import streamlit as st
import pickle
import numpy as np
import pandas as pd

st.title("AI-Driven Project Risk Level Classification Tool")

Project_Type = st.selectbox("Type of the project", ['Construction', 'Manufacturing', 'IT', 'R&D', 'Healthcare', 'Marketing'])

Team_size = st.number_input("Team size", min_value=2, max_value=50)
Project_Budget_USD = st.number_input('Project Budget (USD)', min_value=159355.55, max_value=3768354.37)
Estimated_Timeline_Months = st.number_input('Estimated Timeline (Months)', min_value=2, max_value=36)
Complexity_Score = st.number_input('Complexity Score', min_value=1.62, max_value=10.00)
Stakeholder_Count = st.number_input('Stakeholder Count', min_value=2, max_value=29)

Methodology_Used = st.selectbox('Methodology Used', ['Waterfall', 'Kanban', 'Agile', 'Scrum', 'Hybrid'])
Team_Experience_Level = st.selectbox('Team Experience Level', ['Senior', 'Mixed', 'Junior', 'Expert'])
External_Dependencies_Count = st.number_input('External Dependencies Count', min_value=0, max_value=7)
Requirement_Stability = st.selectbox('Requirement Stability', ['Moderate', 'Stable', 'Volatile'])
Current_Phase_Duration_Months = st.number_input('Current Phase Duration (Months)', min_value=1, max_value=17)

with open("Classification project.pkl", "rb") as f:
    final_model = pickle.load(f)

if st.button("Submit the Details"):
    input_df = pd.DataFrame([{
        'Project_Type': Project_Type,
        'Team_Size': Team_size,
        'Project_Budget_USD': Project_Budget_USD,
        'Estimated_Timeline_Months': Estimated_Timeline_Months,
        'Complexity_Score': Complexity_Score,
        'Stakeholder_Count': Stakeholder_Count,
        'Methodology_Used': Methodology_Used,
        'Team_Experience_Level': Team_Experience_Level,
        'External_Dependencies_Count': External_Dependencies_Count,
        'Requirement_Stability': Requirement_Stability,
        'Current_Phase_Duration_Months': Current_Phase_Duration_Months
    }])

    pred = final_model.predict(input_df)[0]
    st.success(f"The predicted Risk Level is: {pred}")