Create app.py

app.py

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+import torch
+import gradio as gr
+from diffusers import StableDiffusionXLPipeline
+from PIL import Image
+from io import BytesIO
+import os
+import requests
+import time
+from tqdm import tqdm
+
+# Load local Stable Diffusion XL model
+model_path = "networks/TShirtDesignRedmondV2-Tshirtdesign-TshirtDesignAF.safetensors"
+pipe = StableDiffusionXLPipeline.from_single_file(
+    model_path,
+    torch_dtype=torch.float16, 
+    use_safetensors=True,
+)
+pipe = pipe.to("cuda")
+
+repo = "artificialguybr/TshirtDesignRedmond-V2"
+api_url = f"https://api-inference.huggingface.co/models/{repo}"
+
+def infer(color_prompt, dress_type_prompt, design_prompt, text):
+    prompt = (
+        f"A single {color_prompt} colored {dress_type_prompt} featuring a bold {design_prompt} design printed on the {dress_type_prompt},"
+        " hanging on a plain wall. The soft light and shadows create a striking contrast against the minimal background, evoking modern sophistication."
+    )
+    
+    print("Generating image locally with prompt:", prompt)
+    try:
+        image = pipe(prompt).images[0]
+        return image
+    except Exception as e:
+        print("Local generation failed. Switching to API.", str(e))
+        
+        # API fallback
+        headers = {}
+        payload = {
+            "inputs": prompt,
+            "parameters": {
+                "negative_prompt": "(worst quality, low quality, lowres, bad details, watermark, text, blurry, cartoon, 3D, bad anatomy, outdated fashion, cheap look, unreal details, unwanted features)",
+                "num_inference_steps": 30,
+                "scheduler": "DPMSolverMultistepScheduler"
+            },
+        }
+
+        error_count = 0
+        pbar = tqdm(total=None, desc="Loading model")
+        while True:
+            response = requests.post(api_url, headers=headers, json=payload)
+            if response.status_code == 200:
+                return Image.open(BytesIO(response.content))
+            elif response.status_code == 503:
+                time.sleep(1)
+                pbar.update(1)
+            elif response.status_code == 500 and error_count < 5:
+                time.sleep(1)
+                error_count += 1
+            else:
+                raise Exception(f"API Error: {response.status_code}")
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=infer,
+    inputs=[
+        gr.Textbox(lines=1, placeholder="Color"),
+        gr.Textbox(lines=1, placeholder="Dress Type"),
+        gr.Textbox(lines=2, placeholder="Design"),
+        gr.Textbox(lines=1, placeholder="Text (Optional)")
+    ],
+    outputs="image",
+    title="AI-Generated T-Shirt Designs",
+    description="Generate custom t-shirt designs using AI!",
+    examples=[["Red", "T-shirt", "Minimalistic logo", "Brand Name"]]
+)
+
+print("Launching Gradio interface...")
+iface.launch()