app.py

"""
Data Analysis Platform
Copyright (c) 2025 JEAN YOUNG
All rights reserved.

This software is proprietary and confidential.
Unauthorized copying, distribution, or use is prohibited.
"""
import streamlit as st
import pandas as pd
from data_handler import load_data
from analyzer import DataAnalysisWorkflow, AIAssistant

def main():
    st.set_page_config(
        page_title="Data Analysis Platform",
        page_icon="📊",
        layout="wide"
    )
    
    st.title("📊 Data Analysis Platform")
    st.markdown("**Optimized workflow with caching and pagination**")
    
    # Initialize session state
    if 'current_stage' not in st.session_state:
        st.session_state.current_stage = 1
    if 'workflow' not in st.session_state:
        st.session_state.workflow = None
    if 'ai_assistant' not in st.session_state:
        st.session_state.ai_assistant = AIAssistant()
    
    # File upload
    uploaded_file = st.file_uploader("Upload Dataset", type=['csv', 'xlsx'])
    
    if uploaded_file is not None:
        try:
            # Load data
            df = load_data(uploaded_file)
            st.success(f"✅ Dataset loaded! Shape: {df.shape}")
            
            # Initialize workflow
            if st.session_state.workflow is None:
                st.session_state.workflow = DataAnalysisWorkflow(df)
            
            # Progress sidebar
            st.sidebar.header("Progress")
            progress = st.sidebar.progress(st.session_state.current_stage / 5)
            
            stages = ["Data Overview", "Exploration", "Quality Check", "Analysis", "Summary"]
            for i, stage in enumerate(stages, 1):
                if i == st.session_state.current_stage:
                    st.sidebar.write(f"🔄 **{i}. {stage}**")
                elif i < st.session_state.current_stage:
                    st.sidebar.write(f"✅ {i}. {stage}")
                else:
                    st.sidebar.write(f"⏳ {i}. {stage}")
            
            # Navigation
            col1, col2 = st.sidebar.columns(2)
            with col1:
                if st.button("← Previous") and st.session_state.current_stage > 1:
                    st.session_state.current_stage -= 1
                    st.rerun()
            with col2:
                if st.button("Next →") and st.session_state.current_stage < 5:
                    st.session_state.current_stage += 1
                    st.rerun()
            
            # Recent insights
            st.sidebar.header("💡 Recent Insights")
            recent_insights = st.session_state.workflow.insights[-3:]
            for insight in recent_insights:
                st.sidebar.info(f"**Stage {insight['stage']}:** {insight['insight']}")
            
            # Main content with AI assistant
            main_col, ai_col = st.columns([3, 1])
            
            with main_col:
                # Execute current stage
                if st.session_state.current_stage == 1:
                    st.session_state.workflow.stage_1_overview()
                elif st.session_state.current_stage == 2:
                    st.session_state.workflow.stage_2_exploration()
                elif st.session_state.current_stage == 3:
                    st.session_state.workflow.stage_3_cleaning()
                elif st.session_state.current_stage == 4:
                    st.session_state.workflow.stage_4_analysis()
                elif st.session_state.current_stage == 5:
                    st.session_state.workflow.stage_5_summary()
            
            with ai_col:
                st.subheader("🤖 AI Assistant")
                
                # AI model selection
                available_models = st.session_state.ai_assistant.get_available_models()
                
                if available_models:
                    selected_model = st.selectbox("AI Model:", available_models)
                    
                    if st.button("Get AI Insights"):
                        if st.session_state.workflow.insights:
                            with st.spinner("Analyzing with AI..."):
                                ai_analysis = st.session_state.ai_assistant.analyze_insights(
                                    df, st.session_state.workflow.insights, selected_model
                                )
                                st.write("**AI Analysis:**")
                                st.write(ai_analysis)
                        else:
                            st.warning("Complete some analysis stages first.")
                else:
                    st.warning("No AI models available.")
                    st.info("Set GOOGLE_API_KEY or OPENAI_API_KEY environment variables.")
                    
                # Quick insights
                st.subheader("📊 Quick Stats")
                if st.session_state.workflow.insights:
                    st.metric("Total Insights", len(st.session_state.workflow.insights))
                    st.metric("Current Stage", f"{st.session_state.current_stage}/5")
                    
                    # Latest insight
                    if st.session_state.workflow.insights:
                        latest = st.session_state.workflow.insights[-1]
                        st.info(f"**Latest:** {latest['insight']}")
                    
                # Data quality indicator
                quality_score = 100
                if st.session_state.workflow.stats['missing_values'] > 0:
                    quality_score -= 30
                if st.session_state.workflow.stats['duplicates'] > 0:
                    quality_score -= 20
                    
                st.metric("Data Quality", f"{quality_score}%")
        
        except Exception as e:
            st.error(f"Error: {str(e)}")
            st.info("Please check your file format and try again.")

if __name__ == "__main__":
    main()