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import sys
from pathlib import Path
import gradio as gr
from huggingface_hub import hf_hub_download
# -------------------------------
# Step 1: Add CADFusion repo to sys.path
# -------------------------------
# CADFusion folder must contain the 'cadfusion/' subfolder
CADFUSION_DIR = Path("CADFusion")
sys.path.append(str(CADFUSION_DIR.resolve()))
# Now Python can find the 'cadfusion' module
from cadfusion.inference import InferenceRunner
from cadfusion.utils.config import load_config
# -------------------------------
# Step 2: Download config & checkpoint from Hugging Face Hub
# -------------------------------
CONFIG_PATH = hf_hub_download(
repo_id="microsoft/CADFusion",
filename="adapter_config.json",
revision="v1_1"
)
CHECKPOINT_PATH = hf_hub_download(
repo_id="microsoft/CADFusion",
filename="adapter_model.safetensors",
revision="v1_1"
)
# -------------------------------
# Step 3: Initialize CADFusion runner
# -------------------------------
config = load_config(CONFIG_PATH)
runner = InferenceRunner(config=config)
runner.load_checkpoint(CHECKPOINT_PATH)
# -------------------------------
# Step 4: Define CAD generation function
# -------------------------------
def generate_cad(prompt: str):
try:
outputs = runner.infer_from_text(prompt)
out_file = "output.stl"
mesh = outputs.to_trimesh()
mesh.export(out_file)
return out_file
except Exception as e:
return f"Error during inference: {str(e)}"
# -------------------------------
# Step 5: Gradio interface
# -------------------------------
demo = gr.Interface(
fn=generate_cad,
inputs=gr.Textbox(label="Enter CAD description"),
outputs=gr.File(label="Generated STL Model"),
title="CADFusion - Text to CAD",
description="Enter a natural language description and generate a 3D CAD mesh (STL)."
)
if __name__ == "__main__":
demo.launch()
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