|
import streamlit as st |
|
from backend.bot import * |
|
from backend.model import * |
|
import pandas as pd |
|
import time |
|
import google.generativeai as genai |
|
|
|
|
|
st.set_page_config(page_title='Batch Processing', layout='wide') |
|
|
|
st.title("Attrition Prediction Engine") |
|
st.write("Welcome to the Attrition Prediction Engine! This tool is designed to help you batch process employee data and predict attrition.") |
|
|
|
with st.sidebar: |
|
with st.expander("🧪 Experimental Features", expanded=False): |
|
st.caption("API token can be obtained at https://aistudio.google.com/.") |
|
gemini_api = st.text_input("Gemini Token", "", type='password') |
|
try: |
|
genai.configure(api_key=gemini_api) |
|
ai_model = genai.GenerativeModel("gemini-1.5-flash") |
|
test = ai_model.generate_content("Explain how AI works") |
|
st.success("API key is valid. Experimental feature access granted.") |
|
except Exception as e: |
|
st.error("API key is invalid. You don't have access to experimental features.") |
|
|
|
|
|
with st.expander("⚠️ Disclaimer", expanded=False): |
|
st.write("This web app is intended for prediction purposes only. The results are based on the input data provided and \ |
|
the performance of the machine learning model. The accuracy of the predictions may vary depending on data quality \ |
|
and model reliability.") |
|
|
|
st.caption("MIT License © 2025 Khor Kean Teng, Ng Jing Wen, Lim Sze Chie, Tan Yee Thong, Yee See Marn") |
|
|
|
|
|
|
|
with st.chat_message("assistant", avatar="https://cdn4.iconfinder.com/data/icons/heroes-villains-vol-2-colored/100/Terminator-512.png"): |
|
|
|
response = st.write("Hello admin! I am Az-147. How can I assist you today?") |
|
st.caption("If you use predefined data, the file upload step will be hidden.") |
|
toggle = st.toggle('Use Predefined Data', True) |
|
data= get_data("data/sample_data.csv") |
|
|
|
if toggle == False: |
|
uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"]) |
|
if uploaded_file is not None: |
|
data = pd.read_csv(uploaded_file) |
|
|
|
submit = st.button("Execute", type='primary') |
|
|
|
model = load_model("model/model.pkl") |
|
|
|
def count_attrition(predictions): |
|
return sum(predictions) |
|
|
|
if submit: |
|
with st.status("Data Preview", expanded=True): |
|
time.sleep(.5) |
|
st.write(f"You've uploaded a data file of {data.shape[0]} rows and {data.shape[1]} columns. Here's a preview of the data:") |
|
st.write(data.head()) |
|
|
|
with st.status("Predicting Attrition...", expanded=True): |
|
time.sleep(2) |
|
prediction = model.predict(data) |
|
data['Attrition'] = prediction |
|
attrition_count = count_attrition(prediction) |
|
output = f"Prediction completed! There are {attrition_count} cases of attrition. Here's a preview of the data with the predicted attrition status:" |
|
st.write(output) |
|
st.write(data.head()) |
|
|
|
with st.status("AI Opinion", expanded=True): |
|
try: |
|
response = ai_model.generate_content(f"Give some opinions in about 100 word based on the prediction results where there are {attrition_count} cases of attrition.") |
|
st.write(response.text) |
|
except Exception as e: |
|
st.write("You don't have access to this feature. Please authenticate to use this feature.") |
|
|
|
|
