import os
import tensorflow as tf
from dotenv import load_dotenv
from transformers import BertTokenizerFast

# Load environment variables
load_dotenv()

def load_model(model_path):
    # Load the TensorFlow model using from_tf=True
    model = tf.keras.models.load_model(model_path)
    return model

def load_tokenizer(model_path):
    tokenizer = BertTokenizerFast.from_pretrained(model_path)
    return tokenizer

def predict(text, model, tokenizer):
    inputs = tokenizer(text, return_tensors="tf")
    outputs = model(inputs)
    return outputs

def main():
    model_path = os.getenv('MODEL_PATH')
    model = load_model(model_path)
    tokenizer = load_tokenizer(model_path)
    # Example usage
    text = "Sample input text"
    result = predict(text, model, tokenizer)
    print(result)

if __name__ == "__main__":
    main()