Created app.py

app.py

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+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()