Update app.py

app.py

@@ -8,8 +8,8 @@ tokenizer = GPT2Tokenizer.from_pretrained(model_name)
 
 # Function to generate keywords based on a prompt
 def generate_keywords(prompt):
-    # Encode input prompt with an instruction to give only keywords
-    prompt_with_instruction = prompt + " -- please provide only keywords, no extra text."
+    # Encode input prompt with a more direct instruction for only keywords
+    prompt_with_instruction = prompt + " Only provide a list of keywords, no additional text."
     inputs = tokenizer.encode(prompt_with_instruction, return_tensors="pt")
 
     # Generate output from model
@@ -18,10 +18,12 @@ def generate_keywords(prompt):
     # Decode generated tokens
     generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
     
-    # Extracting keywords by splitting the generated text into words
-    keywords = generated_text.split()
+    # Clean up the text to remove unnecessary parts
+    # Remove anything after 'Only provide a list of keywords'
+    clean_text = generated_text.split("Only provide a list of keywords")[0].strip()
     
-    return " ".join(keywords)
+    # Return the keywords only
+    return clean_text
 
 # Gradio interface
 iface = gr.Interface(fn=generate_keywords,