Update app.py

app.py

@@ -1,21 +1,15 @@
 """
-Marketing Image Generator - Agent Workflow Test Version
-
-This version clearly shows the Agent1 -> Agent2 workflow:
-- Agent1: Image Generator (calls Google Imagen)
-- Agent2: Image Reviewer (calls Google Gemini Vision)
-- Clear logging of each step
+Marketing Image Generator with AI Review
+Clean, simple Gradio interface
 """
 
 import gradio as gr
 import json
-import time
-import base64
+import os
+import logging
 from PIL import Image, ImageDraw, ImageFont
 import io
-import os
 import hashlib
-import logging
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
@@ -44,340 +38,180 @@ try:
         logger.info("✅ Google API configured")
 except Exception as e:
     logger.error(f"Google setup failed: {e}")
-    genai = None
-
-# ====== AGENT 1: IMAGE GENERATOR ======
-
-class ImageGeneratorAgent:
-    """Agent 1: Responsible for generating images using Google Imagen"""
-    
-    def __init__(self):
-        self.name = "ImageGeneratorAgent"
-        self.status = "Ready"
-        
-    def enhance_prompt(self, prompt, style):
-        """Enhance user prompt for better results"""
-        logger.info(f"🤖 Agent1: Enhancing prompt for {style} style")
-        
-        style_enhancers = {
-            "Professional": "professional photography, corporate setting, high quality, clean composition, marketing ready",
-            "Creative": "creative composition, artistic flair, innovative design, vibrant colors, eye-catching",
-            "Minimalist": "clean minimal design, simple composition, white space, elegant, professional",
-            "Corporate": "business professional, corporate branding, trustworthy, authoritative, polished",
-            "Modern": "contemporary design, sleek, cutting-edge, stylish, trendy"
-        }
-        
-        enhancer = style_enhancers.get(style, "high quality, professional")
-        enhanced = f"{prompt}, {enhancer}, 4K resolution, sharp focus, marketing quality"
-        
-        logger.info(f"🤖 Agent1: Enhanced prompt: {enhanced[:100]}...")
-        return enhanced
-    
-    def generate_image(self, prompt, style, aspect_ratio):
-        """Generate image using Google Imagen"""
-        logger.info(f"🤖 Agent1: Starting image generation")
-        logger.info(f"🤖 Agent1: Original prompt: {prompt}")
-        logger.info(f"🤖 Agent1: Style: {style}, Format: {aspect_ratio}")
-        
-        # Step 1: Enhance prompt
-        enhanced_prompt = self.enhance_prompt(prompt, style)
-        
-        # Step 2: Try Google Imagen
-        if google_auth_configured and genai:
-            try:
-                logger.info(f"🤖 Agent1: Calling Google Imagen API...")
-                
-                if GOOGLE_SERVICE_ACCOUNT_JSON:
-                    client = genai_sdk.Client()
-                else:
-                    client = genai_sdk.Client(api_key=GOOGLE_API_KEY)
-                
-                result = client.models.generate_images(
-                    model="imagen-3.0-generate-002",
-                    prompt=enhanced_prompt,
-                    config={
-                        "number_of_images": 1,
-                        "output_mime_type": "image/png"
-                    }
-                )
-                
-                if result and hasattr(result, 'generated_images') and result.generated_images:
-                    img_data = result.generated_images[0]
-                    if hasattr(img_data, 'image') and hasattr(img_data.image, 'image_bytes'):
-                        image = Image.open(io.BytesIO(img_data.image.image_bytes))
-                        logger.info(f"✅ Agent1: Successfully generated real image with Google Imagen!")
-                        return {
-                            "success": True,
-                            "image": image,
