Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,996 +1,31 @@
 #!/usr/bin/env python3
 """
-Iran Legal Information Dashboard - Hugging Face Spaces Version
-============================================================
-Optimized for Hugging Face Spaces deployment
+Iran Legal Information Dashboard - src/streamlit_app.py
+====================================================
+Main application file for src directory structure
 """
 
-import streamlit as st
-import pandas as pd
-import plotly.express as px
-import plotly.graph_objects as go
-import sqlite3
+# Import the main application from the parent directory or current directory
+import sys
 import os
-import tempfile
-import io
-import json
-import hashlib
-import logging
-import time
-import re
-from datetime import datetime, timedelta
-from typing import Dict, List, Optional, Any, Tuple
-from urllib.parse import urlparse, urljoin
-from contextlib import contextmanager
-import requests
-from bs4 import BeautifulSoup
-import base64
-from pathlib import Path
 
-# Configure logging for Hugging Face
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
+# Add current directory to path for imports
+current_dir = os.path.dirname(os.path.abspath(__file__))
+sys.path.insert(0, current_dir)
 
-# Page configuration
-st.set_page_config(
-    page_title="داشبورد اطلاعات حقوقی ایران",
-    page_icon="⚖️",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
-
-# Enhanced CSS with Fixed Sidebar Menu and Better Persian Typography
-def load_css():
-    st.markdown("""
-    <style>
-    /* Import Persian Fonts */
-    @import url('https://fonts.googleapis.com/css2?family=Vazirmatn:wght@300;400;500;600;700;800&display=swap');
-    @import url('https://fonts.googleapis.com/css2?family=Yekan+Bakh:wght@300;400;500;600;700&display=swap');
-    
-    /* Root Variables */
-    :root {
-        --primary-gradient: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-        --secondary-gradient: linear-gradient(135deg, #f8fafc 0%, #e2e8f0 100%);
-        --text-primary: #1a202c;
-        --text-secondary: #4a5568;
-        --text-light: #718096;
-        --white: #ffffff;
-        --shadow-light: 0 4px 6px rgba(0, 0, 0, 0.05);
-        --shadow-medium: 0 10px 25px rgba(0, 0, 0, 0.1);
-        --shadow-heavy: 0 20px 40px rgba(102, 126, 234, 0.2);
-        --border-radius: 16px;
-        --transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
-        --sidebar-width: 280px;
-    }
-    
-    /* Global Typography */
-    * {
-        font-family: 'Vazirmatn', 'Yekan Bakh', 'Tahoma', 'Arial', sans-serif !important;
-        font-feature-settings: "kern" 1, "liga" 1;
-        text-rendering: optimizeLegibility;
-        -webkit-font-smoothing: antialiased;
-        -moz-osx-font-smoothing: grayscale;
-    }
-    
-    /* Main Content Area */
-    .main {
-        direction: rtl;
-        text-align: right;
-        background: var(--secondary-gradient);
-        min-height: 100vh;
-        padding: 1.5rem 1.5rem 1.5rem var(--sidebar-width);
-        line-height: 1.8;
-        font-weight: 400;
-        transition: var(--transition);
-    }
-    
-    /* Fixed Sidebar */
-    .css-1d391kg {
-        position: fixed !important;
-        top: 0;
-        left: 0;
-        height: 100vh;
-        width: var(--sidebar-width);
-        background: var(--primary-gradient) !important;
-        z-index: 999999;
-        overflow-y: auto;
-        box-shadow: 4px 0 20px rgba(0, 0, 0, 0.15);
-        border-right: 1px solid rgba(255, 255, 255, 0.1);
-        backdrop-filter: blur(20px);
-    }
-    
-    .css-1d391kg .css-17eq0hr {
-        background: transparent !important;
-        padding: 0 !important;
-    }
-    
-    /* Sidebar Content */
-    .sidebar .sidebar-content {
-        background: transparent !important;
-        color: white !important;
-        padding: 2rem 1.5rem;
-        height: 100%;
-        overflow-y: auto;
-    }
-    
-    /* Sidebar Navigation Buttons */
-    .css-1d391kg .stButton > button {
-        width: 100% !important;
-        background: rgba(255, 255, 255, 0.1) !important;
-        color: white !important;
-        border: 1px solid rgba(255, 255, 255, 0.2) !important;
-        border-radius: 12px !important;
-        padding: 0.8rem 1.2rem !important;
-        margin: 0.3rem 0 !important;
-        font-family: 'Vazirmatn', sans-serif !important;
