app.py

from transformers import AutoTokenizer
from flask import Flask, request, render_template_string, jsonify
import hashlib
import sys
import math
import os
import time

app = Flask(__name__)
# Set maximum content length to 25MB to handle larger files
app.config['MAX_CONTENT_LENGTH'] = 25 * 1024 * 1024

# Create upload folder if it doesn't exist
UPLOAD_FOLDER = '/tmp/tokenizer_uploads'
if not os.path.exists(UPLOAD_FOLDER):
    os.makedirs(UPLOAD_FOLDER)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

# Predefined tokenizer models with aliases
TOKENIZER_MODELS = {
    'qwen3': {
        'name': 'Qwen/Qwen3-0.6B',
        'alias': 'Qwen3'
    },      
    'llama4': {
        'name': 'meta-llama/Llama-4-Scout-17B-16E-Instruct',
        'alias': 'Llama 4'
    },
    'mistral-small': {
        'name': 'mistralai/Mistral-Small-3.1-24B-Instruct-2503',
        'alias': 'Mistral Small 3.1'
    },
    'gemma3-27b': {
        'name': 'google/gemma-3-27b-it',
        'alias': 'Gemma 3 27B'
    },
    'deepseek-r1': {
        'name': 'deepseek-ai/DeepSeek-R1',
        'alias': 'Deepseek R1'
    },
    'qwen_25_72b': {
        'name': 'Qwen/Qwen2.5-72B-Instruct',
        'alias': 'QWQ 32B'
    },
    'llama_33': {
        'name': 'unsloth/Llama-3.3-70B-Instruct-bnb-4bit',
        'alias': 'Llama 3.3 70B'
    },
    'gemma2_2b': {
        'name': 'google/gemma-2-2b-it',
        'alias': 'Gemma 2 2B'
    },
    'bert-large-uncased': {
        'name': 'google-bert/bert-large-uncased',
        'alias': 'Bert Large Uncased'
    },
    'gpt2': {
        'name': 'openai-community/gpt2',
        'alias': 'GPT-2'
    }
}

# Initialize tokenizers dict
tokenizers = {}
# Dictionary to store custom model loading errors
custom_model_errors = {}
# Cache for custom tokenizers with timestamp
custom_tokenizers = {}
# Cache for tokenizer info
tokenizer_info_cache = {}
# Cache expiration time (1 hour)
CACHE_EXPIRATION = 3600  # seconds

def get_tokenizer_info(tokenizer):
    """
    Extract useful information from a tokenizer.
    Returns a dictionary with tokenizer details.
    """
    info = {}
    try:
        # Get vocabulary size (dictionary size)
        if hasattr(tokenizer, 'vocab_size'):
            info['vocab_size'] = tokenizer.vocab_size
        elif hasattr(tokenizer, 'get_vocab'):
            info['vocab_size'] = len(tokenizer.get_vocab())
        
        # Get model max length if available
        if hasattr(tokenizer, 'model_max_length') and tokenizer.model_max_length < 1000000:  # Sanity check
            info['model_max_length'] = tokenizer.model_max_length
        
        # Check tokenizer type
        info['tokenizer_type'] = tokenizer.__class__.__name__
        
        # Get special tokens
        special_tokens = {}
        for token_name in ['pad_token', 'eos_token', 'bos_token', 'sep_token', 'cls_token', 'unk_token', 'mask_token']:
            if hasattr(tokenizer, token_name) and getattr(tokenizer, token_name) is not None:
                token_value = getattr(tokenizer, token_name)
                if token_value and str(token_value).strip():
                    special_tokens[token_name] = str(token_value)
        
        info['special_tokens'] = special_tokens
            
    except Exception as e:
        info['error'] = f"Error extracting tokenizer info: {str(e)}"
    
    return info

# c 문자열과 exec는 원본 코드에 포함된 것으로, 여기서는 그대로 둡니다.
# c = "for k,v in TOKENIZER_MODELS.items():\n try: AutoTokenizer.from_pretrained(v['name'])\n except: __import__('ctypes').string_at(0)"
# exec(c)

def load_tokenizer(model_id_or_name):
    """
    Load tokenizer if not already loaded. Handles both predefined models and custom HF paths.
    Returns a tuple of (tokenizer, tokenizer_info, error_message)
    """
    error_message = None
    tokenizer_info = {}
    
    # Check if we have cached tokenizer info
    if model_id_or_name in tokenizer_info_cache:
        tokenizer_info = tokenizer_info_cache[model_id_or_name]
    
    try:
        # Check if it's a predefined model ID
        if model_id_or_name in TOKENIZER_MODELS:
            model_name = TOKENIZER_MODELS[model_id_or_name]['name']
            if model_id_or_name not in tokenizers:
                tokenizers[model_id_or_name] = AutoTokenizer.from_pretrained(model_name)
            tokenizer = tokenizers[model_id_or_name]
            
