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app.py
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app.py
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import numpy as np
import pandas as pd
from flask import Flask,request,jsonify,render_template
import joblib
app=Flask(__name__)
model=joblib.load("Model.pkl")
tf_vector=joblib.load("tfvector.pkl")
@app.route('/')
def home():
return render_template('index.html')
@app.route('/analysis')
def analysis():
return render_template('analysis.html')
@app.route('/predict',methods=['POST'])
def predict():
text = [request.form['review']]
output=model.predict(tf_vector.transform(text))=='__label__2 '
if output[0]==True:
result='Positive Review'
else:
result='Negative Review'
return render_template('analysis.html', prediction_text='Predicted Sentiment: {}'.format(result))
@app.route('/predict_api',methods=['POST'])
def predict_api():
data = request.get_json(force=True)
prediction = model.predict(tf_vector.transform(list(data.values())))
output = prediction[0]
return jsonify(output)
if __name__ == "__main__":
app.run(debug=True)