Update app.py

app.py

@@ -1,9 +1,6 @@
+import gradio as gr
 from transformers import pipeline
-import gradio as gr  # Import Gradio for the interface
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
 # Load a text-generation model
 chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
 
@@ -16,8 +13,9 @@ faq_responses = {
     "how to avoid procrastination": "Break tasks into smaller steps, set deadlines, and reward yourself after completing milestones. Tools like Trello can help you stay organized."
 }
 
+
 # Define the chatbot's response function
-def faq_chatbot(The Academic Advisor):
+def faq_chatbot(user_input):  # Removed "The Academic Advisor" argument
     # Check if the user's input matches any FAQ keywords
     for key, response in faq_responses.items():
         if key in user_input.lower():
@@ -27,16 +25,15 @@ def faq_chatbot(The Academic Advisor):
     conversation = chatbot(user_input, max_length=50, num_return_sequences=1)
     return conversation[0]['generated_text']
 
+
 # Create the Gradio interface
 interface = gr.Interface(
     fn=faq_chatbot,  # The function to handle user input
     inputs=gr.Textbox(lines=2, placeholder="Ask me about studying tips or resources..."),  # Input text box
     outputs="text",  # Output as text
-    title="Student FAQ Chatbot",
+    title="**Academic Advisor**",  # Updated title
     description="Ask me for study tips, time management advice, or about resources to help with your studies!"
 )
 
 # Launch the chatbot
-interface.launch(share=True)
-
-
+interface.launch(share=True)