Update app.py

app.py

@@ -1,22 +1,9 @@
-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
-# -------------------------------
+# Download config & model from HF Hub
 CONFIG_PATH = hf_hub_download(
     repo_id="microsoft/CADFusion",
     filename="adapter_config.json",
@@ -29,35 +16,25 @@ CHECKPOINT_PATH = hf_hub_download(
     revision="v1_1"
 )
 
-# -------------------------------
-# Step 3: Initialize CADFusion runner
-# -------------------------------
+# Initialize model
 config = load_config(CONFIG_PATH)
 runner = InferenceRunner(config=config)
 runner.load_checkpoint(CHECKPOINT_PATH)
 
-# -------------------------------
-# Step 4: Define CAD generation function
-# -------------------------------
+# Inference 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)}"
+    outputs = runner.infer_from_text(prompt)
+    out_file = "output.stl"
+    mesh = outputs.to_trimesh()
+    mesh.export(out_file)
+    return out_file
 
-# -------------------------------
-# 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)."
+    description="Enter a text prompt to generate a 3D STL mesh."
 )
 
 if __name__ == "__main__":