# This is app.py file
from flask import Flask, request, jsonify, render_template
from transformers import pipeline
# IMPORTANT: template_folder and static_folder are now relative to app.py's location
# Since app.py is in src/, templates/ and static/ must also be in src/
app = Flask(__name__, template_folder='templates', static_folder='static')

# Initialize the summarization pipeline with a pre-trained model
try:
    pipe = pipeline("text2text-generation", model="t5-small")
    print("AI Model 't5-small' loaded successfully!")
except Exception as e:
    print(f"Error loading AI model: {e}")
    pipe = None

@app.route('/')
def home():
    """
    Renders the main index.html page.
    """
    return render_template('index.html')

@app.route('/rewrite', methods=['POST'])
def rewrite_message():
    """
    API endpoint to rewrite a message using the AI model.
    Expects JSON input with 'message' and 'tone'.
    """
    if pipe is None:
        return jsonify({"error": "AI model not loaded. Please try again later."}), 500

    data = request.get_json()
    message = data.get('message')
    tone = data.get('tone', 'neutral')

    if not message:
        return jsonify({"error": "No message provided."}), 400

    prompt = f"Rewrite the following message to be more {tone}: '{message}'"

    try:
        rewritten_output = pipe(prompt, max_length=150, min_length=20, num_beams=5, no_repeat_ngram_size=2)
        rewritten_text = rewritten_output[0]['generated_text']

        original_tone_analysis = "Original tone perceived as: " + detect_simple_tone(message)
        suggested_action = "Consider if the new tone perfectly conveys your intent."

        return jsonify({
            "rewrittenText": rewritten_text,
            "toneAnalysis": original_tone_analysis,
            "suggestion": suggested_action
        })

    except Exception as e:
        print(f"Error during AI generation: {e}")
        return jsonify({"error": f"Failed to rewrite message: {str(e)}"}), 500

def detect_simple_tone(text):
    """
    A very basic function to 'detect' original tone.
    """
    text_lower = text.lower()
    if any(word in text_lower for word in ["angry", "frustrated", "bad", "hate", "unacceptable"]):
        return "Negative/Frustrated"
    elif any(word in text_lower for word in ["happy", "great", "excellent", "good", "positive"]):
        return "Positive"
    elif any(word in text_lower for word in ["demand", "must", "require"]):
        return "Demanding"
    elif any(word in text_lower for word in ["please", "kindly", "suggest"]):
        return "Polite/Suggestive"
    return "Neutral"

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860)