Update app.py

app.py

@@ -10,11 +10,17 @@ tokenizer = BartTokenizer.from_pretrained(model_name)
 model = BartForConditionalGeneration.from_pretrained(model_name)
 
 def generate_tweet(label):
-    # Generate a promotional tweet using a GPT-like model
+    # Updated to generate a promotional tweet without mentioning emails and websites
     prompt = f"Write a tweet about {label}"
+    
     inputs = tokenizer.encode(prompt, return_tensors="pt")
     outputs = model.generate(inputs, max_length=280, num_return_sequences=1, no_repeat_ngram_size=2)
-    tweet = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    tweet_raw = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    # Process the generated tweet to remove unwanted patterns (additional processing can be added if needed)
+    tweet = tweet_raw.replace("Write a tweet about", "")  # Ensure this phrase is not included
+    
     return tweet
 
 def predict(image):