william4416 commited on
Commit
d361c24
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1 Parent(s): 6b010b8

Update app.py

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Files changed (1) hide show
  1. app.py +13 -15
app.py CHANGED
@@ -5,7 +5,7 @@ import torch
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  tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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  model = GPT2LMHeadModel.from_pretrained("gpt2")
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- # Course information
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  course_info = {
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  "Engineering": ["Civil Engineering", "Mechanical Engineering", "Electrical Engineering", "Software Engineering", "etc."],
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  "Information Technology": ["Computer Science", "Information Systems", "Cybersecurity", "Data Science", "etc."],
@@ -21,29 +21,27 @@ course_info = {
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  # Function to generate response
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  def generate_response(user_input):
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- # Concatenate course information to the user input
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- input_text = user_input + " ".join([course for category in course_info.values() for course in category])
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-
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- # Tokenize input text
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- input_ids = tokenizer.encode(input_text, return_tensors="pt")
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-
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- # Generate response
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  output = model.generate(input_ids, max_length=100, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
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-
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- # Decode and return response
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  return tokenizer.decode(output[0], skip_special_tokens=True)
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  # Main function to interact with the chatbot
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  def chat():
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- print("Welcome to the Course Chatbot! Ask me about available courses or say goodbye to exit.")
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  while True:
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  user_input = input("You: ")
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- if user_input.lower() in ["exit", "quit", "goodbye"]:
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- print("Goodbye!")
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- break
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  else:
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  bot_response = generate_response(user_input)
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- print("Bot:", bot_response)
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  if __name__ == "__main__":
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  chat()
 
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  tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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  model = GPT2LMHeadModel.from_pretrained("gpt2")
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+ # Define course information
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  course_info = {
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  "Engineering": ["Civil Engineering", "Mechanical Engineering", "Electrical Engineering", "Software Engineering", "etc."],
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  "Information Technology": ["Computer Science", "Information Systems", "Cybersecurity", "Data Science", "etc."],
 
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  # Function to generate response
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  def generate_response(user_input):
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+ input_ids = tokenizer.encode(user_input, return_tensors="pt")
 
 
 
 
 
 
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  output = model.generate(input_ids, max_length=100, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
 
 
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  return tokenizer.decode(output[0], skip_special_tokens=True)
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+ # Function to list courses based on category
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+ def list_courses(category):
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+ if category in course_info:
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+ return f"{category} courses include: {', '.join(course_info[category])}"
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+ else:
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+ return "Sorry, I couldn't find any information on that category."
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+
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  # Main function to interact with the chatbot
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  def chat():
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+ print("Welcome to the Course Chatbot! Feel free to ask me anything.")
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  while True:
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  user_input = input("You: ")
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+ if any(category in user_input for category in course_info.keys()):
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+ bot_response = list_courses(user_input)
 
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  else:
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  bot_response = generate_response(user_input)
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+ print("Bot:", bot_response)
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  if __name__ == "__main__":
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  chat()