streamlit_app/app.py

#!/usr/bin/env python3
"""
NZ Legislation Loophole Analysis Streamlit App

A modern web interface for analyzing New Zealand legislation text to identify
potential loopholes, ambiguities, and unintended consequences using AI.

Features:
- Advanced UI with multi-page layout
- Context memory cache system for improved performance
- Real-time progress monitoring
- Interactive results visualization
- Batch processing capabilities
- Comprehensive configuration management
"""

import streamlit as st
import sys
import os
from pathlib import Path

# Add the current directory to Python path for imports
sys.path.append(os.path.dirname(os.path.abspath(__file__)))

# Import core modules
from core.cache_manager import CacheManager
from core.text_processor import TextProcessor
from core.llm_analyzer import LLMAnalyzer
from core.dataset_builder import DatasetBuilder
from utils.config import ConfigManager
from utils.ui_helpers import UIHelpers
from utils.performance import PerformanceMonitor

# Configure page settings
st.set_page_config(
    page_title="NZ Legislation Loophole Analyzer",
    page_icon="⚖️",
    layout="wide",
    initial_sidebar_state="expanded",
    menu_items={
        'Get Help': 'https://github.com/your-repo',
        'Report a bug': 'https://github.com/your-repo/issues',
        'About': '''
        ## NZ Legislation Loophole Analyzer
        A powerful AI tool for analyzing New Zealand legislation to identify
        potential loopholes, ambiguities, and unintended consequences.

        **Version:** 1.0.0
        **Built with:** Streamlit, Llama.cpp, and advanced caching
        '''
    }
)

# Initialize session state
def initialize_session_state():
    """Initialize all session state variables"""
    if 'cache_manager' not in st.session_state:
        st.session_state.cache_manager = CacheManager()

    if 'config_manager' not in st.session_state:
        st.session_state.config_manager = ConfigManager()

    if 'performance_monitor' not in st.session_state:
        st.session_state.performance_monitor = PerformanceMonitor()

    if 'current_analysis' not in st.session_state:
        st.session_state.current_analysis = None

    if 'analysis_results' not in st.session_state:
        st.session_state.analysis_results = []

    if 'processing_status' not in st.session_state:
        st.session_state.processing_status = {
            'is_running': False,
            'progress': 0,
            'current_task': '',
            'total_chunks': 0,
            'processed_chunks': 0
        }

def main():
    """Main application function"""
    # Initialize session state
    initialize_session_state()

    # Create sidebar with navigation and status
    with st.sidebar:
        st.title("⚖️ NZ Legislation Analyzer")
        st.markdown("---")

        # Navigation
        pages = {
            "🏠 Home": "home",
            "📤 Upload & Process": "upload",
            "📊 Analysis Results": "results",
            "⚙️ Settings": "settings",
            "📈 Performance": "performance"
        }

        selected_page = st.selectbox(
            "Navigate to:",
            list(pages.keys()),
            key="nav_select"
        )

        st.markdown("---")

        # Cache status
        with st.expander("🧠 Cache Status", expanded=True):
            cache_stats = st.session_state.cache_manager.get_stats()
            st.metric("Cache Hits", cache_stats['hits'])
            st.metric("Cache Misses", cache_stats['misses'])
            st.metric("Hit Rate", ".1f")
            st.metric("Cached Chunks", cache_stats['entries'])

            if st.button("Clear Cache", type="secondary"):
                st.session_state.cache_manager.clear_cache()
                st.rerun()

        # Performance metrics
        with st.expander("📊 Performance", expanded=True):
            perf_stats = st.session_state.performance_monitor.get_stats()
            st.metric("Memory Usage", ".1f")
            st.metric("Avg Processing Time", ".2f")

        # Processing status
        if st.session_state.processing_status['is_running']:
            with st.expander("🔄 Processing Status", expanded=True):
                st.progress(st.session_state.processing_status['progress'])
                st.text(st.session_state.processing_status['current_task'])
                st.text(f"Chunk {st.session_state.processing_status['processed_chunks']}/"
                       f"{st.session_state.processing_status['total_chunks']}")