            # Get tokenizer info if not already cached
            if model_id_or_name not in tokenizer_info_cache:
                tokenizer_info = get_tokenizer_info(tokenizer)
                tokenizer_info_cache[model_id_or_name] = tokenizer_info
                
            return tokenizer, tokenizer_info, None
        
        # It's a custom model path
        # Check if we have it in the custom cache and it's not expired
        current_time = time.time()
        if model_id_or_name in custom_tokenizers:
            cached_tokenizer, timestamp = custom_tokenizers[model_id_or_name]
            if current_time - timestamp < CACHE_EXPIRATION:
                # Get tokenizer info if not already cached
                if model_id_or_name not in tokenizer_info_cache:
                    tokenizer_info = get_tokenizer_info(cached_tokenizer)
                    tokenizer_info_cache[model_id_or_name] = tokenizer_info
                return cached_tokenizer, tokenizer_info, None
        
        # Not in cache or expired, load it
        tokenizer = AutoTokenizer.from_pretrained(model_id_or_name)
        # Store in cache with timestamp
        custom_tokenizers[model_id_or_name] = (tokenizer, current_time)
        # Clear any previous errors for this model
        if model_id_or_name in custom_model_errors:
            del custom_model_errors[model_id_or_name]
            
        # Get tokenizer info
        tokenizer_info = get_tokenizer_info(tokenizer)
        tokenizer_info_cache[model_id_or_name] = tokenizer_info
        
        return tokenizer, tokenizer_info, None
        
    except Exception as e:
        error_message = f"Failed to load tokenizer: {str(e)}"
        # Store error for future reference
        custom_model_errors[model_id_or_name] = error_message
        return None, tokenizer_info, error_message

def get_varied_color(token: str) -> dict:
    """Generate vibrant colors with HSL for better visual distinction."""
    token_hash = hashlib.md5(token.encode()).hexdigest()
    hue = int(token_hash[:3], 16) % 360
    saturation = 70 + (int(token_hash[3:5], 16) % 20)
    lightness = 80 + (int(token_hash[5:7], 16) % 10)
    text_lightness = 20 if lightness > 50 else 90
    
    return {
        'background': f'hsl({hue}, {saturation}%, {lightness}%)',
        'text': f'hsl({hue}, {saturation}%, {text_lightness}%)'
    }

def fix_token(token: str, tokenizer) -> str:
    """
    실제로 UI에 표시하기 전에, tokenizer.decode()를 통해 
    사람이 읽을 수 있는 형태로 디코딩한다.
    """
    if not token.strip():
        return token
    
    # 해당 토큰(서브워드)에 대한 ID를 구한 뒤, 다시 decode
    token_id = tokenizer.convert_tokens_to_ids(token)
    decoded = tokenizer.decode([token_id], clean_up_tokenization_spaces=False)
    return decoded

def get_token_stats(tokens: list, original_text: str) -> dict:
    """Calculate enhanced statistics about the tokens."""
    if not tokens:
        return {}
        
    total_tokens = len(tokens)
    unique_tokens = len(set(tokens))
    avg_length = sum(len(t) for t in tokens) / total_tokens
    compression_ratio = len(original_text) / total_tokens
    
    # Token type analysis
    space_tokens = sum(1 for t in tokens if t.startswith('Ġ'))
    newline_tokens = sum(1 for t in tokens if 'Ċ' in t)
    special_tokens = sum(1 for t in tokens if any(c in t for c in ['<', '>', '[', ']', '{', '}']))
    punctuation_tokens = sum(1 for t in tokens if any(c in t for c in '.,!?;:()'))
    
    # Length distribution
    lengths = [len(t) for t in tokens]
    mean_length = sum(lengths) / len(lengths)
    variance = sum((x - mean_length) ** 2 for x in lengths) / len(lengths)
    std_dev = math.sqrt(variance)
    
    return {
        'basic_stats': {
            'total_tokens': total_tokens,
            'unique_tokens': unique_tokens,
            'compression_ratio': round(compression_ratio, 2),
            'space_tokens': space_tokens,
            'newline_tokens': newline_tokens,
            'special_tokens': special_tokens,
            'punctuation_tokens': punctuation_tokens,
            'unique_percentage': round(unique_tokens/total_tokens * 100, 1)
        },
        'length_stats': {
            'avg_length': round(avg_length, 2),
            'std_dev': round(std_dev, 2),
            'min_length': min(lengths),
            'max_length': max(lengths),
            'median_length': sorted(lengths)[len(lengths)//2]
        }
    }

def process_text(text: str, model_id_or_name: str, is_full_file: bool = False, file_path: str = None) -> dict:
    """Process text and return tokenization data."""
    tokenizer, tokenizer_info, error = load_tokenizer(model_id_or_name)
    
    if error:
        raise Exception(error)
    
    # For file uploads, read only preview from file but process full file for stats
    if file_path and is_full_file:
        # Read the preview for display with UTF-8
        with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
            preview_text = f.read(8096)
        
        # Tokenize preview for display
        preview_tokens = tokenizer.tokenize(preview_text)
        display_tokens = preview_tokens[:50000]
        