-        font-weight: 500 !important;
-        font-size: 0.95rem !important;
-        text-align: right !important;
-        direction: rtl !important;
-        transition: all 0.3s ease !important;
-        backdrop-filter: blur(10px) !important;
-    }
-    
-    .css-1d391kg .stButton > button:hover {
-        background: rgba(255, 255, 255, 0.2) !important;
-        transform: translateX(-5px) !important;
-        box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2) !important;
-        border-color: rgba(255, 255, 255, 0.3) !important;
-    }
-    
-    .css-1d391kg .stButton > button:active,
-    .css-1d391kg .stButton > button:focus {
-        background: rgba(255, 255, 255, 0.25) !important;
-        border-color: rgba(255, 255, 255, 0.4) !important;
-        box-shadow: 0 0 0 2px rgba(255, 255, 255, 0.3) !important;
-    }
-    
-    /* Sidebar Text and Elements */
-    .css-1d391kg .stMarkdown,
-    .css-1d391kg h1, .css-1d391kg h2, .css-1d391kg h3,
-    .css-1d391kg p, .css-1d391kg div {
-        color: white !important;
-        font-family: 'Vazirmatn', sans-serif !important;
-        text-align: right !important;
-        direction: rtl !important;
-    }
-    
-    .css-1d391kg .stMarkdown h3 {
-        font-size: 1.1rem !important;
-        font-weight: 600 !important;
-        margin: 1.5rem 0 1rem 0 !important;
-        text-align: center !important;
-        border-bottom: 2px solid rgba(255, 255, 255, 0.2) !important;
-        padding-bottom: 0.8rem !important;
-    }
-    
-    /* Sidebar Header */
-    .sidebar-header {
-        text-align: center;
-        padding: 1.5rem 1rem;
-        border-bottom: 2px solid rgba(255, 255, 255, 0.15);
-        margin-bottom: 2rem;
-    }
-    
-    .sidebar-header h2 {
-        color: white !important;
-        font-size: 1.4rem !important;
-        font-weight: 700 !important;
-        margin: 0 !important;
-        line-height: 1.4 !important;
-        text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
-    }
-    
-    .sidebar-header p {
-        color: rgba(255, 255, 255, 0.8) !important;
-        font-size: 0.85rem !important;
-        margin: 0.5rem 0 0 0 !important;
-        font-weight: 400 !important;
-    }
-    
-    /* Sidebar Stats */
-    .sidebar-stats {
-        background: rgba(255, 255, 255, 0.1);
-        border-radius: 12px;
-        padding: 1.5rem;
-        margin: 2rem 0;
-        backdrop-filter: blur(10px);
-        border: 1px solid rgba(255, 255, 255, 0.2);
-    }
-    
-    .sidebar-stats h3 {
-        color: white !important;
-        font-size: 1.1rem !important;
-        font-weight: 600 !important;
-        margin-bottom: 1rem !important;
-        text-align: center !important;
-    }
-    
-    .stat-item {
-        display: flex;
-        justify-content: space-between;
-        align-items: center;
-        padding: 0.5rem 0;
-        border-bottom: 1px solid rgba(255, 255, 255, 0.1);
-        direction: rtl;
-    }
-    
-    .stat-item:last-child {
-        border-bottom: none;
-    }
-    
-    .stat-label {
-        color: rgba(255, 255, 255, 0.8) !important;
-        font-size: 0.9rem;
-        font-weight: 400;
-    }
-    
-    .stat-value {
-        color: white !important;
-        font-size: 1rem;
-        font-weight: 600;
-    }
-    
-    /* Main Header */
-    .main-header {
-        background: var(--primary-gradient);
-        padding: 3rem 2.5rem;
-        border-radius: var(--border-radius);
-        color: var(--white);
-        margin-bottom: 2.5rem;
-        text-align: center;
-        box-shadow: var(--shadow-heavy);
-        position: relative;
-        overflow: hidden;
-    }
-    
-    .main-header::before {
-        content: '';
-        position: absolute;
-        top: -50%;
-        left: -50%;
-        width: 200%;
-        height: 200%;
-        background: linear-gradient(45deg, transparent, rgba(255,255,255,0.1), transparent);
-        transform: rotate(45deg);
-        animation: shimmer 4s infinite;
-    }
-    
-    @keyframes shimmer {
-        0% { transform: translateX(-100%) translateY(-100%) rotate(45deg); }
-        100% { transform: translateX(100%) translateY(100%) rotate(45deg); }
-    }
-    
-    .main-header h1 {
-        font-family: 'Yekan Bakh', 'Vazirmatn', sans-serif !important;
-        font-size: 2.5rem;
-        margin-bottom: 1rem;
-        font-weight: 700;
