2.5-High
Rich structural representation, smooth surfaces
0.5
Production-ready assets
Gen-2.5-Extreme-High
High-frequency detail reproduction
1.0
Premium quality, final renders
Gen-2
Legacy tier
0.5
Backward compatibility
Detail/Regular/Smooth/Sketch
Legacy tiers
0.5
Deprecated, use Gen-2.5
Quality Levels (Face Count)
Quality
Raw Mode
Quad Mode
Use Case
high
1M faces
50k faces
Production, close-ups
medium
500k faces
18k faces
Default - balanced
low
60k faces
8k faces
Real-time applications
extra-low
20k faces
4k faces
Mobile, VR/AR
Material Types
Material
Description
PBR
Physically Based Rendering (base color, metallic, normal, roughness maps)
Shaded
Base color texture with baked lighting
All
Both PBR and Shaded materials
None
Geometry only, no materials
Gen-2.5 Exclusive Features
Parameter
Type
Description
Default
hd_texture
bool
Enable 4K texture generation
false
texture_delight
bool
Enhance texture quality and detail
false
texture_mode
string
Advanced texture generation mode
None
is_micro
bool
Optimize for micro-scale objects
false
geometry_instruct_mode
string
Geometry generation guidance
faithful
Mesh Mode Comparison
Mode
Description
Recommended For
Raw
Triangle mesh, maximum detail preservation
Gen-2.5 tiers
Quad
Quadrilateral mesh, cleaner topology
Legacy tiers
Addons
Addon
Cost
Description
HighPack
+1 credit
4K texture resolution upgrade
Command Line Interface
Required Arguments
# Image input (required for Image-to-3D)
--image path/to/image1.jpg [path/to/image2.jpg ...]
# OR Text input (required for Text-to-3D)
--prompt "Your text description"
Trigger Condition: Fast mode is automatically activated when all of the above parameters are set together. This combination provides the quickest generation time for rapid prototyping and preview purposes.
Recipe 4: Batch Processing Workflow
# Process multiple images sequentiallyfor img in ./input/*.jpg; do
python scripts/generate_3d_model.py \
--image "$img" \
--tier Gen-2.5-Medium \
--output ./output/$(basename"$img" .jpg)
done
Python API Integration
Basic Client Usage
from api_client import Hyper3DAPIClient
# Initialize client
client = Hyper3DAPIClient(api_key="your_api_key")
# Generate from image
task_uuid, result = client.generate_3d_model(
images=["input.jpg"],
tier="Gen-2.5-High",
geometry_file_format="glb",
quality="high",
material="PBR",
mesh_mode="Raw",
hd_texture=True,
texture_delight=True,
poll_interval=15,
max_retries=40
)
# Process resultsprint(f"Task completed: {task_uuid}")
for file_info in result.get("list", []):
print(f"File: {file_info['name']} - URL: {file_info['url']}")
Advanced Configuration
from api_client import Hyper3DAPIClient
client = Hyper3DAPIClient(api_key="your_api_key")
# Custom generation with all parameters
task_uuid, result = client.generate_3d_model(
images=["front.jpg", "side.jpg", "top.jpg"],
prompt="A vintage pocket watch with intricate details",
tier="Gen-2.5-Extreme-High",
geometry_file_format="fbx",
quality="high",
material="All",
mesh_mode="Raw",
use_original_alpha=True,
seed=42,
TAPose=False,
bbox_condition=[100, 100, 50],
addons=["HighPack"],
preview_render=True,
hd_texture=True,
texture_delight=True,
is_micro=False,
geometry_instruct_mode="faithful"
)
Manual Task Management
# Submit task
submit_result = client.submit_generation_task(
images=["input.jpg"],
tier="Gen-2.5-Medium"
)
subscription_key = submit_result["jobs"]["subscription_key"]
task_uuid = submit_result["uuid"]
# Manual pollingimport time
for _ inrange(60):
status = client.check_task_status(subscription_key)
jobs = status.get("jobs", [])
ifall(job["status"] == "Done"for job in jobs):
breakelifany(job["status"] == "Failed"for job in jobs):
raise Exception("Task failed")
time.sleep(10)
# Get download links
download_result = client.download_results(task_uuid)
Error Handling & Troubleshooting
Common Error Codes
Error
Cause
Resolution
Not authenticated
Invalid or missing API key
Verify HYPER3D_API_KEY is set correctly
INSUFFICIENT_FUND
Insufficient credits
Add funds via Hyper3D dashboard
Invalid tier
Unknown tier value
Use valid Gen-2.5 tier (see Tier Selection)
Invalid image
Image format/size error
Use JPEG/PNG/WebP, max 16MB, 512x512-4096x4096
Timeout
Generation took too long
Increase --max-retries, check API status
Best Practices
Validate Inputs: Use ImageUtils.validate_image() before submission
Handle Rate Limits: Implement exponential backoff for retries
Store Results: Download models immediately - URLs expire in 10 minutes
Log Everything: Track task UUIDs and status for debugging
Use Appropriate Tier: Match tier to use case to optimize cost/quality