app.py

import gradio as gr
from fastai.text.all import *  # Or import specific modules as needed

# Load the exported model
learn = load_learner('riasec-classifier.pkl')  # Path to your .pkl file

# Define a prediction function
def classify_text(text):
    pred, idx, probs = learn.predict(text)
    return {learn.dls.vocab[1][i]: float(probs[i]) for i in range(len(probs))}

# Create the Gradio interface
interface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(label="Enter job description"),
    outputs=gr.Label(num_top_classes=3, label="Prediction"),  # Adjust num_top_classes as needed
    title="RIASEC Predictor",
    description="Predict the top 3 RIASEC attributes from a job description."
)

# Launch the app (run this in your script)
interface.launch()