-        text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
-        line-height: 1.3;
-        letter-spacing: -0.5px;
-    }
-    
-    .main-header p {
-        font-size: 1.2rem;
-        opacity: 0.9;
-        margin: 0;
-        line-height: 1.6;
-        font-weight: 400;
-    }
-    
-    /* Typography Improvements */
-    h1, h2, h3, h4, h5, h6 {
-        font-family: 'Yekan Bakh', 'Vazirmatn', sans-serif !important;
-        font-weight: 600;
-        line-height: 1.4;
-        color: var(--text-primary);
-        margin-bottom: 1.2rem;
-    }
-    
-    h1 { font-size: 2.2rem; font-weight: 700; }
-    h2 { font-size: 1.8rem; font-weight: 600; }
-    h3 { font-size: 1.5rem; font-weight: 600; }
-    h4 { font-size: 1.3rem; font-weight: 500; }
-    
-    p, div, span, li {
-        font-family: 'Vazirmatn', sans-serif !important;
-        line-height: 1.8;
-        color: var(--text-secondary);
-        font-weight: 400;
-    }
-    
-    /* Strong Text */
-    strong, b {
-        font-weight: 600 !important;
-        color: var(--text-primary);
-    }
-    
-    /* Metric Cards */
-    .metric-card {
-        background: var(--primary-gradient);
-        padding: 2.5rem 2rem;
-        border-radius: var(--border-radius);
-        color: var(--white);
-        text-align: center;
-        margin: 1rem 0;
-        box-shadow: var(--shadow-medium);
-        transition: var(--transition);
-        position: relative;
-        overflow: hidden;
-        border: 1px solid rgba(255, 255, 255, 0.1);
-    }
-    
-    .metric-card::before {
-        content: '';
-        position: absolute;
-        top: 0;
-        left: -100%;
-        width: 100%;
-        height: 100%;
-        background: linear-gradient(90deg, transparent, rgba(255,255,255,0.2), transparent);
-        transition: left 0.6s ease;
-    }
-    
-    .metric-card:hover::before {
-        left: 100%;
-    }
-    
-    .metric-card:hover {
-        transform: translateY(-8px) scale(1.02);
-        box-shadow: 0 20px 40px rgba(102, 126, 234, 0.3);
-    }
-    
-    .metric-value {
-        font-family: 'Yekan Bakh', sans-serif !important;
-        font-size: 3rem;
-        font-weight: 800;
-        margin: 0.8rem 0;
-        text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
-        line-height: 1;
-    }
-    
-    .metric-label {
-        font-size: 1rem;
-        opacity: 0.9;
-        font-weight: 500;
-        letter-spacing: 0.5px;
-        line-height: 1.4;
-    }
-    
-    .metric-subtitle {
-        font-size: 0.85rem;
-        opacity: 0.7;
-        font-weight: 400;
-        margin-top: 0.5rem;
-    }
-    
-    /* Feature Cards */
-    .feature-card {
-        background: rgba(255, 255, 255, 0.95);
-        backdrop-filter: blur(20px);
-        padding: 2.5rem;
-        border-radius: var(--border-radius);
-        box-shadow: var(--shadow-light);
-        margin: 2rem 0;
-        border-right: 4px solid #667eea;
-        transition: var(--transition);
-        position: relative;
-        border: 1px solid rgba(102, 126, 234, 0.1);
-    }
-    
-    .feature-card:hover {
-        transform: translateY(-5px);
-        box-shadow: var(--shadow-medium);
-        border-right-width: 6px;
-    }
-    
-    .feature-card::before {
-        content: '';
-        position: absolute;
-        top: 0;
-        left: 0;
-        right: 0;
-        height: 3px;
-        background: var(--primary-gradient);
-        border-radius: var(--border-radius) var(--border-radius) 0 0;
-    }
-    
-    /* Status Indicators */
-    .status-indicator {
-        display: inline-flex;
-        align-items: center;
-        padding: 0.5rem 1.2rem;
-        border-radius: 25px;
-        font-size: 0.9rem;
-        font-weight: 500;
-        margin: 0.4rem 0.3rem;
-        box-shadow: var(--shadow-light);
-        transition: var(--transition);
-        font-family: 'Vazirmatn', sans-serif !important;
-    }
-    
-    .status-indicator:hover {
-        transform: translateY(-2px);
-        box-shadow: var(--shadow-medium);
-    }
-    
-    .status-success { background: #10b981; color: white; }
-    .status-warning { background: #f59e0b; color: white; }
-    .status-info { background: #3b82f6; color: white; }
-    .status-error { background: #ef4444; color: white; }
-    
-    /* Buttons */
-    .stButton > button {
-        background: var(--primary-gradient) !important;
