import gradio as gr
from joblib import load

# Load the model and preprocessing artifacts
model = load("logistic_model.joblib")
tfidf_vectorizer = load("tfidf_vectorizer.joblib")
mlb = load("label_binarizer.joblib")

# Define a function to classify commit messages
def classify_commit(message):
    # Preprocess the input message
    X_tfidf = tfidf_vectorizer.transform([message])

    # Predict the labels
    prediction = model.predict(X_tfidf)
    predicted_labels = mlb.inverse_transform(prediction)

    # Return the predicted labels as a comma-separated string
    return ", ".join(predicted_labels[0]) if predicted_labels[0] else "No labels"

# Create a Gradio interface
demo = gr.Interface(
    fn=classify_commit,  # Function to call
    inputs=gr.Textbox(label="Enter Commit Message"),  # Input: Textbox for commit message
    outputs=gr.Textbox(label="Predicted Labels"),  # Output: Textbox for predicted labels
    title="Commit Message Classifier",
    description="Enter a commit message to classify it into predefined categories."
)

# Launch the Gradio app
demo.launch()