Create app.py

app.py

@@ -0,0 +1,85 @@
+import gradio as gr
+from diffusers import AutoPipelineForText2Image
+import torch
+import os
+
+# Model configuration
+MODEL_NAME = "katuni4ka/tiny-random-flex.2-preview"
+CACHE_DIR = "./model_cache"
+
+# Create cache directory
+os.makedirs(CACHE_DIR, exist_ok=True)
+
+# Load model with optimized settings
+pipe = AutoPipelineForText2Image.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.float16,
+    cache_dir=CACHE_DIR
+).to("cuda" if torch.cuda.is_available() else "cpu")
+
+# Aspect ratio presets
+ASPECT_RATIOS = {
+    "Square (1:1)": (512, 512),
+    "Landscape (16:9)": (1024, 576),
+    "Portrait (9:16)": (576, 1024),
+    "A4 (3:4)": (864, 1152)
+}
+
+def generate_image(prompt, aspect_ratio, num_inference_steps=25, guidance_scale=4.5):
+    """Generate image with optimized inference settings"""
+    width, height = ASPECT_RATIOS[aspect_ratio]
+    
+    with torch.inference_mode():
+        image = pipe(
+            prompt=prompt,
+            width=width,
+            height=height,
+            num_inference_steps=num_inference_steps,
+            guidance_scale=guidance_scale
+        ).images[0]
+    
+    return image
+
+# UI Configuration
+with gr.Blocks(theme="huggingface", analytics_enabled=False) as demo:
+    gr.Markdown("""
+    # Tiny Random Flex Text-to-Image Generator
+    Create images from text prompts using the `katuni4ka/tiny-random-flex.2-preview` model
+    
+    💡 Tip: Try descriptive prompts like "A futuristic cityscape at sunset" or "Abstract watercolor patterns"
+    """)
+    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="Describe your image...",
+                lines=3
+            )
+            aspect_ratio = gr.Dropdown(
+                label="Aspect Ratio",
+                choices=list(ASPECT_RATIOS.keys()),
+                value="Square (1:1)"
+            )
+            generate_btn = gr.Button("🎨 Generate Image", variant="primary")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image", interactive=False)
+    
+    generate_btn.click(
+        fn=generate_image,
+        inputs=[prompt, aspect_ratio],
+        outputs=output_image
+    )
+    
+    gr.Examples(
+        examples=[
+            ["A vibrant neon cityscape at night", "Landscape (16:9)"],
+            ["Abstract geometric patterns in pastel colors", "Square (1:1)"],
+            ["Mystical forest with glowing plants", "Portrait (9:16)"]
+        ],
+        inputs=[prompt, aspect_ratio]
+    )
+
+if __name__ == "__main__":
+    demo.launch()