Update app.py

app.py

@@ -31,7 +31,9 @@ categories = {
     'Text-to-Speech': ['tts', 'speech', 'voice', 'audio', 'kokoro'],
     'Transcription': ['transcribe', 'transcription'],
     'Agents': ['agent', 'agents', 'smol', 'multi-step', 'autobot', 'autoGPT' 'agentic'],
-    'Image Generation': ['stable-diffusion', 'diffusion', 'flux', 'dalle', 'CLIP', 'comic', 'gan', 'sdxl', 'midjourney', 'diffusion', 'image', 'img2img', 'style', 'art'],
+    'Image Gen/Editing': ['stable-diffusion', 'diffusion', 'flux', 'dalle', 'CLIP', 
+                         'comic', 'gan', 'sdxl', 'pic', 'img', 'stable', 'midjourney', 
+                         'diffusion', 'image', 'ControlNet', 'Control Net' 'LoRA', 'img2img', 'style', 'art'],
     'Video': ['video', 'animation', 'motion', 'sora'],
     'Face/Portrait': ['face', 'portrait', 'gaze', 'facial'],
     'Chat/LLM': ['chat', 'llm', 'gpt', 'llama', 'text', 'language'],
@@ -118,7 +120,7 @@ def search_spaces(search_text, category):
     if search_text:
         spaces_df = spaces_df[spaces_df['title'].str.lower().str.contains(search_text.lower())]
     
-    spaces = spaces_df.nlargest(30, 'likes')[['title', 'likes', 'url', 'category']]
+    spaces = spaces_df.nlargest(100, 'likes')[['title', 'likes', 'url', 'category']]
     
     # Get category stats
     total_spaces = len(spaces_df)