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| import requests | |
| import streamlit as st | |
| import streamlit.components.v1 as components | |
| import time | |
| st.session_state.mytext = "" | |
| global logtxt | |
| global logtxtbox | |
| logtxt = "" | |
| def semanticComparativeClassification(): | |
| st.session_state["respuesta"] = "" | |
| apis_urls = [ | |
| "https://api-inference.huggingface.co/models/symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli", | |
| "https://api-inference.huggingface.co/models/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", | |
| "https://api-inference.huggingface.co/models/sentence-transformers/distiluse-base-multilingual-cased-v2" | |
| ] | |
| for api_url in apis_urls: | |
| semanticComparativeClassificationCall(api_url) | |
| def semanticComparativeClassificationCall(api_url: str): | |
| st.write("Model: "+api_url+"\n") | |
| time.sleep(1) | |
| headers = {"Authorization": "Bearer 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"} | |
| #API_URL = "https://api-inference.huggingface.co/models/Maite89/Roberta_finetuning_semantic_similarity_stsb_multi_mt" | |
| def query(payload): | |
| response = requests.post(api_url, headers=headers, json=payload) | |
| return response.json() | |
| sentences = [ | |
| "Conoces Lya2 , que es Lya2", | |
| "He perdido la contrase帽a, no puedo entrar o acceder a Lya2", | |
| "Calendario de eventos, creamos un evento , borramos un evento ", | |
| "Sincronizamos Lya2 con el tel茅fono o m贸bil" | |
| "Cambios", | |
| "Cambios dobles , pedir, autorizar , borrar un cambio doble", | |
| "Cambios simples , pedir, autorizar , borrar un cambio simple", | |
| "Sessiones", | |
| "Personal", | |
| "Horarios", | |
| "脕reas", | |
| "Rastryco o rastrico", | |
| "Sylbo la aplicaci贸n m贸bil de Lya2", | |
| "Sylbo", | |
| "Hola hi hola", | |
| "Adi贸s adi贸s bye", | |
| "Como programo el personal", | |
| "Como asigno trabajo al personal" | |
| "Pedir permisos", | |
| "Pedir vacaciones" | |
| ] | |
| output = query({ | |
| "inputs": { | |
| "wait_for_model" : True, | |
| "source_sentence": st.session_state.mytext, | |
| "sentences": sentences | |
| }, | |
| }) | |
| #st.write(output) | |
| if "error" in output: | |
| st.write(output["error"]) | |
| else: | |
| index=0 | |
| for i in output: | |
| st.write( str(i) +' - '+sentences[index]) | |
| #container.write(i," - ", sentences[index]) | |
| index = index + 1 | |
| maxim = max(output) | |
| sentenceindex = output.index(maxim) | |
| if output[sentenceindex] < 0.3 : | |
| st.write( "\nNo tengo respuesta para esto, 驴me lo explicas mejor o te pongo en contacto con un humano? ") | |
| st.session_state["respuesta"]= st.session_state["respuesta"] +api_url+"\nNo tengo respuesta para esto, 驴me lo explicas mejor o te pongo en contacto con un humano?"+"\n\n" | |
| else: | |
| st.write("Tema reconocido: "+ str(sentences[sentenceindex])) | |
| st.session_state["respuesta"] = st.session_state["respuesta"] +api_url+"\nTema reconocido: \n"+str(sentences[sentenceindex])+"\n\n" | |
| #x = st.slider('Select a value') | |
| #st.write(x, 'squared is', x * x) | |
| st.session_state.response = "" | |
| st.session_state.logresp = "" | |
| st.title('Reconocimiento sem谩ntico') | |
| title = st.text_input('Pregunta', '', on_change=semanticComparativeClassification,key='mytext') | |
| st.text_area( "Respuesta: ", key= "respuesta", height=200 ) |