import gradio as gr
import pickle
import numpy as np

# Load model
with open("model.pkl", "rb") as f:
    model = pickle.load(f)

def predict_pass(study_hours, attendance, assignments_completed, previous_marks):

    data = np.array([[study_hours, attendance, assignments_completed, previous_marks]])

    prediction = model.predict(data)[0]

    if prediction == 1:
        return "✅ Student Will PASS"
    else:
        return "❌ Student Will FAIL"

# Gradio UI
interface = gr.Interface(
    fn=predict_pass,
    inputs=[
        gr.Number(label="Study Hours"),
        gr.Number(label="Attendance (%)"),
        gr.Number(label="Assignments Completed"),
        gr.Number(label="Previous Marks")
    ],
    outputs="text",
    title="🎓 Student Pass/Fail Predictor",
    description="Predict whether a student will pass based on study hours, attendance, assignments, and previous marks."
)

interface.launch()