import gradio as gr
from joblib import dump, load

model_names = ['Logistic_Regression', 'LDA', 'QDA', 'Naive_Bayes', 'SVC']
models = {}

vectorizer = load('vectorizer.joblib')

for name in model_names:
  models[name] = load(name + '.joblib')


def predict(text, method):

  prediction = models[method].predict_proba(vectorizer.transform([text]).toarray())[0]


  return {'Negative Comment':prediction[0], 'Positive Comment':prediction[1]}


input_module1 = gr.Textbox(label='Review Comment')
input_module2 = gr.Dropdown(choices=model_names, label = "method")

output_module = gr.Label(num_top_classes=2,label = "Predicted Probabilities")

gr.Interface(fn=predict, inputs=[input_module1,input_module2], outputs=output_module).launch(debug=True)