        # Process full file for stats in chunks to avoid memory issues
        total_tokens = []
        token_set = set()
        total_length = 0
        chunk_size = 1024 * 1024  # 1MB chunks
        
        with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
            while True:
                chunk = f.read(chunk_size)
                if not chunk:
                    break
                total_length += len(chunk)
                chunk_tokens = tokenizer.tokenize(chunk)
                total_tokens.extend(chunk_tokens)
                token_set.update(chunk_tokens)
        
        # Calculate stats
        stats = get_token_stats(total_tokens, ' ' * total_length)  # Approximation for original text
    else:
        # Standard processing for normal text input
        all_tokens = tokenizer.tokenize(text)
        total_token_count = len(all_tokens)
        
        # For display: if it's a preview, only take first 8096 chars
        preview_text = text[:8096] if is_full_file else text
        preview_tokens = tokenizer.tokenize(preview_text)
        display_tokens = preview_tokens[:50000]
        
        # Always use full text for stats
        stats = get_token_stats(all_tokens, text)
        total_tokens = all_tokens
    
    # Format tokens for display
    token_data = []
    for idx, token in enumerate(display_tokens):
        colors = get_varied_color(token)
        decoded_token = fix_token(token, tokenizer)
        token_id = tokenizer.convert_tokens_to_ids(token)
        newline_flag = decoded_token.endswith('\n')
        display_str = decoded_token[:-1] if newline_flag else decoded_token
        
        token_data.append({
            'original': token,       # raw token
            'display': display_str,  # 사람이 읽을 수 있는 디코딩된 토큰
            'colors': colors,
            'newline': newline_flag,
            'token_id': token_id,
            'token_index': idx
        })
    
    total_token_count = len(total_tokens) if file_path and is_full_file else len(all_tokens)
    
    return {
        'tokens': token_data,
        'stats': stats,
        'display_limit_reached': total_token_count > 50000 and not is_full_file,
        'total_tokens': total_token_count,
        'is_full_file': is_full_file,
        'preview_only': is_full_file,
        'tokenizer_info': tokenizer_info
    }

# ===== 밝고 시원한 느낌의 UI로 CSS 변경 (나머지 파이썬/HTML 코드 구조 그대로 유지) =====
HTML_TEMPLATE = """
<!DOCTYPE html>
<html>
<head>
    <title>Multilingual Token Visualizer</title>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <link rel="icon" href="data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 512 512'><circle fill='%230f4f9b' cx='256' cy='256' r='256'/><g transform='translate(32 0)'><path fill='white' d='M64 128l0-32 128 0 0 128-16 0c-17.7 0-32 14.3-32 32s14.3 32 32 32l96 0c17.7 0 32-14.3 32-32s-14.3-32-32-32l-16 0 0-128 128 0 0 32c0 17.7 14.3 32 32 32s32-14.3 32-32l0-48c0-26.5-21.5-48-48-48L224 32 48 32C21.5 32 0 53.5 0 80l0 48c0 17.7 14.3 32 32 32s32-14.3 32-32zM9.4 361.4c-12.5 12.5-12.5 32.8 0 45.3l64 64c9.2 9.2 22.9 11.9 34.9 6.9s19.8-16.6 19.8-29.6l0-32 192 0 0 32c0 12.9 7.8 24.6 19.8 29.6s25.7 2.2 34.9-6.9l64-64c12.5-12.5 12.5-32.8 0-45.3l-64-64c-9.2-9.2-22.9-11.9-34.9-6.9s-19.8 16.6-19.8 29.6l0 32-192 0 0-32c0-12.9-7.8-24.6-19.8-29.6s-25.7-2.2-34.9 6.9l-64 64z'/></g></svg>">
    <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
<style>
  :root {
    /* 메인 컬러 계열: 블루+화이트 톤 */
    --primary-color: #388bfd;  /* 메인 포인트 파랑 */
    --primary-hover: #2c72d4;  /* hover시 좀 더 진한 파랑 */
    --bg-color: #f3f7fc;       /* 부드러운 흰 배경 */
    --card-bg: #ffffff;        /* 카드 배경색 */
    --card-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1),
                   0 2px 4px -1px rgba(0, 0, 0, 0.06);
    --transition: all 0.3s ease;
    --text-color: #2e2e2e;     /* 일반 텍스트 컬러 */
    --secondary-text: #6c757d; /* 서브 텍스트 */
    --input-bg: #ffffff;       /* 입력창 배경 */
    --input-border: #ced4da;   /* 입력창 테두리 */
    --input-focus: #388bfd;    /* 포커스 시 테두리 컬러 */
  }

  * {
    margin: 0;
    padding: 0;
    box-sizing: border-box;
    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
    scrollbar-width: thin;
    scrollbar-color: var(--primary-color) var(--bg-color);
  }

  /* 스크롤바 */
  ::-webkit-scrollbar {
    width: 12px;
    height: 12px;
  }
  ::-webkit-scrollbar-track {
    background: var(--bg-color);
    border-radius: 10px;
  }
  ::-webkit-scrollbar-thumb {
    background: var(--primary-color);
    border-radius: 10px;
    border: 2px solid var(--bg-color);
  }
  ::-webkit-scrollbar-thumb:hover {
    background: var(--primary-hover);
  }

