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https://huggingface.co/spaces/tonthw/azuremlworkshop09/resolve/main/app.py
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2.29 kB
| import streamlit as st | |
| import urllib.request | |
| import json | |
| st.title('Loan Prediction App') | |
| # Create a form for user input | |
| st.subheader('Enter Customer Information:') | |
| gender = st.selectbox('Gender', ['Male', 'Female']) | |
| married = st.selectbox('Married', ['Yes', 'No']) | |
| dependents = st.selectbox('Dependents', ['0', '1', '2', '3+']) | |
| education = st.selectbox('Education', ['Graduate', 'Not Graduate']) | |
| self_employed = st.selectbox('Self Employed', ['Yes', 'No']) | |
| applicant_income = st.number_input('Applicant Income') | |
| coapplicant_income = st.number_input('Coapplicant Income') | |
| loan_amount = st.number_input('Loan Amount') | |
| term = st.number_input('Term (in months)') | |
| credit_history = st.selectbox('Credit History', ['0.0', '1.0']) | |
| area = st.selectbox('Area', ['Urban', 'Rural', 'Semiurban']) | |
| # When the user clicks the "Predict" button | |
| if st.button('Predict'): | |
| # Create the data payload | |
| data = { | |
| "Inputs": { | |
| "data": [ | |
| { | |
| "Gender": gender, | |
| "Married": married, | |
| "Dependents": dependents, | |
| "Education": education, | |
| "Self_Employed": self_employed, | |
| "Applicant_Income": applicant_income, | |
| "Coapplicant_Income": coapplicant_income, | |
| "Loan_Amount": loan_amount, | |
| "Term": term, | |
| "Credit_History": float(credit_history), | |
| "Area": area | |
| } | |
| ] | |
| }, | |
| "GlobalParameters": { | |
| "method": "predict" | |
| } | |
| } | |
| # Convert data to JSON | |
| json_data = json.dumps(data).encode('utf-8') | |
| # Send a POST request to the specified URL | |
| url = 'http://28132852-a923-4783-b934-0c91b8f04bfa.southeastasia.azurecontainer.io/score' | |
| headers = {'Content-Type': 'application/json'} | |
| try: | |
| response = urllib.request.urlopen(urllib.request.Request(url, json_data, headers)) | |
| # Read and display the result | |
| result = response.read() | |
| st.subheader('Prediction Result:') | |
| st.json(json.loads(result)) | |
| except urllib.error.HTTPError as error: | |
| st.error(f'The request failed with status code: {error.code}') | |
| st.error(error.read().decode("utf8", 'ignore')) | |