-        color: white !important;
-        border: none !important;
-        border-radius: 12px !important;
-        padding: 0.8rem 2.5rem !important;
-        font-weight: 600 !important;
-        font-family: 'Vazirmatn', sans-serif !important;
-        font-size: 1rem !important;
-        transition: var(--transition) !important;
-        box-shadow: var(--shadow-light) !important;
-        line-height: 1.4 !important;
-        text-align: center !important;
-    }
-    
-    .stButton > button:hover {
-        transform: translateY(-3px) !important;
-        box-shadow: var(--shadow-medium) !important;
-    }
-    
-    .stButton > button:active {
-        transform: translateY(-1px) !important;
-    }
-    
-    /* Responsive Design */
-    @media (max-width: 1024px) {
-        :root { --sidebar-width: 250px; }
-        
-        .main {
-            padding-left: var(--sidebar-width);
-        }
-        
-        .css-1d391kg {
-            width: var(--sidebar-width);
-        }
-    }
-    
-    @media (max-width: 768px) {
-        :root { --sidebar-width: 0px; }
-        
-        .main {
-            padding-left: 1rem !important;
-            padding-right: 1rem !important;
-        }
-        
-        .css-1d391kg {
-            position: relative !important;
-            width: 100% !important;
-            height: auto !important;
-            margin-bottom: 1rem;
-        }
-        
-        .main-header h1 { 
-            font-size: 1.8rem; 
-        }
-        
-        .main-header p { 
-            font-size: 1rem; 
-        }
-        
-        .metric-value {
-            font-size: 2.2rem;
-        }
-    }
-    
-    /* Hide Streamlit Elements */
-    #MainMenu { visibility: hidden; }
-    footer { visibility: hidden; }
-    header { visibility: hidden; }
-    .stDeployButton { display: none; }
-    
-    /* Custom Scrollbar */
-    ::-webkit-scrollbar {
-        width: 8px;
-        height: 8px;
-    }
-    
-    ::-webkit-scrollbar-track {
-        background: rgba(255, 255, 255, 0.1);
-        border-radius: 4px;
-    }
-    
-    ::-webkit-scrollbar-thumb {
-        background: rgba(255, 255, 255, 0.3);
-        border-radius: 4px;
-    }
-    
-    ::-webkit-scrollbar-thumb:hover {
-        background: rgba(255, 255, 255, 0.5);
-    }
-    
-    /* Loading States */
-    .stSpinner > div {
-        border-top-color: #667eea !important;
-    }
-    
-    /* Alerts */
-    .stAlert {
-        direction: rtl !important;
-        text-align: right !important;
-        font-family: 'Vazirmatn', sans-serif !important;
-        border-radius: 12px !important;
-        font-weight: 500 !important;
-    }
-    
-    /* Footer in Sidebar */
-    .sidebar-footer {
-        position: absolute;
-        bottom: 1rem;
-        left: 1rem;
-        right: 1rem;
-        text-align: center;
-        padding: 1rem;
-        background: rgba(255, 255, 255, 0.1);
-        border-radius: 12px;
-        backdrop-filter: blur(10px);
-    }
-    
-    .sidebar-footer p {
-        color: rgba(255, 255, 255, 0.7) !important;
-        font-size: 0.8rem !important;
-        margin: 0 !important;
-        line-height: 1.4 !important;
-    }
-    </style>
-    """, unsafe_allow_html=True)
-
-# Enhanced Database Manager for Hugging Face Environment
-class DatabaseManager:
-    def __init__(self, db_path: str = None):
-        """Initialize DatabaseManager optimized for Hugging Face Spaces"""
-        self.logger = logging.getLogger(__name__)
-        
-        # For Hugging Face Spaces, use temp storage explicitly
-        if db_path:
-            self.db_path = db_path
-        else:
-            # Use /tmp/ directly for Hugging Face Spaces
-            self.db_path = "/tmp/iran_legal.db"
-            self.logger.info(f"🗄️ Using Hugging Face temp storage: {self.db_path}")
-        
-        self.initialize_database()
-    
-    def _find_writable_path(self, paths):
-        """Find the first writable path"""
-        for path in paths:
-            try:
-                directory = os.path.dirname(path)
-                if directory and not os.path.exists(directory):
-                    os.makedirs(directory, exist_ok=True)
-                
-                # Test write access
-                test_file = path + ".test"
-                with open(test_file, 'w') as f:
-                    f.write("test")
