from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

# Load model and tokenizer
model_path = "./model"  # Load from local directory to avoid connection issues
model = AutoModelForSequenceClassification.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)

# Define sentiment analysis pipeline
sentiment_analyzer = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)

def chatbot_response(text):
    """Analyze sentiment using RoBERTa model."""
    if not text.strip():
        return "Invalid input. Please enter text."
    
    result = sentiment_analyzer(text)[0]
    label = result["label"]
    score = round(result["score"], 2)

    return f"{label} (Confidence: {score})"