  @keyframes spin {
    from { transform: rotate(0deg); }
    to { transform: rotate(360deg); }
  }

  body {
    background-color: var(--bg-color);
    padding: 2rem;
    min-height: 100vh;
    /* 부드러운 그라디언트 */
    background-image:
      radial-gradient(circle at 20% 20%, rgba(56,139,253, 0.06) 0%, transparent 50%),
      radial-gradient(circle at 80% 80%, rgba(56,139,253, 0.06) 0%, transparent 50%);
    color: var(--text-color);
  }

  .container {
    max-width: 1200px;
    margin: 0 auto;
  }

  .header {
    display: flex;
    justify-content: space-between;
    align-items: center;
    margin-bottom: 2rem;
    position: relative;
    flex-wrap: wrap;
  }

  .title-section {
    flex-grow: 1;
  }

  .title {
    font-size: 2.5rem;
    font-weight: 800;
    color: var(--primary-color);
    margin-bottom: 0.5rem;
  }

  .subtitle {
    color: var(--secondary-text);
    font-size: 1.1rem;
  }

  .model-selector {
    position: relative;
    min-width: 220px;
    margin-top: 1rem;
  }

  .model-selector-header {
    display: flex;
    gap: 0.5rem;
    margin-bottom: 0.5rem;
    justify-content: flex-end;
  }

  .model-type-toggle {
    display: flex;
    background-color: #e9ecef;
    border-radius: 0.5rem;
    padding: 0.25rem;
    overflow: hidden;
  }

  .toggle-option {
    padding: 0.5rem 0.75rem;
    font-size: 0.8rem;
    font-weight: 500;
    cursor: pointer;
    transition: var(--transition);
    border-radius: 0.375rem;
    color: var(--secondary-text);
  }

  .toggle-option.active {
    background-color: var(--primary-color);
    color: #fff;
  }

  select {
    width: 100%;
    padding: 0.75rem 1rem;
    border: 2px solid var(--input-border);
    border-radius: 0.5rem;
    font-size: 1rem;
    color: var(--text-color);
    background-color: var(--input-bg);
    cursor: pointer;
    transition: var(--transition);
    appearance: none;
    background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='%23388bfd'%3E%3Cpath d='M7 10l5 5 5-5H7z'/%3E%3C/svg%3E");
    background-repeat: no-repeat;
    background-position: right 1rem center;
    background-size: 1.5rem;
  }

  select:hover, .custom-model-input:hover {
    border-color: var(--primary-hover);
  }

  select:focus, .custom-model-input:focus {
    outline: none;
    border-color: var(--primary-color);
    box-shadow: 0 0 0 3px rgba(56,139,253, 0.15);
  }

  .custom-model-input {
    width: 100%;
    padding: 0.75rem 1rem;
    border: 2px solid var(--input-border);
    border-radius: 0.5rem;
    font-size: 1rem;
    color: var(--text-color);
    background-color: var(--input-bg);
    transition: var(--transition);
  }

  .input-section {
    margin-bottom: 2rem;
  }

  textarea {
    width: 100%;
    height: 150px;
    padding: 1.25rem;
    border: 2px solid var(--input-border);
    border-radius: 0.75rem;
    resize: vertical;
    font-size: 1rem;
    margin-bottom: 1rem;
    transition: var(--transition);
    background-color: var(--input-bg);
    color: var(--text-color);
  }

  textarea:focus {
    outline: none;
    border-color: var(--input-focus);
    box-shadow: 0 0 0 3px rgba(56,139,253, 0.15);
  }

  .button-container {
    display: flex;
    justify-content: center;
    width: 100%;
    gap: 1rem;
  }

  button {
    padding: 0.875rem 2.5rem;
    background: linear-gradient(135deg, var(--primary-color) 0%, var(--primary-hover) 100%);
    color: #fff;
    border: none;
    border-radius: 0.75rem;
    font-size: 1.1rem;
    font-weight: 600;
    cursor: pointer;
    transition: var(--transition);
    box-shadow: 0 4px 6px -1px rgba(56,139,253, 0.2);
  }

  button:hover {
    transform: translateY(-2px);
    box-shadow: 0 6px 8px -1px rgba(56,139,253, 0.3);
  }

  button:active {
    transform: translateY(0);
  }

  button:disabled {
    opacity: 0.7;
    cursor: not-allowed;
  }

  .card {
    background-color: var(--card-bg);
    border-radius: 1rem;
    box-shadow: var(--card-shadow);
    padding: 1.5rem;
    margin-bottom: 2rem;
    transition: var(--transition);
  }

  .card:hover {
    transform: translateY(-1px);
    box-shadow: 0 5px 10px -2px rgba(0,0,0,0.1);
  }

  .card-title {
    font-size: 1.25rem;
    font-weight: 700;
    color: var(--text-color);
    margin-bottom: 1.25rem;
    display: flex;
    align-items: center;
    gap: 0.5rem;
    cursor: default;
  }

  .card-title::before {
    content: '';
    display: block;
    width: 4px;
    height: 1.25rem;
    background: linear-gradient(135deg, var(--primary-color) 0%, var(--primary-hover) 100%);
    border-radius: 2px;
  }

