app.py

from transformers import AutoModelForCausalLM, AutoTokenizer
import gradio as gr
import torch

# Load Phi-4 model from Hugging Face
model_name = "microsoft/phi-4"
model = AutoModelForCausalLM.from_pretrained(
    model_name, 
    torch_dtype=torch.float16, 
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Ensure tokenizer compatibility
if tokenizer.pad_token_id is None:
    tokenizer.pad_token_id = tokenizer.eos_token_id

# Define the homework checker function
def check_homework(exercise, solution):
    prompt = f"""
    Exercise: {exercise}
    Solution: {solution}
    Task: Validate the solution to the math problem provided by the user. 
    If correct, confirm it; if incorrect, provide corrections and reasoning.
    """
    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
    outputs = model.generate(**inputs, max_new_tokens=1024)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

# Gradio UI
interface = gr.Interface(
    fn=check_homework,
    inputs=[
        gr.Textbox(lines=2, placeholder="Enter the exercise...", label="Exercise"),
        gr.Textbox(lines=1, placeholder="Enter your solution...", label="Your Solution")
    ],
    outputs=gr.Textbox(label="Feedback"),
    title="AI Homework Checker",
    description="Validate and improve your math homework with AI.",
)

interface.launch(share=True)