File size: 1,840 Bytes
a19b6e4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | #!/usr/local/bin/python3.9
import streamlit as st
import requests
import json
import datetime
print(datetime.datetime.now(),"Program start.")
def get_prediction_aiclub(s):
data={"Tweet_Text":s}
url = 'https://askai.aiclub.world/bb38c320-72aa-4397-be1c-77bc95787625'
r = requests.post(url, data=json.dumps(data))
response = getattr(r,'_content').decode("utf-8")
print("Response:",response)
b1=json.loads(response)["body"]
j2=json.loads(b1)
p=j2["predicted_label"]
confidence=j2["confidence_score"]
s=sorted(confidence.items(), key=lambda x: x[1], reverse=True)
return p,s
st.title("Hate Speech Detector")
sentence=st.text_input('Sentence to analyze')
labels=['Homophobe', 'Sexist', 'OtherHate', 'NotHate', 'Religion', 'Racist']
msgs={
'Homophobe': 'Determined this to be a homophobic comment',
'Sexist':'AI says that this message is sexist',
'OtherHate':'AI believes that this is a hateful message',
'NotHate':'AI determines that this is not a hateful message',
'Religion':'AI determined this comment to be hateful to religious people',
'Racist':' AI says that this message is racist'
}
paras={
'Homophobe': 'Paragrapg for homophobic comments. \nSecond line for homophobic comment',
'Sexist':'Para for AI says that this message is sexist',
'OtherHate':'Para for other hateful message',
'NotHate':'Para for not a hateful message',
'Religion':'Para for hateful to religious people',
'Racist':'Para for racist'
}
if sentence:
print("*************\nSentence:",sentence)
(pr,s)=get_prediction_aiclub(sentence)
cv=s[0][1]*100
print(f"Saw {pr} with {s} for {cv}")
c=f" with confidence: {cv:.1f}%"
m=msgs[pr]
p=paras[pr]
print(p+c+m)
st.title(m+c)
st.text(p)
print(datetime.datetime.now(),"Program end.")
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