-                            "method": "Google Imagen",
-                            "enhanced_prompt": enhanced_prompt,
-                            "agent": "ImageGeneratorAgent"
-                        }
-                        
-                logger.warning(f"⚠️ Agent1: Google Imagen returned no images")
-                        
-            except Exception as e:
-                logger.error(f"❌ Agent1: Google Imagen failed: {e}")
-        
-        # Step 3: Fallback to demo image
-        logger.info(f"🤖 Agent1: Creating demo image (fallback)")
-        demo_image = self.create_demo_image(prompt, style, aspect_ratio)
-        
-        return {
-            "success": True,
-            "image": demo_image,
-            "method": "Demo Mode",
-            "enhanced_prompt": enhanced_prompt,
-            "agent": "ImageGeneratorAgent"
-        }
-    
-    def create_demo_image(self, prompt, style, aspect_ratio):
-        """Create demo image when API isn't available"""
-        # Set dimensions
-        if "Square" in aspect_ratio:
-            width, height = 400, 400
-        elif "Portrait" in aspect_ratio:
-            width, height = 400, 500
-        else:
-            width, height = 500, 300
-        
-        # Style colors
-        colors = {
-            "Professional": (59, 130, 246),
-            "Creative": (139, 92, 246),
-            "Minimalist": (107, 114, 128),
-            "Corporate": (30, 64, 175),
-            "Modern": (5, 150, 105)
-        }
-        
-        color = colors.get(style, (59, 130, 246))
-        img = Image.new('RGB', (width, height), color)
-        draw = ImageDraw.Draw(img)
-        
-        try:
-            font = ImageFont.load_default()
-            
-            # Add text overlay
-            title = "Marketing Image"
-            bbox = draw.textbbox((0, 0), title, font=font)
-            text_width = bbox[2] - bbox[0]
-            x = (width - text_width) // 2
-            y = height // 2 - 30
-            draw.text((x, y), title, fill="white", font=font)
-            
-            style_text = f"{style} Style"
-            bbox2 = draw.textbbox((0, 0), style_text, font=font)
-            text_width2 = bbox2[2] - bbox2[0]
-            x2 = (width - text_width2) // 2
-            draw.text((x2, y + 25), style_text, fill="white", font=font)
-            
-        except:
-            pass
-        
-        return img
-
-# ====== AGENT 2: IMAGE REVIEWER ======
-
-class ImageReviewerAgent:
-    """Agent 2: Responsible for reviewing images using Google Gemini Vision"""
-    
-    def __init__(self):
-        self.name = "ImageReviewerAgent"
-        self.status = "Ready"
-    
-    def review_image(self, image, original_prompt, enhanced_prompt, generation_method):
-        """Review generated image for quality and marketing effectiveness"""
-        logger.info(f"🔍 Agent2: Starting image review")
-        logger.info(f"🔍 Agent2: Reviewing image generated by: {generation_method}")
-        logger.info(f"🔍 Agent2: Original prompt: {original_prompt}")
-        
-        if google_auth_configured and genai and generation_method == "Google Imagen":
-            try:
-                logger.info(f"🔍 Agent2: Calling Google Gemini Vision for AI review...")
-                
-                model = genai.GenerativeModel('gemini-2.0-flash-exp')
-                
-                review_prompt = f"""You are an expert marketing image reviewer. Analyze this image that was generated from the prompt: "{original_prompt}"
-
-                Rate the image on a scale of 1-10 and provide specific feedback on:
-                1. Technical Quality (clarity, composition, lighting)
-                2. Marketing Effectiveness (professional appeal, brand suitability)  
-                3. Prompt Matching (how well it matches the original request)
 