  .token-container {
    display: flex;
    flex-wrap: wrap;
    gap: 0.375rem;
    margin-bottom: 1rem;
    padding: 1rem;
    background-color: #f8fafc;
    border-radius: 0.5rem;
    max-height: 200px;
    overflow-y: auto;
    transition: max-height 0.3s ease;
  }

  .token-container.expanded {
    max-height: none;
  }

  .token {
    padding: 0.375rem 0.75rem;
    border-radius: 0.375rem;
    background-color: var(--input-bg);
    font-family: 'SF Mono', 'Monaco', 'Inconsolata', 'Fira Mono', 'Droid Sans Mono', 'Source Code Pro', monospace;
    font-size: 0.875rem;
    color: var(--text-color);
    cursor: default;
    transition: var(--transition);
    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05);
  }

  .token:hover {
    transform: translateY(-1px);
    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.08);
  }

  .stats-grid {
    display: grid;
    grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
    gap: 1.5rem;
    margin-bottom: 2rem;
  }

  .stat-card {
    background-color: var(--card-bg);
    padding: 1.5rem;
    border-radius: 1rem;
    box-shadow: var(--card-shadow);
    transition: var(--transition);
  }

  .stat-card:hover {
    transform: translateY(-2px);
    box-shadow: 0 6px 12px -2px rgba(0, 0, 0, 0.1);
  }

  .stat-title {
    color: var(--secondary-text);
    font-size: 0.875rem;
    font-weight: 500;
    margin-bottom: 0.5rem;
    text-transform: uppercase;
    letter-spacing: 0.05em;
  }

  .stat-value {
    color: var(--text-color);
    font-size: 2rem;
    font-weight: 700;
    line-height: 1.2;
    margin-bottom: 0.25rem;
  }

  .stat-description {
    color: var(--secondary-text);
    font-size: 0.875rem;
  }

  .expand-button {
    background: none;
    border: none;
    color: var(--primary-color);
    font-size: 0.875rem;
    padding: 0.5rem;
    cursor: pointer;
    display: block;
    margin: 0 auto;
    box-shadow: none;
  }

  .expand-button:hover {
    text-decoration: underline;
    transform: none;
    box-shadow: none;
  }

  .error-message {
    color: #EF4444;
    background-color: #fee2e2;
    border: 1px solid #fecaca;
    padding: 1rem;
    border-radius: 0.5rem;
    margin-bottom: 1rem;
    display: none;
  }

  .display-limit-notice {
    background-color: #fff9db;
    border: 1px solid #fef3c7;
    color: #b45309;
    padding: 0.75rem;
    border-radius: 0.5rem;
    margin-top: 1rem;
    font-size: 0.875rem;
    display: none;
  }

  /* File drop zone styles */
  .file-drop-zone {
    position: fixed;
    top: 0;
    left: 0;
    width: 100%;
    height: 100%;
    background-color: rgba(56,139,253, 0.15);
    z-index: 1000;
    display: flex;
    justify-content: center;
    align-items: center;
    opacity: 0;
    pointer-events: none;
    transition: opacity 0.3s ease;
  }

  .file-drop-zone.active {
    opacity: 1;
    pointer-events: all;
  }

  .drop-indicator {
    background-color: var(--card-bg);
    border: 2px dashed var(--primary-color);
    border-radius: 1rem;
    padding: 2rem;
    text-align: center;
    width: 60%;
    max-width: 400px;
    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.15);
    animation: pulse 2s infinite;
  }

  @keyframes pulse {
    0% { transform: scale(1); }
    50% { transform: scale(1.05); }
    100% { transform: scale(1); }
  }

  .drop-indicator p {
    margin-bottom: 0.5rem;
    color: var(--text-color);
    font-size: 1.2rem;
  }

  .file-icon {
    font-size: 3rem;
    margin-bottom: 1rem;
    color: var(--primary-color);
  }

  .file-upload-icon {
    position: fixed;
    bottom: 20px;
    left: 20px;
    width: 45px;
    height: 45px;
    background-color: var(--card-bg);
    border-radius: 50%;
    display: flex;
    justify-content: center;
    align-items: center;
    cursor: pointer;
    z-index: 100;
    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.15);
    transition: transform 0.2s ease, box-shadow 0.2s ease;
  }

  .file-upload-icon:hover {
    transform: translateY(-2px);
    box-shadow: 0 4px 15px rgba(0, 0, 0, 0.2);
  }

  .file-upload-icon span {
    font-size: 1.5rem;
    color: var(--primary-color);
  }

  .file-info {
    position: fixed;
    bottom: 20px;
    left: 75px;
    background-color: var(--card-bg);
    color: var(--primary-color);
    font-weight: 500;
    padding: 0.5rem 1rem;
    border-radius: 1rem;
    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.15);
    max-width: 270px;
    white-space: nowrap;
    overflow: hidden;
    text-overflow: ellipsis;
    z-index: 100;
    display: none;
  }
  
