import pickle

import numpy as np
import gradio as gr

# install transformers and torch in requirements.txt

from transformers import AutoTokenizer, AutoModelForSequenceClassification
from sklearn.feature_extraction.text import TfidfVectorizer

model = pickle.load(open("model.pkl", "rb"))
vectorizer = pickle.load(open("vectorizer.pkl", "rb"))


def classify_text(inp):
    
    new_question_vector = vectorizer.transform([inp])
    prediction = model.predict(new_question_vector)
    return str(prediction[0])

iface = gr.Interface(fn=classify_text, inputs="text", outputs="label",title="Tabibu Bot",
                        interpretation="default", examples=[
                            ["I am feeling depressed"],
                            ["I am feeling anxious"],
                            ["I am feeling stressed"],
                            ["I am feeling sad"],
                        ])
iface.launch()