-                Provide your response in this format:
-                SCORE: X/10
-                QUALITY: [brief assessment]
-                MARKETING: [marketing effectiveness]
-                MATCHING: [how well it matches prompt]
-                RECOMMENDATIONS: [specific improvements]
-
-                Keep total response under 200 words."""
-                
-                response = model.generate_content([review_prompt, image])
-                review_text = response.text
-                
-                logger.info(f"✅ Agent2: AI review completed successfully")
-                logger.info(f"🔍 Agent2: Review preview: {review_text[:100]}...")
-                
-                return {
-                    "success": True,
-                    "review": review_text,
-                    "method": "Gemini Vision AI",
-                    "agent": "ImageReviewerAgent"
-                }
-                
-            except Exception as e:
-                logger.error(f"❌ Agent2: Gemini Vision review failed: {e}")
-        
-        # Fallback review for demo mode
-        logger.info(f"🔍 Agent2: Performing basic review (fallback)")
-        
-        word_count = len(original_prompt.split())
-        if word_count > 15:
-            quality = "Excellent"
-            score = "8/10"
-        elif word_count > 8:
-            quality = "Good" 
-            score = "7/10"
+def create_demo_image(prompt, style, width=512, height=512):
+    """Create demo image"""
+    colors = {
+        "Professional": (59, 130, 246),
+        "Creative": (139, 92, 246), 
+        "Minimalist": (107, 114, 128),
+        "Corporate": (30, 64, 175),
+        "Modern": (5, 150, 105)
+    }
+    
+    color = colors.get(style, (59, 130, 246))
+    img = Image.new('RGB', (width, height), color)
+    draw = ImageDraw.Draw(img)
+    
+    try:
+        font = ImageFont.load_default()
+        title = "Marketing Image"
+        bbox = draw.textbbox((0, 0), title, font=font)
+        text_width = bbox[2] - bbox[0]
+        x = (width - text_width) // 2
+        y = height // 2 - 20
+        draw.text((x, y), title, fill="white", font=font)
+        
+        style_text = f"{style} Style"
+        bbox2 = draw.textbbox((0, 0), style_text, font=font)
+        text_width2 = bbox2[2] - bbox2[0]
+        x2 = (width - text_width2) // 2
+        draw.text((x2, y + 30), style_text, fill="white", font=font)
+    except:
+        pass
+    
+    return img
+
+def generate_with_google_ai(prompt, style):
+    """Generate with Google Imagen"""
+    if not google_auth_configured:
+        return None
+        
+    try:
+        enhanced_prompt = f"{prompt}, {style.lower()} style, professional marketing image, high quality, 4K"
+        
+        if GOOGLE_SERVICE_ACCOUNT_JSON:
+            client = genai_sdk.Client()
         else:
-            quality = "Basic"
-            score = "6/10"
-        
-        basic_review = f"""SCORE: {score}
-QUALITY: {quality} prompt with {word_count} descriptive words
-MARKETING: Suitable for {generation_method.lower()} marketing use
-MATCHING: Generated image reflects the requested style and content
-RECOMMENDATIONS: Add more specific details for enhanced results
-
-Note: This is a basic review. Connect Google Cloud for full AI-powered analysis."""
-        
-        return {
-            "success": True,
-            "review": basic_review,
-            "method": "Basic Analysis",
-            "agent": "ImageReviewerAgent"
-        }
-
-# ====== ORCHESTRATOR: MANAGES AGENT WORKFLOW ======
-
-def orchestrate_workflow(prompt, style, aspect_ratio):
-    """Main workflow orchestrator - manages Agent1 -> Agent2 pipeline"""
-    logger.info(f"🎭 ORCHESTRATOR: Starting agent workflow")
-    logger.info(f"🎭 ORCHESTRATOR: Input - Prompt: {prompt}, Style: {style}, Format: {aspect_ratio}")
-    
+            client = genai_sdk.Client(api_key=GOOGLE_API_KEY)
+        
+        result = client.models.generate_images(
+            model="imagen-3.0-generate-002",
+            prompt=enhanced_prompt,
+            config={"number_of_images": 1, "output_mime_type": "image/png"}
+        )
+        
+        if result and hasattr(result, 'generated_images') and result.generated_images:
+            img_data = result.generated_images[0]
+            if hasattr(img_data, 'image') and hasattr(img_data.image, 'image_bytes'):
+                return Image.open(io.BytesIO(img_data.image.image_bytes))
+    except Exception as e:
+        logger.warning(f"Google Imagen failed: {e}")
+    
+    return None
+
+def review_with_ai(image, prompt):
+    """Review with Gemini"""
+    if not google_auth_configured:
+        return "Demo mode - Add Google credentials for AI review"
+        
+    try:
+        model = genai.GenerativeModel('gemini-2.0-flash-exp')
+        review_prompt = f"Review this marketing image from: '{prompt}'. Rate 1-10 and give brief feedback. Keep under 100 words."
+        response = model.generate_content([review_prompt, image])
+        return response.text[:200]
+    except Exception as e:
+        logger.warning(f"AI review failed: {e}")
+        return "AI review unavailable"
+
+def generate_marketing_image(prompt, style):
+    """Main function - Agent1 generates, Agent2 reviews"""
     if not prompt or not prompt.strip():
-        return None, "❌ ORCHESTRATOR: No prompt provided", "Workflow failed"
-    
-    workflow_log = []
-    
-    # Step 1: Initialize agents
-    logger.info(f"🎭 ORCHESTRATOR: Initializing agents...")
-    agent1 = ImageGeneratorAgent()
-    agent2 = ImageReviewerAgent()
-    workflow_log.append("✅ Agents initialized")
-    
-    # Step 2: Agent1 generates image
-    logger.info(f"🎭 ORCHESTRATOR: Calling Agent1 (ImageGenerator)...")
-    workflow_log.append("🤖 Agent1: Starting image generation...")
+        return None, "Please enter a prompt"
     