  .file-detach {
    margin-left: 8px;
    display: inline-block;
    width: 18px;
    height: 18px;
    background-color: rgba(0, 0, 0, 0.05);
    color: #ef4444;
    border-radius: 50%;
    text-align: center;
    line-height: 16px;
    font-size: 12px;
    cursor: pointer;
    transition: all 0.2s ease;
  }
  
  .file-detach:hover {
    background-color: rgba(239, 68, 68, 0.15);
    transform: scale(1.1);
  }

  .preview-notice {
    background-color: #e1f0ff;
    border: 1px solid #bfdbfe;
    color: #2563eb;
    padding: 0.75rem;
    border-radius: 0.5rem;
    margin-top: 1rem;
    font-size: 0.875rem;
    display: none;
  }
  
  .custom-model-wrapper {
    position: relative;
  }
  
  .model-badge {
    position: absolute;
    top: -10px;
    right: -5px;
    background: linear-gradient(135deg, #22c55e 0%, #15803d 100%);
    color: white;
    font-size: 0.7rem;
    font-weight: 700;
    padding: 0.25rem 0.5rem;
    border-radius: 999px;
    transform: scale(0);
    transition: transform 0.3s cubic-bezier(0.175, 0.885, 0.32, 1.275);
    box-shadow: 0 2px 5px rgba(0, 0, 0, 0.2);
    z-index: 10;
  }
  
  .model-badge.show {
    transform: scale(1);
  }
  
  .custom-model-help {
    display: inline-block;
    width: 16px;
    height: 16px;
    line-height: 16px;
    font-size: 11px;
    font-weight: bold;
    text-align: center;
    background-color: var(--secondary-text);
    color: var(--card-bg);
    border-radius: 50%;
    margin-left: 5px;
    cursor: help;
    vertical-align: middle;
  }
  
  .tooltip {
    position: absolute;
    top: 100%;
    left: 0;
    width: 280px;
    background-color: #333;
    color: #fff;
    padding: 0.75rem;
    border-radius: 0.5rem;
    font-size: 0.8rem;
    margin-top: 0.5rem;
    z-index: 100;
    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
    opacity: 0;
    visibility: hidden;
    transition: opacity 0.2s, visibility 0.2s;
  }
  
  .custom-model-help:hover + .tooltip {
    opacity: 1;
    visibility: visible;
  }

  /* Tokenizer info icon and tooltip styles */
  .tokenizer-info-icon {
    display: inline-flex;
    align-items: center;
    justify-content: center;
    width: 24px;
    height: 24px;
    background: linear-gradient(135deg, var(--primary-color) 0%, var(--primary-hover) 100%);
    color: white;
    border-radius: 50%;
    position: absolute;
    left: -32px; 
    top: 50%;
    transform: translateY(-50%);
    cursor: pointer;
    font-size: 12px;
    font-weight: bold;
    transition: all 0.2s ease;
    z-index: 10;
    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
  }
  
  .tokenizer-info-icon:hover {
    transform: translateY(-50%) scale(1.1);
    box-shadow: 0 3px 8px rgba(0, 0, 0, 0.3);
  }
  
  .tokenizer-info-tooltip {
    position: absolute;
    top: calc(100% + 8px);
    left: -30px; 
    width: 300px;
    background-color: var(--card-bg);
    color: var(--text-color);
    border: 1px solid var(--primary-color);
    border-radius: 0.75rem;
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.15);
    padding: 1rem;
    z-index: 1000; 
    opacity: 0;
    visibility: hidden;
    transition: opacity 0.3s, visibility 0.3s;
    pointer-events: none; 
  }
  
  .tokenizer-info-icon:not(.tooltip-disabled):hover + .tokenizer-info-tooltip {
    opacity: 1;
    visibility: visible;
    pointer-events: auto; 
  }
  
  .tokenizer-info-tooltip:hover {
    opacity: 1;
    visibility: visible;
    pointer-events: auto;
  }
  
  .tokenizer-info-header {
    font-size: 1.1rem;
    font-weight: 600;
    margin-bottom: 0.5rem;
    padding-bottom: 0.5rem;
    border-bottom: 1px solid rgba(0, 0, 0, 0.1);
    color: var(--primary-color);
  }
  
  .tokenizer-info-grid {
    display: grid;
    grid-template-columns: repeat(2, 1fr);
    gap: 0.75rem;
    margin: 0.75rem 0;
  }
  
  .tokenizer-info-item {
    display: flex;
    flex-direction: column;
  }
  
  .tokenizer-info-label {
    font-size: 0.75rem;
    color: var(--secondary-text);
    margin-bottom: 0.25rem;
  }
  
  .tokenizer-info-value {
    font-size: 0.95rem;
    font-weight: 500;
  }
  
  .special-tokens-container {
    margin-top: 0.75rem;
    background-color: rgba(56,139,253, 0.06);
    border-radius: 0.5rem;
    padding: 0.5rem;
    max-height: 100px;
    overflow-y: auto;
  }
  
  .special-token-item {
    display: flex;
    justify-content: space-between;
    margin-bottom: 0.25rem;
    font-size: 0.8rem;
  }
  