-                os.remove(test_file)
-                
-                self.logger.info(f"✅ Found writable path: {path}")
-                return path
-                
-            except (OSError, PermissionError) as e:
-                self.logger.warning(f"⚠️ Cannot write to {path}: {e}")
-                continue
-        
-        # Fallback
-        fallback_path = f"/tmp/iran_legal_{int(time.time())}.db"
-        self.logger.warning(f"⚠️ Using fallback path: {fallback_path}")
-        return fallback_path
-    
-    def initialize_database(self):
-        """Initialize database with error handling for Hugging Face"""
-        try:
-            with sqlite3.connect(self.db_path, timeout=30.0) as conn:
-                conn.execute("PRAGMA journal_mode=WAL;")
-                conn.execute("PRAGMA foreign_keys = ON;")
-                
-                # Test connection
-                cursor = conn.cursor()
-                cursor.execute("SELECT sqlite_version();")
-                version = cursor.fetchone()[0]
-                self.logger.info(f"📊 SQLite version: {version}")
-                
-                # Create tables
-                self._create_tables(conn)
-                
-                # Add sample data if database is empty
-                cursor.execute("SELECT COUNT(*) FROM documents")
-                doc_count = cursor.fetchone()[0]
-                
-                if doc_count == 0:
-                    self._add_sample_data(conn)
-                    self.logger.info("📝 Added sample data to empty database")
-                
-                self.logger.info("✅ Database initialized successfully")
-                
-        except Exception as e:
-            self.logger.error(f"❌ Database initialization failed: {e}")
-            # Create minimal fallback database
-            self._create_fallback_database()
-    
-    def _create_fallback_database(self):
-        """Create a minimal in-memory database as fallback"""
-        try:
-            self.db_path = ":memory:"
-            with sqlite3.connect(self.db_path) as conn:
-                self._create_tables(conn)
-                self._add_minimal_sample_data(conn)
-            self.logger.info("🆘 Created fallback in-memory database")
-        except Exception as e:
-            self.logger.error(f"❌ Even fallback database failed: {e}")
-    
-    def _create_tables(self, conn):
-        """Create database tables"""
-        cursor = conn.cursor()
-        
-        # Documents table
-        cursor.execute("""
-            CREATE TABLE IF NOT EXISTS documents (
-                id INTEGER PRIMARY KEY AUTOINCREMENT,
-                title TEXT NOT NULL,
-                content TEXT NOT NULL,
-                source TEXT,
-                category TEXT,
-                ai_score REAL DEFAULT 0.0,
-                keywords TEXT,
-                created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-                file_size INTEGER DEFAULT 0,
-                language TEXT DEFAULT 'fa'
-            )
-        """)
-        
-        # Scraped items table
-        cursor.execute("""
-            CREATE TABLE IF NOT EXISTS scraped_items (
-                id TEXT PRIMARY KEY,
-                url TEXT NOT NULL,
-                title TEXT,
-                content TEXT,
-                domain TEXT,
-                rating_score REAL DEFAULT 0.0,
-                word_count INTEGER DEFAULT 0,
-                created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-                status TEXT DEFAULT 'completed'
-            )
-        """)
-        
-        # Create indexes
-        cursor.execute("CREATE INDEX IF NOT EXISTS idx_docs_category ON documents(category);")
-        cursor.execute("CREATE INDEX IF NOT EXISTS idx_docs_score ON documents(ai_score);")
-        cursor.execute("CREATE INDEX IF NOT EXISTS idx_scraped_domain ON scraped_items(domain);")
-        
-        conn.commit()
-    
-    def _add_sample_data(self, conn):
-        """Add comprehensive sample data"""
-        sample_documents = [
-            {
-                'title': 'قانون اساسی جمهوری اسلامی ایران - اصول کلی',
-                'content': '''فصل اول - اصول کلی
-
-اصل یکم: حکومت ایران، جمهوری اسلامی است که ملت ایران بر اساس ایمان دیرینه‌اش به حاکمیت حق و عدالت قرآن، در انقلاب اسلامی سال ۱۳۵۷ تحت رهبری امام خمینی به آن رأی مثبت داد.