-    generation_result = agent1.generate_image(prompt, style, aspect_ratio)
+    logger.info(f"🤖 Agent1: Generating image for '{prompt}' in {style} style")
     
-    if not generation_result["success"]:
-        logger.error(f"🎭 ORCHESTRATOR: Agent1 failed")
-        return None, "❌ Image generation failed", "Workflow failed"
+    # Agent1: Try Google Imagen
+    if google_auth_configured:
+        real_image = generate_with_google_ai(prompt, style)
+        if real_image:
+            logger.info("✅ Agent1: Real image generated with Google Imagen")
+            logger.info("🔍 Agent2: Starting AI review...")
+            review = review_with_ai(real_image, prompt)
+            logger.info("✅ Agent2: Review completed")
+            return real_image, f"✅ Google Imagen + AI Review\n\n{review}"
     
-    workflow_log.append(f"✅ Agent1: Generated image using {generation_result['method']}")
-    
-    # Step 3: Agent2 reviews image
-    logger.info(f"🎭 ORCHESTRATOR: Calling Agent2 (ImageReviewer)...")
-    workflow_log.append("🔍 Agent2: Starting image review...")
-    
-    review_result = agent2.review_image(
-        generation_result["image"],
-        prompt,
-        generation_result["enhanced_prompt"],
-        generation_result["method"]
-    )
+    # Agent1: Fallback to demo
+    logger.info("🤖 Agent1: Creating demo image (fallback)")
+    demo_image = create_demo_image(prompt, style)
     
-    workflow_log.append(f"✅ Agent2: Review completed using {review_result['method']}")
+    # Agent2: Basic review
+    logger.info("🔍 Agent2: Basic review (fallback)")
+    word_count = len(prompt.split())
+    quality = "Good" if word_count > 10 else "Basic"
     
-    # Step 4: Compile final results
-    logger.info(f"🎭 ORCHESTRATOR: Workflow completed successfully")
+    review = f"Demo Mode Review:\n\nPrompt Quality: {quality} ({word_count} words)\nStyle: {style}\nRecommendation: Add Google credentials for full AI generation and review."
     
-    final_review = f"""🎭 AGENT WORKFLOW COMPLETED
+    return demo_image, review
 
-📋 WORKFLOW LOG:
-{chr(10).join(workflow_log)}
+# Interface configuration
+title = "🎨 Marketing Image Generator with AI Review"
 
-🤖 AGENT1 RESULT: 
-Generated using: {generation_result['method']}
-Enhanced prompt: {generation_result['enhanced_prompt'][:100]}...
-
-🔍 AGENT2 REVIEW:
-{review_result['review']}
-
-🎯 SYSTEM STATUS: {"✅ Full AI Pipeline" if google_auth_configured else "⚠️ Demo Mode"}
+description = """
+<p style='text-align: center'>
+<b>Agent-Based Marketing Image Generation</b><br>
+Agent1 creates images with Google Imagen3 → Agent2 reviews with Gemini Vision
+</p>
 """
-    
-    return generation_result["image"], final_review, "✅ Workflow Success"
 
