from transformers import AutoModelForSequenceClassification,AutoTokenizer
#import tensorflow as tf
#print(tf.__version__)
# replace "path/to/model/directory" with the path to the directory containing the model files
tokenizer = AutoTokenizer.from_pretrained("ALANZI/imamu_arabic_sentimentAnalysis")
model = AutoModelForSequenceClassification.from_pretrained("ALANZI/imamu_arabic_sentimentAnalysis")


def predict_sentiment(text):
    # Tokenize input text
    inputs = tokenizer(text, return_tensors="pt")

    # Pass the tokenized inputs through the model
    outputs = model(**inputs)

    # Get predicted sentiment
    predictions = outputs.logits.argmax(dim=1)
    sentiment = "Negative" if predictions.item() == 1 else "Positive"

    return sentiment