    # Main content area
    page = pages[selected_page]

    if page == "home":
        show_home_page()
    elif page == "upload":
        show_upload_page()
    elif page == "results":
        show_results_page()
    elif page == "settings":
        show_settings_page()
    elif page == "performance":
        show_performance_page()

    # Footer
    st.markdown("---")
    st.markdown(
        """
        <div style='text-align: center; color: #666; font-size: 12px;'>
        NZ Legislation Loophole Analyzer v1.0.0 | Built with Streamlit & Llama.cpp
        </div>
        """,
        unsafe_allow_html=True
    )

def show_home_page():
    """Display the home page with overview and quick start"""
    st.title("🏠 NZ Legislation Loophole Analyzer")
    st.markdown("### AI-Powered Legal Analysis Tool")

    col1, col2 = st.columns([2, 1])

    with col1:
        st.markdown("""
        This advanced tool analyzes New Zealand legislation to identify:

        🔍 **Potential Loopholes** - Legal ambiguities that could be exploited
        📋 **Unintended Consequences** - Hidden implications in legislative language
        ⚖️ **Ambiguities** - Vague or unclear legal provisions
        🎯 **Circumvention Strategies** - Ways legislation might be bypassed

        **Key Features:**
        - **Smart Caching**: Avoid re-processing identical content
        - **Advanced UI**: Modern interface with real-time progress
        - **Batch Processing**: Handle multiple legislation files
        - **Performance Monitoring**: Track memory usage and processing speed
        - **Export Options**: Multiple formats for analysis results
        """)

        st.markdown("### Quick Start")
        st.markdown("""
        1. **Upload** your NZ legislation files (JSON lines or raw text)
        2. **Configure** analysis parameters and model settings
        3. **Process** the legislation with AI-powered analysis
        4. **Review** results with interactive visualizations
        5. **Export** findings in multiple formats
        """)

    with col2:
        st.markdown("### Current Configuration")

        config = st.session_state.config_manager.get_config()

        # Model settings
        st.subheader("🤖 Model Settings")
        st.info(f"**Model:** {config['model']['path']}")
        st.info(f"**Context Length:** {config['model']['context_length']}")
        st.info(f"**Max Tokens:** {config['model']['max_tokens']}")

        # Processing settings
        st.subheader("⚙️ Processing")
        st.info(f"**Chunk Size:** {config['processing']['chunk_size']}")
        st.info(f"**Overlap:** {config['processing']['chunk_overlap']}")
        st.info(f"**Batch Size:** {config['processing']['batch_size']}")

        # Cache settings
        st.subheader("🧠 Cache")
        cache_stats = st.session_state.cache_manager.get_stats()
        st.info(f"**Status:** {'Active' if cache_stats['enabled'] else 'Disabled'}")
        st.info(f"**Hit Rate:** {cache_stats['hit_rate']:.1f}%")

        if st.button("🚀 Start Analysis", type="primary", use_container_width=True):
            st.switch_page("pages/1_upload.py")

def show_upload_page():
    """Display the upload and processing page"""
    st.title("📤 Upload & Process Legislation")

    # File upload section
    st.subheader("📁 Upload Legislation Files")

    col1, col2 = st.columns([1, 1])

    with col1:
        uploaded_files = st.file_uploader(
            "Select NZ legislation files",
            accept_multiple_files=True,
            type=['json', 'txt', 'jsonl'],
            help="Upload JSON lines format (.jsonl), JSON arrays (.json), or raw text (.txt) files"
        )

        if uploaded_files:
            st.success(f"📄 {len(uploaded_files)} file(s) selected")

            # Show file details
            for file in uploaded_files:
                with st.expander(f"📋 {file.name}"):
                    st.write(f"**Size:** {file.size:,} bytes")
                    st.write(f"**Type:** {file.type}")

                    # Preview content
                    if file.type in ['text/plain', 'application/json']:
                        content = file.read().decode('utf-8')
                        st.text_area("Preview", content[:500] + "..." if len(content) > 500 else content,
                                   height=100, disabled=True)
                        file.seek(0)  # Reset file pointer

    with col2:
        # Processing configuration
        st.subheader("⚙️ Processing Configuration")

        config = st.session_state.config_manager.get_config()

