Update app.py

app.py

@@ -2,75 +2,88 @@ import os
 import gradio as gr
 import google.generativeai as genai
 from PIL import Image
-import io
-import base64
-import time
 
-# Configuration optimized for Hugging Face
-MAX_RETRIES = 3
-TIMEOUT = 10  # Keep under 20s Hugging Face limit
+# Configuration for Hugging Face Spaces
+MAX_SIZE = 512  # Reduced image size for HF memory limits
+TIMEOUT = 18  # Stay safely under 20s timeout
+STYLES = ["General", "Vector", "Realistic", "Kawaii"]
 
-# Simplified style instructions for faster processing
-STYLE_INSTRUCTIONS = {
-    "General": "Describe as Flux prompt focusing on key elements",
-    "Vector": "Clean vector style with sharp lines and B&W",
-    "Realistic": "Photorealistic details with accurate textures",
-}
-
-def optimize_image(img):
-    """Fast image optimization for web"""
-    img = img.convert("RGB")
-    img.thumbnail((512, 512))  # Reduce image size
+def process_image(image):
+    """Optimize image for Hugging Face environment"""
+    img = image.convert("RGB")
+    img.thumbnail((MAX_SIZE, MAX_SIZE))
     return img
 
 def generate_prompt(image, api_key, style):
-    for attempt in range(MAX_RETRIES):
-        try:
-            start_time = time.time()
-            
-            # Configure API
-            genai.configure(api_key=api_key)
-            model = genai.GenerativeModel('gemini-pro-vision')
-            
-            # Optimize image
-            img = optimize_image(image)
-            img_byte_arr = io.BytesIO()
-            img.save(img_byte_arr, format='JPEG', quality=85)
-            
-            # Timeout control
-            if time.time() - start_time > TIMEOUT - 2:
-                raise TimeoutError("Image processing too slow")
-                
-            response = model.generate_content([
-                STYLE_INSTRUCTIONS[style],
-                {"mime_type": "image/jpeg", "data": img_byte_arr.getvalue()}
-            ], request_options={"timeout": TIMEOUT})
-            
-            return response.text
-            
-        except Exception as e:
-            if attempt == MAX_RETRIES - 1:
-                return f"Error: {str(e)}"
-            time.sleep(1)
+    try:
+        # Validate inputs
+        if not image:
+            return "⚠️ Please upload an image first"
+        if not api_key:
+            return "🔑 API key required"
+
+        # Process image
+        img = process_image(image)
+        
+        # Configure Gemini
+        genai.configure(api_key=api_key)
+        model = genai.GenerativeModel('gemini-pro-vision')
+        
+        # Create prompt based on style
+        base_prompt = "Describe this design concisely for Flux 1.1 Pro"
+        if style == "Vector":
+            instruction = f"{base_prompt} in clean vector style with sharp lines"
+        elif style == "Realistic":
+            instruction = f"{base_prompt} with photorealistic details"
+        else:
+            instruction = base_prompt
+
+        # Generate with timeout safety
+        response = model.generate_content(
+            contents=[instruction, img],
+            request_options={"timeout": TIMEOUT}
+        )
+        
+        return response.text if response.text else "❌ No response generated"
+
+    except Exception as e:
+        return f"⚠️ Error: {str(e)}"
 
-# Hugging Face optimized interface
-with gr.Blocks() as app:
-    gr.Markdown("## 🚀 HF-Friendly Flux Generator")
+# Gradio interface optimized for Hugging Face
+with gr.Blocks(title="Flux Prompt Generator") as app:
+    gr.Markdown("# 🎨 Flux AI Prompt Generator")
     
     with gr.Row():
-        api_key = gr.Textbox(label="Gemini Key", type="password")
-        style = gr.Dropdown(list(STYLE_INSTRUCTIONS), label="Style")
+        api_key = gr.Textbox(
+            label="Google Gemini API Key",
+            type="password",
+            placeholder="Enter your API key..."
+        )
+        style = gr.Dropdown(
+            STYLES,
+            value="General",
+            label="Design Style"
+        )
     
-    image_input = gr.Image(type="pil", label="Upload Design")
-    generate_btn = gr.Button("Generate", variant="primary")
-    output = gr.Textbox(label="Prompt", interactive=False)
+    image_input = gr.Image(
+        label="Upload Your Design",
+        type="pil",
+        height=300
+    )
+    
+    generate_btn = gr.Button("Generate Prompt", variant="primary")
+    
+    output = gr.Textbox(
+        label="Generated Prompt",
+        placeholder="Your prompt will appear here...",
+        lines=5
+    )
 
     generate_btn.click(
-        generate_prompt,
+        fn=generate_prompt,
         inputs=[image_input, api_key, style],
-        outputs=output,
-        concurrency_limit=3  # Better HF resource management
+        outputs=output
     )
 
-# HF-specific launch settings
-app.queue(concurrency_count=3, max_size=20).launch(debug=True)
+# Hugging Face compatible launch settings
+app.launch(debug=False, show_error=True)