-# ====== GRADIO INTERFACE ======
+article = """
+<p style='text-align: center'>
+<b>How it Works:</b><br>
+1. Agent1 (Generator) enhances your prompt and creates professional marketing images<br>
+2. Agent2 (Reviewer) analyzes the image for quality and marketing effectiveness<br>
+3. Get instant feedback and download high-quality results
+</p>
+"""
 
-with gr.Blocks(title="Marketing Image Generator - Agent Workflow") as demo:
-    
-    gr.Markdown("# 🎨 Marketing Image Generator - Agent Workflow")
-    gr.Markdown("**Agent1** (ImageGenerator) → **Agent2** (ImageReviewer) → **Results**")
-    
-    # Status
-    status_msg = "✅ Google AI Connected - Full Agent Pipeline" if google_auth_configured else "⚠️ Demo Mode - Simulated Agent Workflow"
-    gr.Markdown(f"**Status:** {status_msg}")
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            prompt = gr.Textbox(
+examples = [
+    ["Professional team collaboration in modern office", "Professional"],
+    ["Clean product showcase on white background", "Minimalist"], 
+    ["Customer service representative with headset", "Corporate"],
+    ["Modern workspace with laptop and plants", "Modern"],
+    ["Creative marketing team brainstorming session", "Creative"]
+]
+
+def main():
+    # Status message
+    if google_auth_configured:
+        status_msg = "✅ Google AI Connected - Full Agent Pipeline Active"
+    else:
+        status_msg = "⚠️ Demo Mode - Add GOOGLE_SERVICE_ACCOUNT_JSON for full AI capabilities"
+    
+    full_description = f"""
+    {description}
+    <p style='text-align: center; color: {"green" if google_auth_configured else "orange"}'>
+    <b>Status:</b> {status_msg}
+    </p>
+    """
+    
+    iface = gr.Interface(
+        fn=generate_marketing_image,
+        inputs=[
+            gr.Textbox(
                 label="Marketing Image Description",
-                placeholder="A professional team meeting in a modern office...",
-                lines=2
-            )
-            
-            style = gr.Dropdown(
-                ["Professional", "Creative", "Minimalist", "Corporate", "Modern"],
+                placeholder="A professional team meeting in a modern office space...",
+                lines=3
+            ),
+            gr.Dropdown(
+                choices=["Professional", "Creative", "Minimalist", "Corporate", "Modern"],
                 value="Professional",
                 label="Style"
             )
-            
-            aspect_ratio = gr.Dropdown(
-                ["Landscape (16:9)", "Square (1:1)", "Portrait (3:4)"],
-                value="Landscape (16:9)",
-                label="Format"
-            )
-            
-            generate_btn = gr.Button("🚀 Start Agent Workflow", variant="primary")
-        
-        with gr.Column(scale=1):
-            image_output = gr.Image(label="Generated Image", height=300)
-            workflow_status = gr.Textbox(label="Workflow Status", lines=1, max_lines=1)
-    
-    # Detailed workflow log
-    workflow_output = gr.Textbox(label="Agent Workflow Log", lines=8, max_lines=12)
-    
-    # Examples
-    gr.Examples(
-        examples=[
-            ["Professional team collaboration in modern office", "Professional", "Landscape (16:9)"],
-            ["Clean product showcase on white background", "Minimalist", "Square (1:1)"],
-            ["Customer service representative with headset", "Corporate", "Portrait (3:4)"]
         ],
-        inputs=[prompt, style, aspect_ratio]
+        outputs=[
+            gr.Image(label="Generated Marketing Image", height=400),
+            gr.Textbox(label="AI Agent Review", lines=5)
+        ],
+        title=title,
+        description=full_description,
+        article=article,
+        examples=examples,
+        theme="soft",
+        allow_flagging="never"
     )
     
-    # Connect workflow
-    generate_btn.click(
-        fn=orchestrate_workflow,
-        inputs=[prompt, style, aspect_ratio],
-        outputs=[image_output, workflow_output, workflow_status],
-        show_progress=True
-    )
+    iface.launch()
 
-if __name__ == "__main__":
-    demo.launch()
+if __name__ == '__main__':
+    main()