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import streamlit as st | |
import json | |
import requests | |
import os | |
API_TOKEN = os.environ.get("API_TOKEN") | |
API_URL = os.environ.get("API_URL") | |
headers = {"Authorization": f"Bearer {API_TOKEN}"} | |
def query(payload): | |
data = json.dumps(payload) | |
response = requests.request("POST", API_URL, headers=headers, data=data) | |
return json.loads(response.content.decode("utf-8")) | |
def analyze_txt(txt): | |
label_dict={'LABEL_0':'Geoteknik','LABEL_1':'Hidrolik','LABEL_2':'Malzeme','LABEL_3':'Ulaştırma','LABEL_4':'Yapı'} | |
data = query(txt) | |
result=data[0][0]['label'] | |
decode_result=label_dict[result] | |
prob=data[0][0]['score'] | |
result2=data[0][1]['label'] | |
decode_result2=label_dict[result2] | |
prob2=data[0][1]['score'] | |
strn='Best guess '+str(decode_result)+' ->confidence: '+str(round(prob,3)) | |
strn2= 'Other guess '+str(decode_result2)+' ->confidence: '+str(round(prob2,3)) | |
return strn,strn2 | |
st.header('Find the Category of Turkish Civil Engineering Abstracts') | |
st.caption('classify->geoteknik,hidrolik,malzeme,ulaştırma,yapı') | |
txt = st.text_area('Abstract to analyze and predict(in Turkish)') | |
if st.button('Find the category'): | |
if txt != '': | |
txt1,txt2=analyze_txt(txt) | |
st.success(txt1, icon="✅") | |
st.info(txt2, icon="ℹ️") | |
else: | |
st.write('Please input text') |