import requests
import streamlit as st
import streamlit.components.v1 as components

def semanticComparativeClassification():
    print('Pregunta ',st.session_state.mytext)
    #API_URL = "https://api-inference.huggingface.co/models/Maite89/Roberta_finetuning_semantic_similarity_stsb_multi_mt"
    API_URL = "https://api-inference.huggingface.co/models/symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli"
    headers = {"Authorization": "Bearer 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"}
    
    def query(payload):
    	response = requests.post(API_URL, headers=headers, json=payload)
    	return response.json()
    	
    output = query({
    	"inputs": {
            "wait_for_model" : True,
    		"source_sentence": st.session_state.mytext,
    		"sentences": [
    			"Conoces Lya2",
    			"He perdido la contraseña",
    			"Calendario de eventos",
    			"Cambios dobles",
                "Cambios simples"
    		]
    	},
    })

    for i in output:
        print(i)   
    
    return output


#x = st.slider('Select a value')
#st.write(x, 'squared is', x * x)
 


st.title('Uber pickups in NYC')
title = st.text_input('Query', '¿Conoces Lya2?', on_change=semanticComparativeClassification,key='mytext')
#st.write('The current movie title is', title)