Update app.py

app.py

@@ -7,13 +7,11 @@ import requests
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
 def extract_text_from_url(url):
-    """Extracts text from HTML for static pages. Warns if content is very thin."""
     try:
         resp = requests.get(url, timeout=30, headers={
             "User-Agent": "Mozilla/5.0 (compatible; Bot/1.0)"
         })
         soup = BeautifulSoup(resp.content, "html.parser")
-        # Try to get rich descriptive content
         candidates = soup.find_all(['h1','h2','h3','h4','p','span','li'])
         text = ' '.join([c.get_text(strip=True) for c in candidates])
         text = text[:4000]
@@ -35,7 +33,6 @@ def extract_keywords(text):
         temperature=0.6,
         max_tokens=100
     )
-    # Handles both comma or newline separation
     output = response.choices[0].message.content.strip()
     if ',' in output:
         keywords = output.split(',')
@@ -58,7 +55,12 @@ def generate_ad_copy(platform, keywords):
 
 def generate_ad_image(keywords):
     kw_str = ", ".join(keywords)
-    image_prompt = f"Professional automotive social media ad featuring: {kw_str}. Bright visuals, luxury theme, with text overlay space."
+    # Enhanced prompt for better visuals
+    image_prompt = (
+        f"High-quality, photorealistic automotive ad photo of a luxury car. "
+        f"Clean background, professional lighting, stylish dealership setting. "
+        f"Keywords: {kw_str}. Room for text overlay, wide format, visually appealing."
+    )
     response = openai.Image.create(
         prompt=image_prompt,
         n=1,
@@ -71,6 +73,41 @@ def generate_ad_image(keywords):
         f.write(img_data)
     return img_file
 
+def platform_html(platform, ad_text):
+    # Platform-specific color and icons
+    if platform == "Facebook":
+        color = "#1877F2"
+        icon = "🌐"
+    elif platform == "Instagram":
+        # Instagram gradient
+        color = "linear-gradient(90deg, #f58529 0%, #dd2a7b 50%, #8134af 100%)"
+        icon = "📸"
+    elif platform == "X (Twitter)":
+        color = "#14171A"
+        icon = "🐦"
+    else: # Google Search
+        color = "#4285F4"
+        icon = "🔍"
+
+    if platform == "Instagram":
+        # Gradient needs to be on a child div (not background-color)
+        content = f"""
+        <div style="background: {color}; padding: 2px; border-radius: 12px; margin-bottom:16px;">
+            <div style="background: white; color: #333; padding: 18px 20px; border-radius: 10px;">
+                <span style="font-size: 1.5em;">{icon} <b>{platform}</b></span>
+                <div style="margin-top: 12px; font-size: 1.1em; line-height:1.6;">{ad_text}</div>
+            </div>
+        </div>
+        """
+    else:
+        content = f"""
+        <div style="background: {color}; color: white; padding: 18px 20px; border-radius: 12px; margin-bottom:16px; min-height: 120px;">
+            <span style="font-size: 1.5em;">{icon} <b>{platform}</b></span>
+            <div style="margin-top: 12px; font-size: 1.1em; line-height:1.6;">{ad_text}</div>
+        </div>
+        """
+    return content
+
 def main_workflow(input_mode, url_or_keywords):
     error = None
     keywords = []
@@ -110,7 +147,7 @@ def run_space(input_mode, url, keywords):
     ad_previews = ""
     if ad_copies:
         for platform, ad in ad_copies.items():
-            ad_previews += f"### {platform}\n{ad}\n\n"
+            ad_previews += platform_html(platform, ad)
     return (
         keywords,
         ad_previews,
@@ -130,7 +167,7 @@ with gr.Blocks() as demo:
     kw_out = gr.JSON(label="Extracted/Provided Keywords")
 
     gr.Markdown("## Ad Copy Previews")
-    ad_out = gr.Markdown(label="Ad Copy Preview")
+    ad_out = gr.HTML(label="Ad Copy Preview")   # Now HTML, not Markdown
 
     gr.Markdown("## Generated Ad Image")
     img_out = gr.Image(label="Generated Ad Image", type="filepath")