        # Model settings
        with st.expander("🤖 Model Configuration", expanded=True):
            model_path = st.text_input(
                "Model Path",
                value=config['model']['path'],
                help="Path to your GGUF model file"
            )

            context_length = st.slider(
                "Context Length",
                min_value=1024,
                max_value=65536,
                value=config['model']['context_length'],
                step=1024,
                help="Maximum context length for the model"
            )

            max_tokens = st.slider(
                "Max Response Tokens",
                min_value=256,
                max_value=4096,
                value=config['model']['max_tokens'],
                step=64,
                help="Maximum tokens in model response"
            )

        # Text processing settings
        with st.expander("📝 Text Processing", expanded=True):
            chunk_size = st.slider(
                "Chunk Size",
                min_value=512,
                max_value=8192,
                value=config['processing']['chunk_size'],
                step=256,
                help="Size of text chunks for processing"
            )

            chunk_overlap = st.slider(
                "Chunk Overlap",
                min_value=64,
                max_value=1024,
                value=config['processing']['chunk_overlap'],
                step=32,
                help="Overlap between chunks for context preservation"
            )

        # Analysis settings
        with st.expander("🔍 Analysis Settings", expanded=True):
            analysis_depth = st.select_slider(
                "Analysis Depth",
                options=["Basic", "Standard", "Detailed", "Comprehensive"],
                value=config['analysis']['depth'],
                help="Level of detail in legal analysis"
            )

            include_recommendations = st.checkbox(
                "Include Recommendations",
                value=config['analysis']['include_recommendations'],
                help="Generate specific recommendations for addressing identified issues"
            )

    # Process button and status
    col1, col2, col3 = st.columns([1, 1, 1])

    with col1:
        if st.button("🔄 Start Processing", type="primary", use_container_width=True):
            if not uploaded_files:
                st.error("Please upload at least one legislation file")
            else:
                start_processing(uploaded_files, {
                    'model': {
                        'path': model_path,
                        'context_length': context_length,
                        'max_tokens': max_tokens
                    },
                    'processing': {
                        'chunk_size': chunk_size,
                        'chunk_overlap': chunk_overlap
                    },
                    'analysis': {
                        'depth': analysis_depth,
                        'include_recommendations': include_recommendations
                    }
                })

    with col2:
        if st.button("⏹️ Stop Processing", use_container_width=True):
            stop_processing()

    with col3:
        if st.button("📊 View Results", use_container_width=True):
            st.switch_page("pages/2_analysis.py")

def start_processing(files, config):
    """Start the processing workflow"""
    st.session_state.processing_status = {
        'is_running': True,
        'progress': 0,
        'current_task': 'Initializing...',
        'total_chunks': 0,
        'processed_chunks': 0
    }

    # Update configuration
    st.session_state.config_manager.update_config(config)

    # TODO: Implement actual processing logic
    st.rerun()

def stop_processing():
    """Stop the current processing"""
    st.session_state.processing_status['is_running'] = False
    st.session_state.processing_status['current_task'] = 'Stopped by user'

def show_results_page():
    """Display analysis results page"""
    st.title("📊 Analysis Results")

    if not st.session_state.analysis_results:
        st.info("No analysis results available. Please upload and process legislation files first.")
        return

    # Results overview
    st.subheader("📈 Results Overview")

    col1, col2, col3, col4 = st.columns(4)

    total_results = len(st.session_state.analysis_results)
    total_loopholes = sum(len(result.get('loopholes', [])) for result in st.session_state.analysis_results)
    avg_confidence = sum(result.get('confidence', 0) for result in st.session_state.analysis_results) / max(total_results, 1)

    with col1:
        st.metric("Total Analyses", total_results)

    with col2:
        st.metric("Loopholes Found", total_loopholes)

    with col3:
        st.metric("Avg Confidence", ".2f")

    with col4:
        cache_stats = st.session_state.cache_manager.get_stats()
        st.metric("Cache Hit Rate", ".1f")

