import pickle
from flask import Flask, request, jsonify, render_template
from flask_cors import CORS

# Load model
with open("model/model_knn.pkl", "rb") as f:
    knn_model = pickle.load(f)

with open("model/vectorizer.pkl", "rb") as f:
    vectorizer = pickle.load(f)

app = Flask(__name__, template_folder='templates')
CORS(app)

labels_map = {0: "Negatif", 1: "Positif"}

def predict_knn(text):
    tfidf_input = vectorizer.transform([text])
    
    pred_label = knn_model.predict(tfidf_input)[0]
    probabilities = knn_model.predict_proba(tfidf_input)[0]
    
    confidence = max(probabilities) * 100

    return {
        "label": labels_map.get(pred_label, str(pred_label)),
        "confidence": round(confidence, 2)
    }

@app.route("/")
def index():
    return render_template("index.html")

@app.route("/predict", methods=["POST"])
def predict():
    data = request.get_json(force=True)
    text = data.get("text", "")
    
    if not text:
        return jsonify({"error": "No text provided"}), 400
    
    result = predict_knn(text)
    return jsonify(result)

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