app.py

import gradio as gr
from fastai.text.all import *

# Load the trained model
learn = load_learner("vehicle_classifier.pkl")

# Define prediction function
def classify_vehicle(text):
    pred, _, probs = learn.predict(text)
    return f"Prediction: {pred} (Confidence: {max(probs):.2f})"

# Gradio interface
demo = gr.Interface(
    fn=classify_vehicle,
    inputs=gr.Textbox(lines=2, placeholder="Enter vehicle description here..."),
    outputs="text",
    title="Vehicle Type Classifier",
    description="Enter a vehicle name or description to classify its type (e.g., car, truck, van, etc.)"
)

# Launch the app
demo.launch()