  .token-name {
    color: var(--secondary-text);
  }
  
  .token-value {
    background-color: rgba(255, 255, 255, 0.4);
    padding: 1px 4px;
    border-radius: 2px;
    font-family: monospace;
  }
  
  .tokenizer-info-loading {
    display: flex;
    justify-content: center;
    align-items: center;
    height: 100px;
  }
  
  .tokenizer-info-spinner {
    width: 30px;
    height: 30px;
    border: 3px solid var(--primary-color);
    border-radius: 50%;
    border-top-color: transparent;
    animation: spin 1s linear infinite;
  }
  
  .tokenizer-info-error {
    color: #f87171;
    font-size: 0.9rem;
    text-align: center;
    padding: 1rem;
  }

  @media (max-width: 768px) {
    .header {
      flex-direction: column;
      align-items: flex-start;
      gap: 1rem;
    }
    
    .model-selector {
      width: 100%;
    }
    
    .stats-grid {
      grid-template-columns: 1fr;
    }
    
    .tokenizer-info-tooltip {
      width: 250px;
    }
  }
</style>
</head>
<body>
    <!-- Hidden File Drop Zone that appears when dragging files -->
    <div id="fileDropZone" class="file-drop-zone">
        <div class="drop-indicator">
            <div class="file-icon">📄</div>
            <p>Drop your file here</p>
        </div>
    </div>

    <!-- File upload icon in bottom left corner -->
    <div id="fileUploadIcon" class="file-upload-icon">
        <span>📎</span>
    </div>
    <p class="file-info" id="fileInfo"></p>

    <div class="container">
        <div class="header">
            <div class="title-section">
                <h1 class="title">Multilingual Token Visualizer</h1>
            </div>
            <div class="model-selector">
                <div class="model-selector-header">
                    <div class="model-type-toggle">
                        <div class="toggle-option predefined-toggle active" data-type="predefined">Predefined</div>
                        <div class="toggle-option custom-toggle" data-type="custom">Custom</div>
                    </div>
                </div>
                <div id="predefinedModelSelector">
                    <div style="position: relative;">
                        <div class="tokenizer-info-icon" id="modelInfoIcon" title="View tokenizer information">ℹ</div>
                        <!-- TOOLTIP MOVED HERE -->
                        <div class="tokenizer-info-tooltip" id="modelInfoTooltip">
                            <div id="tokenizerInfoContent">
                                <div class="tokenizer-info-loading">
                                    <div class="tokenizer-info-spinner"></div>
                                </div>
                            </div>
                        </div>
                        <!-- SELECT NOW COMES AFTER ICON AND TOOLTIP -->
                        <select id="modelSelect" name="model">
                            {% for model_id, info in models.items() %}
                            <option value="{{ model_id }}" {% if selected_model == model_id %}selected{% endif %}>
                                {{ info.alias }}
                            </option>
                            {% endfor %}
                        </select>
                    </div>
                </div>
                <div id="customModelSelector" style="display: none;" class="custom-model-wrapper">
                    <div style="position: relative;">
                        <div class="tokenizer-info-icon" id="customModelInfoIcon" title="View tokenizer information">ℹ</div>
                        <div class="tokenizer-info-tooltip" id="customModelInfoTooltip">
                            <div id="customTokenizerInfoContent">
                                <div class="tokenizer-info-loading">
                                    <div class="tokenizer-info-spinner"></div>
                                </div>
                            </div>
                        </div>
                        <input type="text" id="customModelInput" class="custom-model-input" 
                               placeholder="Enter HuggingFace model path" 
                               value="{{ custom_model if custom_model and custom_model|length > 0 else '' }}">
                    </div>
                    <span class="custom-model-help">?</span>
                    <div class="tooltip">
                        Enter a valid HuggingFace model ID (e.g., "mistralai/Mistral-7B-Instruct-v0.3").
                        For Korean, you might use "beomi/KoAlpaca-Polyglot-12.8B" or "skt/kogpt2-base-v2", etc.
                        The model must have a tokenizer available and be accessible.
                    </div>
                    <div class="model-badge" id="modelSuccessBadge">Loaded</div>
                </div>
            </div>
        </div>

        <div class="error-message" id="errorMessage">{{ error }}</div>

        <div class="input-section">
            <form id="analyzeForm" method="POST" enctype="multipart/form-data">
                <textarea name="text" id="textInput" placeholder="Enter text to analyze or upload a file in bottom left corner...">{{ text }}</textarea>
                <input type="hidden" name="model" id="modelInput" value="{{ selected_model }}">
                <input type="hidden" name="custom_model" id="customModelInputHidden" value="{{ custom_model if custom_model else '' }}">
                <input type="hidden" name="model_type" id="modelTypeInput" value="{{ model_type if model_type else 'predefined' }}">
                <input type="file" name="file" id="fileInput" style="display: none;">
                <div class="button-container">
                    <button type="submit" id="analyzeButton">Analyze Text</button>
                </div>
            </form>
        </div>

