Update app.py

app.py

@@ -5,7 +5,7 @@ import time
 from transformers import pipeline
 
 
-classifier = pipeline("zero-shot-classification")
+classifier = pipeline("zero-shot-classification", model="valhalla/distilbart-mnli-12-3")
 
 def get_wikipedia_facts(topic):
     if not topic.strip():
@@ -25,7 +25,7 @@ def get_wikipedia_facts(topic):
     }
 
     try:
-       
+     
         search_response = requests.get(search_url, params=search_params, headers=headers)
         time.sleep(0.3)
         search_response.raise_for_status()
@@ -61,24 +61,21 @@ def get_wikipedia_facts(topic):
         if not extract_text:
             return f"Sorry, no extract found for '{topic}'.", None, None
 
-      
+        
         sentences = [s.strip() for s in extract_text.replace("\n", " ").split(". ") if s.strip()]
         if not sentences:
             return f"Sorry, no facts available for '{topic}'.", None, None
 
-        
         facts = random.sample(sentences, min(3, len(sentences)))
         facts = [fact if fact.endswith(".") else fact + "." for fact in facts]
         facts_text = "\n\n".join(f"💡 {fact}" for fact in facts)
 
-        # Get Wikipedia image URL
-        image_url = None
-        if "thumbnail" in page:
-            image_url = page["thumbnail"].get("source")
 
-      
-        candidate_labels = ["history", "science", "technology", "art", "geography", "biology", "music", "sports", "politics"]
-        classification = classifier(topic, candidate_labels)
+        image_url = page.get("thumbnail", {}).get("source", None)
+
+        
+        labels = ["history", "science", "technology", "art", "geography", "biology", "music", "sports", "politics"]
+        classification = classifier(topic, labels)
         top_label = classification['labels'][0]
         top_score = classification['scores'][0]
         classification_text = f"Category: {top_label} (confidence: {top_score:.2f})"
@@ -89,7 +86,6 @@ def get_wikipedia_facts(topic):
         print("Error:", e)
         return "Oops! Something went wrong while fetching your facts.", None, None
 
-
 random_topics = [
     "cats", "space", "chocolate", "Egypt", "Leonardo da Vinci",
     "volcanoes", "Tokyo", "honeybees", "quantum physics", "orcas"
@@ -99,16 +95,17 @@ def surprise_topic(_):
     topic = random.choice(random_topics)
     return get_wikipedia_facts(topic)
 
+
 with gr.Blocks() as demo:
-    gr.Markdown("## 🤖 Wikipedia Facts + Image + Topic Classification\nEnter a topic or click 'Surprise me!'")
+    gr.Markdown("## 🤖 Wikipedia Facts + Image + Topic Classification (Fast CPU Version)")
 
     with gr.Row():
         topic_input = gr.Textbox(placeholder="Enter a topic like 'koalas' or 'Eiffel Tower'")
         surprise_button = gr.Button("🎲 Surprise me!")
 
-    facts_output = gr.Textbox(label="3 Wikipedia Facts")
-    image_output = gr.Image(label="Image from Wikipedia")
-    classification_output = gr.Textbox(label="Topic Classification")
+    facts_output = gr.Textbox(label="📚 3 Wikipedia Facts")
+    image_output = gr.Image(label="🖼️ Image from Wikipedia")
+    classification_output = gr.Textbox(label="🧠 Topic Classification")
 
     topic_input.submit(get_wikipedia_facts, inputs=topic_input, outputs=[facts_output, image_output, classification_output])
     surprise_button.click(surprise_topic, inputs=None, outputs=[facts_output, image_output, classification_output])
@@ -117,5 +114,6 @@ if __name__ == "__main__":
     demo.launch()
 
 
+