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"""Hunyuan3D-2.1 3D model generation."""
# CRITICAL: Import spaces BEFORE torch/CUDA packages
import spaces
import torch
from pathlib import Path
from gradio_client import Client, handle_file
import httpx
from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type
from core.config import HUNYUAN_SETTINGS, QualityPreset
from utils.memory import MemoryManager
class HunyuanGenerator:
"""Generates 3D models using Hunyuan3D-2.1."""
def __init__(self):
self.memory_manager = MemoryManager()
@retry(
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=4, max=10),
retry=retry_if_exception_type((httpx.TimeoutException, httpx.NetworkError))
)
def _call_api(self, client: Client, **kwargs):
"""Call Hunyuan3D API with automatic retry."""
return client.predict(**kwargs)
@spaces.GPU(duration=90)
def generate(
self,
image_path: Path,
preset: QualityPreset,
output_dir: Path
) -> Path:
"""Generate 3D model from 2D image."""
try:
print(f"[Hunyuan3D] Generating 3D model: {preset.name} quality")
print(f"[Hunyuan3D] Input image: {image_path}")
print(f"[Hunyuan3D] Settings: steps={preset.hunyuan_steps}, guidance={preset.hunyuan_guidance}, octree={preset.octree_resolution}")
# Validate input image exists
if not image_path.exists():
raise FileNotFoundError(f"Input image not found: {image_path}")
# Connect to API
print(f"[Hunyuan3D] Connecting to {HUNYUAN_SETTINGS['space_id']}...")
client = Client(
HUNYUAN_SETTINGS["space_id"],
httpx_kwargs={
"timeout": httpx.Timeout(
HUNYUAN_SETTINGS["timeout"],
connect=HUNYUAN_SETTINGS["connect_timeout"]
)
}
)
print(f"[Hunyuan3D] Connected successfully")
# Call API (returns tuple: file, output, mesh_stats, seed)
print(f"[Hunyuan3D] Calling API with parameters...")
result = self._call_api(
client,
image=handle_file(str(image_path)),
mv_image_front=None,
mv_image_back=None,
mv_image_left=None,
mv_image_right=None,
steps=preset.hunyuan_steps,
guidance_scale=preset.hunyuan_guidance,
seed=1234,
octree_resolution=preset.octree_resolution,
check_box_rembg=True,
num_chunks=preset.num_chunks,
randomize_seed=True,
api_name="/shape_generation"
)
print(f"[Hunyuan3D] API call completed")
# Extract GLB path from tuple response
# API returns: (file, output, mesh_stats, seed)
print(f"[Hunyuan3D] Raw result type: {type(result)}")
print(f"[Hunyuan3D] Raw result length: {len(result) if isinstance(result, (tuple, list)) else 'N/A'}")
if not isinstance(result, tuple):
raise ValueError(
f"Unexpected result type from Hunyuan3D API: {type(result)}. "
f"Expected tuple of (file, output, mesh_stats, seed)."
)
if len(result) != 4:
raise ValueError(
f"Unexpected result length from Hunyuan3D API: {len(result)}. "
f"Expected 4 elements (file, output, mesh_stats, seed), got {len(result)}."
)
# Extract GLB file path (first element)
file_data, html_output, mesh_stats, used_seed = result
print(f"[Hunyuan3D] file_data type: {type(file_data)}")
print(f"[Hunyuan3D] mesh_stats: {mesh_stats}")
print(f"[Hunyuan3D] used_seed: {used_seed}")
# Extract path from file_data
if file_data is None:
raise ValueError(
"Hunyuan3D API returned None for file. "
"This usually means the generation failed on the server side. "
"Possible causes:\n"
" - Invalid image input\n"
" - API timeout\n"
" - Server overload\n"
"Try again with a different image or quality setting."
)
# Handle different file_data formats
if isinstance(file_data, dict):
print(f"[Hunyuan3D] file_data is dict with keys: {file_data.keys()}")
if 'path' in file_data:
glb_path = file_data['path']
elif 'value' in file_data:
glb_path = file_data['value']
elif 'name' in file_data:
glb_path = file_data['name']
else:
raise ValueError(
f"Unexpected dict format from Hunyuan3D API. "
f"Keys: {list(file_data.keys())}"
)
elif isinstance(file_data, str):
glb_path = file_data
else:
raise ValueError(
f"Unexpected file_data type: {type(file_data)}. "
f"Expected dict or str."
)
print(f"[Hunyuan3D] Extracted GLB path: {glb_path}")
# Validate path exists
if not glb_path or glb_path == "None":
raise ValueError(
"Hunyuan3D API returned invalid path. "
"The generation may have failed on the server side."
)
if not Path(glb_path).exists():
raise ValueError(
f"GLB file not found at path: {glb_path}. "
f"The file may not have been generated or saved correctly."
)
print(f"[Hunyuan3D] Model generated: {glb_path}")
# Cleanup
del client
import gc
gc.collect()
torch.cuda.empty_cache()
return Path(glb_path)
except Exception as e:
import traceback
error_details = traceback.format_exc()
print(f"[Hunyuan3D] ERROR: {e}")
print(f"[Hunyuan3D] Full traceback:\n{error_details}")
# Provide helpful error message
if "list index out of range" in str(e):
raise ValueError(
f"Hunyuan3D API returned unexpected result format. "
f"This usually means the generation failed on the server side. "
f"Please try again with a different prompt or quality setting."
) from e
elif "timeout" in str(e).lower():
raise TimeoutError(
f"Hunyuan3D generation timed out. "
f"Try using a lower quality preset (Fast or Balanced)."
) from e
else:
raise RuntimeError(
f"Hunyuan3D generation failed: {e}. "
f"Check logs for details."
) from e
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