    # Results display
    st.subheader("🔍 Detailed Results")

    for i, result in enumerate(st.session_state.analysis_results):
        with st.expander(f"📋 Analysis {i+1}: {result.get('title', 'Unknown Title')}", expanded=i==0):
            col1, col2 = st.columns([2, 1])

            with col1:
                st.markdown("**Summary:**")
                st.write(result.get('summary', 'No summary available'))

                st.markdown("**Key Findings:**")
                for finding in result.get('loopholes', []):
                    st.markdown(f"- {finding}")

            with col2:
                st.metric("Confidence", ".2f")
                st.metric("Processing Time", ".2f")
                st.metric("Chunks Processed", result.get('chunks_processed', 0))

    # Export options
    st.subheader("💾 Export Results")

    col1, col2, col3 = st.columns(3)

    with col1:
        if st.button("📄 Export as JSON", use_container_width=True):
            export_results('json')

    with col2:
        if st.button("📊 Export as CSV", use_container_width=True):
            export_results('csv')

    with col3:
        if st.button("📋 Export as Excel", use_container_width=True):
            export_results('excel')

def export_results(format_type):
    """Export analysis results in specified format"""
    # TODO: Implement export functionality
    st.success(f"Results exported as {format_type.upper()}")

def show_settings_page():
    """Display settings page"""
    st.title("⚙️ Settings & Configuration")

    tabs = st.tabs(["🤖 Model Settings", "📝 Processing", "🧠 Cache", "🎨 UI", "🔧 Advanced"])

    with tabs[0]:
        st.subheader("🤖 Model Configuration")

        config = st.session_state.config_manager.get_config()

        model_path = st.text_input(
            "Model Path",
            value=config['model']['path'],
            help="Path to your GGUF model file"
        )

        repo_id = st.text_input(
            "HuggingFace Repo ID",
            value=config['model']['repo_id'],
            help="HuggingFace repository ID for model download"
        )

        filename = st.text_input(
            "Model Filename",
            value=config['model']['filename'],
            help="Specific model filename in the repository"
        )

        context_length = st.slider(
            "Context Length",
            min_value=1024,
            max_value=131072,
            value=config['model']['context_length'],
            step=1024
        )

        max_tokens = st.slider(
            "Max Response Tokens",
            min_value=256,
            max_value=8192,
            value=config['model']['max_tokens'],
            step=64
        )

        temperature = st.slider(
            "Temperature",
            min_value=0.0,
            max_value=2.0,
            value=config['model']['temperature'],
            step=0.1,
            help="Controls randomness in model output"
        )

    with tabs[1]:
        st.subheader("📝 Text Processing")

        chunk_size = st.slider(
            "Chunk Size",
            min_value=256,
            max_value=16384,
            value=config['processing']['chunk_size'],
            step=256
        )

        chunk_overlap = st.slider(
            "Chunk Overlap",
            min_value=32,
            max_value=2048,
            value=config['processing']['chunk_overlap'],
            step=32
        )

        batch_size = st.slider(
            "Batch Size",
            min_value=1,
            max_value=32,
            value=config['processing']['batch_size'],
            step=1
        )

        clean_text = st.checkbox(
            "Clean Text",
            value=config['processing']['clean_text'],
            help="Apply text cleaning and normalization"
        )

    with tabs[2]:
        st.subheader("🧠 Cache Configuration")

        enable_cache = st.checkbox(
            "Enable Caching",
            value=config['cache']['enabled'],
            help="Use cache to avoid re-processing identical chunks"
        )

        max_cache_size = st.slider(
            "Max Cache Size (MB)",
            min_value=100,
            max_value=8192,
            value=config['cache']['max_size_mb'],
            step=100
        )

        cache_ttl = st.slider(
            "Cache TTL (hours)",
            min_value=1,
            max_value=168,
            value=config['cache']['ttl_hours'],
            step=1,
            help="Time-to-live for cached entries"
        )

        persistent_cache = st.checkbox(
            "Persistent Cache",
            value=config['cache']['persistent'],
            help="Save cache to disk for persistence across sessions"
        )

    with tabs[3]:
        st.subheader("🎨 UI Configuration")

        theme = st.selectbox(
            "Theme",
            options=["Auto", "Light", "Dark"],
            index=["Auto", "Light", "Dark"].index(config['ui']['theme'])
        )

        show_progress = st.checkbox(
            "Show Progress Bars",
            value=config['ui']['show_progress'],
            help="Display progress indicators during processing"
        )

