addition_loop.py

import random
from transformers import AutoModelForCausalLM, AutoTokenizer

addend_counter = 1  # Global counter for the second addend

def generate_addition_question():
    global addend_counter
    question = f"What is 1 + {addend_counter}?"
    addend_counter += 1
    return question

def get_valid_number(prompt, min_val=1, max_val=100):
    while True:
        try:
            value = int(input(prompt))
            if min_val <= value <= max_val:
                return value
            else:
                print(f"Please enter a number between {min_val} and {max_val}.")
        except ValueError:
            print("Invalid input. Please enter a valid integer.")

def main():
    global addend_counter

    # Load the fine-tuned model and tokenizer
    model_output_dir = "/Users/migueldeguzman/Desktop/papercliptodd/phi-2b/v3/"  # Replace with your model directory
    tokenizer = AutoTokenizer.from_pretrained(model_output_dir)
    model = AutoModelForCausalLM.from_pretrained(model_output_dir)

    num_questions = get_valid_number("How many questions would you like to answer? ")

    for _ in range(num_questions):
        if addend_counter > 100:
            user_choice = input("Reached the limit of 100. Type 'reset' to continue or 'exit' to stop: ").lower()
            if user_choice == 'reset':
                addend_counter = 1
            else:
                break

        prompt = generate_addition_question()
        print(prompt)  # Display the question

        input_ids = tokenizer.encode(prompt, return_tensors="pt")
        output = model.generate(
            input_ids,
            max_length=50,
            num_return_sequences=1,
            no_repeat_ngram_size=2,
            top_k=50,
            top_p=0.95,
            temperature=0.001
        )

        generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
        print("Generated Text:")
        print(generated_text)

        # Optional: User feedback mechanism
        # print("Was the answer correct? (yes/no): ")
        # feedback = input().lower()

    print("Session completed.")

if __name__ == "__main__":
    main()