-
-اصل دوم: جمهوری اسلامی، نظامی است مبتنی بر ایمان به خدای یکتا، حاکمیت و قانون الهی، عدل، ایمان و تقوا.
-
-اصل سوم: برای نیل به اهداف مندرج در اصل دوم، دولت جمهوری اسلامی ایران موظف است تمام امکانات خود را برای دستیابی به اهداف زیر به کار گیرد:
-۱- ایجاد محیط مساعد برای رشد فضایل اخلاقی
-۲- ارتقاء سطح آگاهی عمومی
-۳- آموزش و پرورش رایگان برای همه''',
-                'source': 'قانون اساسی ج.ا.ایران',
-                'category': 'قانون',
-                'ai_score': 0.95,
-                'keywords': json.dumps(['قانون اساسی', 'جمهوری اسلامی', 'حاکمیت']),
-                'file_size': 2450,
-                'language': 'fa'
-            },
-            {
-                'title': 'قانون مجازات اسلامی - مقدمات',
-                'content': '''باب اول - احکام عمومی
-
-ماده ۱- مجازات‌ها به اعتبار کیفیت به سه دسته تقسیم می‌شوند:
-الف) حدود
-ب) قصاص  
-ج) تعزیرات
-
-ماده ۲- حدود عبارت است از مجازات‌هایی که نوع و میزان آنها در شرع مقدس تعیین شده است.
-
-ماده ۳- قصاص عبارت است از مجازاتی که در شرع مقدس تعیین شده و حق العبد محسوب می‌شود.
-
-ماده ۴- تعزیرات عبارت است از مجازات‌هایی غیر از حدود و قصاص که برای تأدیب مرتکب تعیین می‌شود.''',
-                'source': 'قانون مجازات اسلامی',
-                'category': 'قانون',
-                'ai_score': 0.88,
-                'keywords': json.dumps(['مجازات', 'حدود', 'قصاص', 'تعزیرات']),
-                'file_size': 1850,
-                'language': 'fa'
-            },
-            {
-                'title': 'نمونه قرارداد خرید و فروش',
-                'content': '''قرارداد خرید و فروش
-
-طرفین قرارداد:
-فروشنده: .........................
-خریدار: .........................
-
-ماده ۱- موضوع قرارداد
-فروشنده متعهد می‌شود ملک واقع در آدرس مشخص شده را به خریدار منتقل نماید.
-
-ماده ۲- مبلغ قرارداد  
-مبلغ کل قرارداد ................ ریال می‌باشد.
-
-ماده ۳- تعهدات طرفین
-فروشنده متعهد است اسناد مالکیت را تحویل دهد.
-خریدار متعهد است مبلغ قرارداد را پرداخت نماید.''',
-                'source': 'نمونه قرارداد',
-                'category': 'قرارداد',
-                'ai_score': 0.75,
-                'keywords': json.dumps(['قرارداد', 'خرید', 'فروش', 'طرفین']),
-                'file_size': 1200,
-                'language': 'fa'
-            }
-        ]
-        
-        for doc in sample_documents:
-            conn.execute("""
-                INSERT INTO documents (title, content, source, category, ai_score, keywords, file_size, language)
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?)
-            """, (
-                doc['title'], doc['content'], doc['source'], doc['category'],
-                doc['ai_score'], doc['keywords'], doc['file_size'], doc['language']
-            ))
-        
-        sample_scraped = [
-            {
-                'id': 'sample_hf_001',
-                'url': 'https://dastour.ir/sample',
-                'title': 'نمونه محتوای قانونی',
-                'content': 'این یک نمونه محتوای قانونی است که از وب‌سایت‌های معتبر جمع‌آوری شده است.',
-                'domain': 'dastour.ir',
-                'rating_score': 0.85,
-                'word_count': 25,
-                'status': 'completed'
-            }
-        ]
-        
-        for item in sample_scraped:
-            conn.execute("""
-                INSERT INTO scraped_items (id, url, title, content, domain, rating_score, word_count, status)
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?)
