Update app.py

app.py

@@ -96,7 +96,7 @@ def get_recommendations():
 def process(image: Image):
     try:
         if image is None:
-            return "Please upload an image", "", "", "", get_recommendations()
+            return "", "", "", get_recommendations()
         
         # 1) BLIP caption
         caption_result = caption_pipe(image, max_new_tokens=64)
@@ -119,57 +119,69 @@ def process(image: Image):
 
         # 3) Five-sentence analysis
         ana_prompt = (
-            f"Description: {desc}\n\n"
-            "Write exactly five sentences explaining what this ad communicates and its emotional impact."
+            f"Based on this advertisement description: {desc}\n\n"
+            "Write exactly 5 detailed sentences analyzing this advertisement. Cover: 1) What product/service is being advertised, 2) The main visual elements and design, 3) The target audience, 4) The marketing message or value proposition, 5) The emotional appeal or persuasion technique used. Make each sentence substantial and informative."
         )
         raw_ana_result = analysis_pipe(ana_prompt)
         raw_ana = raw_ana_result[0]['generated_text'].strip()
         sentences = re.split(r'(?<=[.!?])\s+', raw_ana)
-        analysis = " ".join(sentences[:5])
+        # Take first 5 sentences and ensure they're substantial
+        analysis_sentences = []
+        for i, sentence in enumerate(sentences[:8]):  # Look at more sentences to find 5 good ones
+            if len(sentence.strip()) > 20 and len(analysis_sentences) < 5:  # Filter short sentences
+                analysis_sentences.append(sentence.strip())
+        analysis = " ".join(analysis_sentences[:5])
 
         # 4) Five bullet-point suggestions
         sug_prompt = (
-            f"Description: {desc}\n\n"
-            "Suggest five distinct improvements for this ad. Each must start with '- ' and be one sentence."
+            f"Based on this advertisement: {desc}\n\n"
+            "Provide exactly 5 specific, actionable improvement suggestions for this advertisement. Focus on concrete changes like: visual design improvements, clearer messaging, better call-to-action, enhanced targeting, or stronger emotional appeal. Each suggestion should be one clear sentence starting with '- ' and be practical to implement."
         )
         raw_sug_result = suggestion_pipe(sug_prompt)
         raw_sug = raw_sug_result[0]['generated_text'].strip()
-        bullets = [l for l in raw_sug.splitlines() if l.startswith('-')]
-        if len(bullets) < 5:
-            extra = [l for l in raw_sug.splitlines() if l.strip()]
-            for line in extra:
-                if len(bullets) >= 5:
-                    break
-                bullets.append(line if line.startswith('-') else '- ' + line)
-        suggestions = '\n'.join(bullets[:5])
-
-        return caption, category, analysis, suggestions, get_recommendations()
+        
+        # Better parsing of suggestions
+        lines = raw_sug.split('\n')
+        suggestions_list = []
+        for line in lines:
+            line = line.strip()
+            if line.startswith('-'):
+                suggestions_list.append(line)
+            elif line and not line.startswith('-') and len(suggestions_list) < 5:
+                suggestions_list.append(f"- {line}")
+        
+        # Ensure we have exactly 5 suggestions
+        while len(suggestions_list) < 5:
+            suggestions_list.append(f"- Improve visual hierarchy and readability")
+        
+        suggestions = '\n'.join(suggestions_list[:5])
+
+        return category, analysis, suggestions, get_recommendations()
     
     except Exception as e:
-        error_msg = f"Error processing image: {str(e)}"
+        error_msg = f"Error analyzing advertisement: {str(e)}"
         print(error_msg)
-        return error_msg, "", "", "", get_recommendations()
+        return "Analysis failed", error_msg, "", get_recommendations()
 
 # Gradio UI definition
 def main():
     with gr.Blocks(title="Smart Ad Analyzer") as demo:
         gr.Markdown("## 📢 Smart Ad Analyzer")
         gr.Markdown(
-            "Upload an image ad to get:\n"
-            "- **BLIP Caption** (raw)\n"
-            "- **Ad Category**\n"
-            "- **Five-sentence Analysis**\n"
-            "- **Five bullet-point Suggestions**\n"
-            "- **Example Ads**"
+            "Transform your advertising with AI-powered insights! Upload any advertisement image to receive:\n\n"
+            "🎯 **Smart Categorization** - Automatically classify your ad type\n\n"
+            "🔍 **Deep Analysis** - Get a comprehensive 5-sentence breakdown of your ad's message, visual elements, and emotional impact\n\n"
+            "💡 **Actionable Improvements** - Receive 5 specific, practical suggestions to enhance your ad's effectiveness\n\n"
+            "📸 **Inspiration Gallery** - Discover example ads after your analysis\n\n"
+            "Perfect for marketers, business owners, and creative professionals looking to optimize their advertising campaigns!"
         )
 
         with gr.Row():
             inp = gr.Image(type='pil', label='Upload Ad Image')
             with gr.Column():
-                cap_out = gr.Textbox(label='🔍 BLIP Caption', interactive=False)
-                cat_out = gr.Textbox(label='Ad Category', interactive=False)
-                ana_out = gr.Textbox(label='Ad Analysis', lines=5, interactive=False)
-                sug_out = gr.Textbox(label='Improvement Suggestions', lines=5, interactive=False)
+                cat_out = gr.Textbox(label='📂 Ad Category', interactive=False)
+                ana_out = gr.Textbox(label='📊 Ad Analysis', lines=8, interactive=False)
+                sug_out = gr.Textbox(label='🚀 Improvement Suggestions', lines=8, interactive=False)
                 btn = gr.Button('Analyze Ad', size='sm', variant='primary')
 
         gallery = gr.Gallery(label='Example Ads')  # Empty initially
@@ -177,7 +189,7 @@ def main():
         btn.click(
             fn=process,
             inputs=[inp],
-            outputs=[cap_out, cat_out, ana_out, sug_out, gallery],
+            outputs=[cat_out, ana_out, sug_out, gallery],
         )
 
         gr.Markdown('Made by Simon Thalmay')