Update app.py

app.py

@@ -8,47 +8,45 @@ from concurrent.futures import ThreadPoolExecutor
 
 # ===== CONFIGURATION =====
 HF_API_TOKEN = os.environ.get("HF_API_TOKEN")
-MODEL_NAME = "stabilityai/stable-diffusion-xl-base-1.0"
+MODEL_NAME = "stabilityai/stable-diffusion-xl-base-1.0"  # Using SDXL
 API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
 headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
 WATERMARK_TEXT = "SelamGPT"
 MAX_RETRIES = 3
-TIMEOUT = 45  # Increased timeout for larger images
-EXECUTOR = ThreadPoolExecutor(max_workers=2)  # Handle concurrent requests
+TIMEOUT = 60  # Increased for SDXL's longer processing
+EXECUTOR = ThreadPoolExecutor(max_workers=2)
 
 # ===== WATERMARK FUNCTION =====
 def add_watermark(image_bytes):
-    """Add watermark with smaller text and simplified positioning"""
+    """Add clean watermark with small text in bottom-right"""
     try:
         image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
         draw = ImageDraw.Draw(image)
         
-        # Smaller font size (24 instead of 40)
+        # Font setup (smaller size)
         font_size = 24
         try:
             font = ImageFont.truetype("Roboto-Bold.ttf", font_size)
         except:
             font = ImageFont.load_default(font_size)
         
-        text = "SelamGPT"
-        margin = 10  # Reduced from 20
+        # Positioning (10px margin from edges)
+        text_width = draw.textlength(WATERMARK_TEXT, font=font)
+        x = image.width - text_width - 10
+        y = image.height - 34  # Slightly above bottom edge
         
-        # Calculate position using textlength
-        text_width = draw.textlength(text, font=font)
-        x = image.width - text_width - margin
-        y = image.height - 30  # Fixed vertical position
-        
-        # Simpler white text without transparency
-        draw.text((x, y), text, font=font, fill=(255, 255, 255))
+        # Draw white text with slight shadow for readability
+        draw.text((x+1, y+1), WATERMARK_TEXT, font=font, fill=(0, 0, 0, 128))  # Shadow
+        draw.text((x, y), WATERMARK_TEXT, font=font, fill=(255, 255, 255))  # Main text
         
         return image
     except Exception as e:
         print(f"Watermark error: {str(e)}")
         return Image.open(io.BytesIO(image_bytes))
 
-# ===== IMAGE GENERATION =====
+# ===== IMAGE GENERATION (SDXL-OPTIMIZED) =====
 def generate_image(prompt):
-    """Generate image with robust error handling"""
+    """Generate image with SDXL-specific parameters"""
     if not prompt.strip():
         return None, "⚠️ Please enter a prompt"
     
@@ -59,9 +57,10 @@ def generate_image(prompt):
             json={
                 "inputs": prompt,
                 "parameters": {
-                    "height": 768,
-                    "width": 768,
-                    "num_inference_steps": 25
+                    "height": 1024,  # SDXL's native resolution
+                    "width": 1024,
+                    "num_inference_steps": 30,  # Better quality than 25
+                    "guidance_scale": 7.5  # SDXL's optimal value
                 },
                 "options": {"wait_for_model": True}
             },
@@ -76,18 +75,18 @@ def generate_image(prompt):
             if response.status_code == 200:
                 return add_watermark(response.content), "✔️ Generation successful"
             elif response.status_code == 503:
-                wait_time = (attempt + 1) * 10
+                wait_time = (attempt + 1) * 15  # Longer wait for SDXL
                 print(f"Model loading, waiting {wait_time}s...")
                 time.sleep(wait_time)
                 continue
             else:
                 return None, f"⚠️ API Error: {response.text[:200]}"
         except requests.Timeout:
-            return None, "⚠️ Timeout: Model took too long to respond"
+            return None, f"⚠️ Timeout: Model took >{TIMEOUT}s to respond"
         except Exception as e:
             return None, f"⚠️ Unexpected error: {str(e)[:200]}"
     
-    return None, "⚠️ Failed after multiple attempts. Please try again later."
+    return None, "⚠️ Failed after multiple attempts. Please try later."
 
 # ===== GRADIO INTERFACE =====
 theme = gr.themes.Default(
@@ -99,7 +98,7 @@ theme = gr.themes.Default(
 with gr.Blocks(theme=theme, title="SelamGPT Image Generator") as demo:
     gr.Markdown("""
     # 🎨 SelamGPT Image Generator
-    *Generate watermarked images with Stable Diffusion XL*
+    *Now powered by Stable Diffusion XL (1024x1024 resolution)*
     """)
     
     with gr.Row():
@@ -117,17 +116,17 @@ with gr.Blocks(theme=theme, title="SelamGPT Image Generator") as demo:
             
             gr.Examples(
                 examples=[
-                    ["An ancient Aksumite warrior in cyberpunk armor"],
-                    ["Traditional Ethiopian coffee ceremony in space"],
-                    ["Hyper-realistic portrait of a Habesha woman with neon tribal markings"]
+                    ["An ancient Aksumite warrior in cyberpunk armor, 4k detailed"],
+                    ["Traditional Ethiopian coffee ceremony in zero gravity, photorealistic"],
+                    ["Portrait of a Habesha queen with golden jewelry, studio lighting"]
                 ],
                 inputs=prompt_input,
-                label="Example Prompts"
+                label="Try these SDXL-optimized prompts:"
             )
             
         with gr.Column(scale=2):
             output_image = gr.Image(
-                label="Generated Image",
+                label="Generated Image (1024x1024)",
                 height=512,
                 elem_id="output-image"
             )
@@ -137,7 +136,6 @@ with gr.Blocks(theme=theme, title="SelamGPT Image Generator") as demo:
                 elem_id="status-box"
             )
     
-    # Event handlers
     generate_btn.click(
         fn=generate_image,
         inputs=prompt_input,
@@ -151,10 +149,6 @@ with gr.Blocks(theme=theme, title="SelamGPT Image Generator") as demo:
         outputs=[output_image, status_output]
     )
 
-# ===== DEPLOYMENT CONFIG =====
 if __name__ == "__main__":
-    demo.queue(max_size=2)  # Correct parameter name
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860
-    )
+    demo.queue(max_size=2)
+    demo.launch(server_name="0.0.0.0", server_port=7860)