-            """, (
-                item['id'], item['url'], item['title'], item['content'],
-                item['domain'], item['rating_score'], item['word_count'], item['status']
-            ))
-        
-        conn.commit()
-    
-    def _add_minimal_sample_data(self, conn):
-        """Add minimal sample data for fallback"""
-        conn.execute("""
-            INSERT INTO documents (title, content, source, category, ai_score, keywords, file_size, language)
-            VALUES (?, ?, ?, ?, ?, ?, ?, ?)
-        """, (
-            'نمونه سند قانونی',
-            'این یک نمونه سند قانونی برای نمایش عملکرد سیستم است.',
-            'نمونه',
-            'قانون',
-            0.5,
-            json.dumps(['نمونه', 'قانون']),
-            100,
-            'fa'
-        ))
-        conn.commit()
-    
-    @contextmanager
-    def get_connection(self):
-        """Get database connection with error handling"""
-        conn = None
-        try:
-            conn = sqlite3.connect(self.db_path, timeout=10.0)
-            conn.row_factory = sqlite3.Row
-            yield conn
-        except Exception as e:
-            self.logger.error(f"Database connection error: {e}")
-            raise
-        finally:
-            if conn:
-                conn.close()
-    
-    def get_statistics(self) -> Dict:
-        """Get database statistics"""
-        stats = {
-            'total_documents': 0,
-            'total_scraped': 0,
-            'avg_ai_score': 0.0,
-            'avg_rating': 0.0,
-            'categories': {}
-        }
-        
-        try:
-            with self.get_connection() as conn:
-                cursor = conn.execute("SELECT COUNT(*) FROM documents")
-                stats['total_documents'] = cursor.fetchone()[0]
-                
-                cursor = conn.execute("SELECT AVG(ai_score) FROM documents WHERE ai_score > 0")
-                result = cursor.fetchone()[0]
-                stats['avg_ai_score'] = result if result else 0.0
-                
-                cursor = conn.execute("SELECT COUNT(*) FROM scraped_items")
-                stats['total_scraped'] = cursor.fetchone()[0]
-                
-                cursor = conn.execute("SELECT AVG(rating_score) FROM scraped_items WHERE rating_score > 0")
-                result = cursor.fetchone()[0]
-                stats['avg_rating'] = result if result else 0.0
-                
-                cursor = conn.execute("""
-                    SELECT category, COUNT(*) 
-                    FROM documents 
-                    WHERE category IS NOT NULL 
-                    GROUP BY category
-                """)
-                stats['categories'] = dict(cursor.fetchall())
-                
-        except Exception as e:
-            self.logger.error(f"Error getting statistics: {e}")
-        
-        return stats
-    
-    def get_documents(self, limit: int = 100) -> List[Dict]:
-        """Get documents from database"""
-        try:
-            with self.get_connection() as conn:
-                cursor = conn.execute("""
-                    SELECT * FROM documents 
-                    ORDER BY created_at DESC 
-                    LIMIT ?
-                """, (limit,))
-                return [dict(row) for row in cursor.fetchall()]
-        except Exception as e:
-            self.logger.error(f"Error getting documents: {e}")
-            return []
-    
-    def get_scraped_items(self, limit: int = 100) -> List[Dict]:
-        """Get scraped items from database"""
-        try:
-            with self.get_connection() as conn:
-                cursor = conn.execute("""
-                    SELECT * FROM scraped_items 
-                    ORDER BY created_at DESC 
-                    LIMIT ?
