Phase 5: 3D Generation · 50 min · Python · Tripo API · Rodin API

3D Generation API Integration & Evaluation

Generate, evaluate, host, deliver — the full 3D generation engineering pipeline.

Hiring signal: 3D API integration and evaluation (Chamfer distance, geometric accuracy) demonstrates you can build production 3D generation systems, not just call APIs.

What you will learn

Integrate Tripo API and Rodin API for programmatic 3D generation
Deploy Hunyuan3D for self-hosted 3D generation
Evaluate 3D model quality: mesh quality, texture fidelity, geometric accuracy (Chamfer distance)
Implement 3D model hosting and delivery: CDN, format conversion, thumbnail generation

The Problem

A team integrates the Tripo API for 3D generation. They can generate models, but:

They don't know how to evaluate quality — is the generated model accurate?
They don't know how to host models — where do they store the GLB files?
They don't know how to generate thumbnails — they need preview images
They don't have a fallback — if Tripo fails, they have no backup

3D API integration and evaluation (Chamfer distance, geometric accuracy) demonstrates you can build production 3D generation systems, not just call APIs.

What you'll build
Integrate Tripo API and Rodin API for programmatic 3D generation. Evaluate 3D model quality (mesh quality, texture fidelity, Chamfer distance). Implement 3D model hosting and delivery (CDN, format conversion, thumbnails).

Tripo API Integration

Generate 3D Model

import requests

TRIPO_API_KEY = os.getenv("TRIPO_API_KEY")
TRIPO_API = "https://api.tripo3d.ai/v1"

def generate_tripo(prompt: str = None, image_url: str = None,
                   topology: str = "game_ready", format: str = "glb") -> dict:
    """Generate 3D model with Tripo API."""
    payload = {"topology": topology, "format": format}
    
    if prompt:
        payload["type"] = "text_to_model"
        payload["prompt"] = prompt
    elif image_url:
        payload["type"] = "image_to_model"
        payload["image"] = image_url
    
    response = requests.post(
        f"{TRIPO_API}/generate",
        headers={"Authorization": f"Bearer {TRIPO_API_KEY}"},
        json=payload,
    )
    return response.json()

Async Pattern (Same as Video/Audio)

def generate_tripo_async(prompt: str) -> str:
    """Submit generation and return job ID."""
    resp = requests.post(f"{TRIPO_API}/generate",
        headers={"Authorization": f"Bearer {TRIPO_API_KEY}"},
        json={"type": "text_to_model", "prompt": prompt})
    return resp.json()["job_id"]

def poll_tripo_status(job_id: str, timeout=180) -> dict:
    """Poll for generation status."""
    start = time.time()
    while time.time() - start < timeout:
        resp = requests.get(f"{TRIPO_API}/jobs/{job_id}",
            headers={"Authorization": f"Bearer {TRIPO_API_KEY}"})
        data = resp.json()
        if data["status"] == "completed":
            return data
        elif data["status"] == "failed":
            raise Exception(f"Generation failed: {data}")
        time.sleep(5)
    raise TimeoutError(f"Job {job_id} timed out")

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Rodin API Integration, Hunyuan3D (Self-Hosted), 3D Model Quality Evaluation, 3D Model Hosting & Delivery, Multi-Provider Router, Key Takeaways, What's Next — plus a hands-on lab, quiz, and project artifact.

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