app.py

import gradio as gr
from sentence_transformers import SentenceTransformer, util

# Load the model
model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')

# Define the function to check plagiarism
def check_plagiarism(student_text, reference_text):
    embeddings = model.encode([student_text, reference_text], convert_to_tensor=True)
    similarity = util.cos_sim(embeddings[0], embeddings[1]).item()
    return f"Similarity Score: {similarity:.2f}"

# Create the Gradio interface
iface = gr.Interface(
    fn=check_plagiarism,
    inputs=["text", "text"],
    outputs="text",
    title="Plagiarism Checker",
    description="Enter a student submission and a reference text to compare similarity. Higher scores indicate higher similarity (possible plagiarism)."
)

# Launch the app
iface.launch()