-                """, (limit,))
-                return [dict(row) for row in cursor.fetchall()]
-        except Exception as e:
-            self.logger.error(f"Error getting scraped items: {e}")
-            return []
-
-# Simplified AI Analysis Engine for Hugging Face
-class AIAnalysisEngine:
-    def __init__(self):
-        self.legal_keywords = {
-            'قانون': ['قانون', 'ماده', 'تبصره', 'بند', 'فصل', 'باب'],
-            'قرارداد': ['قرارداد', 'عقد', 'طرفین', 'متعاهدین'],
-            'حکم': ['حکم', 'رای', 'دادگاه', 'قاضی'],
-            'اداری': ['اداره', 'سازمان', 'وزارت', 'دولت']
-        }
-    
-    def analyze_text(self, text: str, title: str = "") -> Dict:
-        """Analyze text and return analysis"""
-        if not text:
-            return {'ai_score': 0.0, 'category': 'نامشخص', 'keywords': []}
-        
-        quality_score = self._calculate_quality_score(text)
-        category = self._predict_category(text + " " + title)
-        keywords = self._extract_keywords(text)
-        
-        return {
-            'ai_score': quality_score,
-            'category': category,
-            'keywords': keywords,
-            'word_count': len(text.split()),
-            'char_count': len(text)
-        }
-    
-    def _calculate_quality_score(self, text: str) -> float:
-        """Calculate text quality score"""
-        score = 0.0
-        word_count = len(text.split())
-        
-        # Length scoring
-        if 50 <= word_count <= 5000:
-            score += 0.3
-        elif word_count >= 20:
-            score += 0.1
-        
-        # Legal terms scoring
-        legal_term_count = 0
-        for category_terms in self.legal_keywords.values():
-            for term in category_terms:
-                legal_term_count += text.count(term)
-        
-        if legal_term_count >= 3:
-            score += 0.4
-        elif legal_term_count >= 1:
-            score += 0.2
-        
-        # Persian language bonus
-        persian_ratio = len(re.findall(r'[\u0600-\u06FF]', text)) / max(len(text), 1)
-        if persian_ratio > 0.5:
-            score += 0.3
-        
-        return min(score, 1.0)
-    
-    def _predict_category(self, text: str) -> str:
-        """Predict document category"""
-        text_lower = text.lower()
-        category_scores = {}
-        
-        for category, keywords in self.legal_keywords.items():
-            score = sum(text_lower.count(keyword) for keyword in keywords)
-            category_scores[category] = score
-        
-        if category_scores:
-            best_category = max(category_scores, key=category_scores.get)
-            return best_category if category_scores[best_category] > 0 else 'عمومی'
-        
-        return 'عمومی'
-    
-    def _extract_keywords(self, text: str, max_keywords: int = 5) -> List[str]:
-        """Extract keywords from text"""
-        words = re.findall(r'[\u0600-\u06FF]{3,}', text)
-        word_freq = {}
-        
-        for word in words:
-            if len(word) > 2:
-                word_freq[word] = word_freq.get(word, 0) + 1
-        
-        sorted_words = sorted(word_freq.items(), key=lambda x: x[1], reverse=True)
-        return [word[0] for word in sorted_words[:max_keywords]]
-
-# UI Helper Functions
-def show_status_message(message: str, status_type: str = "info"):
-    """Show styled status message"""
-    status_class = f"status-{status_type}"
-    st.markdown(f'<div class="status-indicator {status_class}">{message}</div>', unsafe_allow_html=True)
-
-def create_metric_card(title: str, value: str, subtitle: str = ""):
-    """Create a beautiful metric card with enhanced typography"""
-    return f"""
-    <div class="metric-card">
-        <div class="metric-label">{title}</div>
-        <div class="metric-value">{value}</div>
-        {f'<div class="metric-subtitle">{subtitle}</div>' if subtitle else ''}
-    </div>
-    """
-
-# Initialize services for Hugging Face
-@st.cache_resource
-def initialize_services():
-    """Initialize services optimized for Hugging Face"""
+try:
+    # Try to import from current directory
+    from app import main
+except ImportError:
     try:
-        db_manager = DatabaseManager()
-        ai_engine = AIAnalysisEngine()
-        
-        # Check database health
-        stats = db_manager.get_statistics()
-        
-        if stats['total_documents'] > 0:
-            st.success(f"✅ Database loaded successfully ({stats['total_documents']} documents)")
-        else:
-            st.warning("⚠️ Database is empty, using fallback data")
-        
-        return db_manager, ai_engine
-        
-    except Exception as e:
-            st.error(f"An error occurred: {e}")
+        # Try to import from parent directory
+        parent_dir = os.path.dirname(current_dir)
+        sys.path.insert(0, parent_dir)
+        from app import main
+    except ImportError:
+        import streamlit as st
+        st.error("❌ Could not import main application. Please ensure app.py is in the correct location.")
+        st.stop()
+
+if __name__ == "__main__":
+    main()