import streamlit as st
import numpy as np
import joblib

#load the training the model
model=joblib.load("./models/models.pkl")
st.set_page_config(page_title="🎓Student Placement Prediction System",page_icon="🎓",layout="wide")
#tit
st.markdown("<h1 style='text-align: center;background-color:darkblue; color: white;'>🎓Student Placement Prediction System</h1>",unsafe_allow_html=True)
st.markdown("---")
st.sidebar.header("Student Details")
gender=st.selectbox("Gender",["Male","Female"])
tenth_board=st.selectbox("10th Board",["CBSE","Diploma","ICSE","ISE","Other state Board","State Board","WBBSE"])
tenth_marks=st.number_input("10th marks")
twelfth_board=st.selectbox("12th Board",["CBSE","Diploma","ISE","Other state Board","State Board","WBCHSE"])
twelfth_marks=st.number_input("12th marks")
stream=st.selectbox("Stream",["Civil Engineering","Computer Science and Engineering","Computer Science in AIML","Electronics and Communication Engineering","Information Technology","Mechanical Engineering","Production Engineering"])
cgpa=st.number_input("Cgpa")
internship=st.selectbox("Internships(Y/N)",["Yes","No"])
training=st.selectbox("Training(Y/N)",["Yes","No"])
backlog=st.number_input("Backlog in 5th sem")
innovative_project=st.selectbox("Innovative Project(Y/N)",["Yes","No"])
communication=st.slider("Communication Skills",0,5)
Course=st.selectbox("Technical Course(Y/N)",["Yes","No"])

st.markdown("📑Students Inputs Summary")
col1,col2,col3=st.columns(3)
col1.metric("10th Marks",tenth_marks)
col2.metric("12th Marks",twelfth_marks)
col3.metric("CGPA",cgpa)
st.markdown("---")
if st.button("Predict Placement"):
    gender=1 if gender=="Male" else 0
    tenth_board_encoded=["CBSE","Diploma","ICSE","ISE","Other state Board","State Board","WBBSE"].index(tenth_board)
    twelfth_board_encoded=["CBSE","Diploma","ISE","Other state Board","State Board","WBCHSE"].index(twelfth_board)
    stream_encoded=["Civil Engineering","Computer Science and Engineering","Computer Science in AIML","Electronics and Communication Engineering","Information Technology","Mechanical Engineering","Production Engineering"].index(stream)
    internship=1 if internship=="Yes" else 0   
    training=1 if training=="Yes" else 0 
    backlog=1 if backlog>0 else 0
    innovative_project=1 if innovative_project=="Yes" else 0
    courses=1 if Course=="Yes" else 0

    input_data=np.array([[gender,tenth_board_encoded,tenth_marks,twelfth_board_encoded,twelfth_marks,stream_encoded,cgpa,internship,training,backlog,innovative_project,communication,courses]])
    prediction=model.predict(input_data)

    if prediction[0]==1:
        st.success("🎉🎉Student will be placed")
        st.balloons()
    else:
        st.error("❌😒Student will not be placed")
        st.snow()