        auto_refresh = st.checkbox(
            "Auto-refresh Results",
            value=config['ui']['auto_refresh'],
            help="Automatically refresh results view"
        )

    with tabs[4]:
        st.subheader("🔧 Advanced Settings")

        debug_mode = st.checkbox(
            "Debug Mode",
            value=config['advanced']['debug_mode'],
            help="Enable detailed logging and debugging information"
        )

        log_level = st.selectbox(
            "Log Level",
            options=["DEBUG", "INFO", "WARNING", "ERROR"],
            index=["DEBUG", "INFO", "WARNING", "ERROR"].index(config['advanced']['log_level'])
        )

        memory_limit = st.slider(
            "Memory Limit (MB)",
            min_value=512,
            max_value=32768,
            value=config['advanced']['memory_limit_mb'],
            step=512
        )

    # Save settings
    col1, col2 = st.columns([1, 1])

    with col1:
        if st.button("💾 Save Settings", type="primary", use_container_width=True):
            new_config = {
                'model': {
                    'path': model_path,
                    'repo_id': repo_id,
                    'filename': filename,
                    'context_length': context_length,
                    'max_tokens': max_tokens,
                    'temperature': temperature
                },
                'processing': {
                    'chunk_size': chunk_size,
                    'chunk_overlap': chunk_overlap,
                    'batch_size': batch_size,
                    'clean_text': clean_text
                },
                'cache': {
                    'enabled': enable_cache,
                    'max_size_mb': max_cache_size,
                    'ttl_hours': cache_ttl,
                    'persistent': persistent_cache
                },
                'ui': {
                    'theme': theme,
                    'show_progress': show_progress,
                    'auto_refresh': auto_refresh
                },
                'advanced': {
                    'debug_mode': debug_mode,
                    'log_level': log_level,
                    'memory_limit_mb': memory_limit
                }
            }

            st.session_state.config_manager.update_config(new_config)
            st.success("Settings saved successfully!")

    with col2:
        if st.button("🔄 Reset to Defaults", use_container_width=True):
            st.session_state.config_manager.reset_to_defaults()
            st.success("Settings reset to defaults!")
            st.rerun()

def show_performance_page():
    """Display performance monitoring page"""
    st.title("📈 Performance Dashboard")

    # Real-time metrics
    st.subheader("📊 Real-time Metrics")

    col1, col2, col3, col4 = st.columns(4)

    perf_stats = st.session_state.performance_monitor.get_stats()

    with col1:
        st.metric("Memory Usage", ".1f", "MB")

    with col2:
        st.metric("CPU Usage", ".1f", "%")

    with col3:
        st.metric("Active Threads", perf_stats.get('active_threads', 0))

    with col4:
        cache_stats = st.session_state.cache_manager.get_stats()
        st.metric("Cache Hit Rate", ".1f", "%")

    # Performance charts
    st.subheader("📈 Performance History")

    # TODO: Add interactive charts for performance metrics

    # System information
    st.subheader("💻 System Information")

    col1, col2 = st.columns(2)

    with col1:
        st.markdown("**Hardware:**")
        # TODO: Add system information display

    with col2:
        st.markdown("**Software:**")
        # TODO: Add software information display

    # Cache performance
    st.subheader("🧠 Cache Performance")

    cache_stats = st.session_state.cache_manager.get_stats()

    col1, col2, col3, col4 = st.columns(4)

    with col1:
        st.metric("Total Requests", cache_stats['hits'] + cache_stats['misses'])

    with col2:
        st.metric("Cache Hits", cache_stats['hits'])

    with col3:
        st.metric("Cache Misses", cache_stats['misses'])

    with col4:
        st.metric("Hit Rate", ".1f")

    # Performance recommendations
    st.subheader("💡 Performance Recommendations")

    recommendations = []

    if cache_stats['hit_rate'] < 50:
        recommendations.append("Consider increasing cache size or adjusting chunk sizes to improve hit rate")

    if perf_stats.get('memory_usage_mb', 0) > 8000:
        recommendations.append("High memory usage detected. Consider reducing batch size or chunk size")

    if not recommendations:
        recommendations.append("Performance is optimal!")

    for rec in recommendations:
        st.info(rec)

if __name__ == "__main__":
    main()