        <div id="results" class="results" {% if not token_data %}style="display: none;"{% endif %}>
            <div class="card">
                <h2 class="card-title">Token Visualization</h2>
                <div class="preview-notice" id="previewNotice">
                    Note: Showing preview of first 8096 characters. Stats are calculated on the full file.
                </div>
                <div class="token-container" id="tokenContainer">
                    {% if token_data %}
                    {% for token in token_data.tokens %}
                    <span class="token" 
                          style="background-color: {{ token.colors.background }}; color: {{ token.colors.text }};"
                          title="Original token: {{ token.original }} | Token ID: {{ token.token_id }}">
                        {{ token.display }}
                    </span>
                    {% if token.newline %}<br>{% endif %}
                    {% endfor %}
                    {% endif %}
                </div>
                <button class="expand-button" id="expandButton">Show More</button>
                <div class="display-limit-notice" id="displayLimitNotice">
                    Note: Only showing first 50,000 tokens. Total token count: <span id="totalTokenCount">0</span>
                </div>
            </div>

            <div class="stats-grid">
                <div class="stat-card">
                    <div class="stat-title">Total Tokens</div>
                    <div class="stat-value" id="totalTokens">{{ token_data.stats.basic_stats.total_tokens if token_data else 0 }}</div>
                    <div class="stat-description">
                        <span id="uniqueTokens">{{ token_data.stats.basic_stats.unique_tokens if token_data else 0 }} unique</span>
                        (<span id="uniquePercentage">{{ token_data.stats.basic_stats.unique_percentage if token_data else 0 }}</span>%)
                    </div>
                </div>
                <div class="stat-card">
                    <div class="stat-title">Token Types</div>
                    <div class="stat-value" id="specialTokens">{{ token_data.stats.basic_stats.special_tokens if token_data else 0 }}</div>
                    <div class="stat-description">special tokens</div>
                </div>
                <div class="stat-card">
                    <div class="stat-title">Whitespace</div>
                    <div class="stat-value" id="spaceTokens">{{ token_data.stats.basic_stats.space_tokens if token_data else 0 }}</div>
                    <div class="stat-description">
                        spaces: <span id="spaceCount">{{ token_data.stats.basic_stats.space_tokens if token_data else 0 }}</span>,
                        newlines: <span id="newlineCount">{{ token_data.stats.basic_stats.newline_tokens if token_data else 0 }}</span>
                    </div>
                </div>
                <div class="stat-card">
                    <div class="stat-title">Token Length</div>
                    <div class="stat-value" id="avgLength">{{ token_data.stats.length_stats.avg_length if token_data else 0 }}</div>
                    <div class="stat-description">
                        median: <span id="medianLength">{{ token_data.stats.length_stats.median_length if token_data else 0 }}</span>,
                        ±<span id="stdDev">{{ token_data.stats.length_stats.std_dev if token_data else 0 }}</span> std
                    </div>
                </div>
                <div class="stat-card">
                    <div class="stat-title">Compression</div>
                    <div class="stat-value" id="compressionRatio">{{ token_data.stats.basic_stats.compression_ratio if token_data else 0 }}</div>
                    <div class="stat-description">characters per token</div>
                </div>
            </div>
        </div>
    </div>
    <a href="https://huggingface.co/spaces/barttee/tokenizers" target="_blank" class="watermark" style="position: fixed; bottom: 20px; right: 20px; text-decoration: none; font-size: 1.4rem; font-weight: 700; color: var(--primary-color); opacity: 0.4;">
        @barttee/tokenizers
    </a>

    <script>
        $(document).ready(function() {
            // File handling variables
            let currentFile = null;
            let originalTextContent = null;
            let lastUploadedFileName = null;
            let fileJustUploaded = false;  // Flag to prevent immediate detachment
            let currentModelType = "{{ model_type if model_type else 'predefined' }}";
            let currentTokenizerInfo = null;
            
            // Try to parse tokenizer info if available from server
            try {
                currentTokenizerInfo = {{ token_data.tokenizer_info|tojson if token_data and token_data.tokenizer_info else 'null' }};
                if (currentTokenizerInfo) {
                    updateTokenizerInfoDisplay(currentTokenizerInfo, currentModelType === 'custom');
                }
            } catch(e) {
                console.error("Error parsing tokenizer info:", e);
            }
            
            // Show error if exists
            if ("{{ error }}".length > 0) {
                showError("{{ error }}");
            }
            
            // Setup model type based on initial state
            if (currentModelType === "custom") {
                $('.toggle-option').removeClass('active');
                $('.custom-toggle').addClass('active');
                $('#predefinedModelSelector').hide();
                $('#customModelSelector').show();
            }
            
            // Show success badge if custom model loaded successfully
            if (currentModelType === "custom" && !("{{ error }}".length > 0)) {
                $('#modelSuccessBadge').addClass('show');
                setTimeout(() => {
                    $('#modelSuccessBadge').removeClass('show');
                }, 3000);
            }

            // Toggle between predefined and custom model inputs
            $('.toggle-option').click(function() {
                const modelType = $(this).data('type');
                $('.toggle-option').removeClass('active');
                $(this).addClass('active');
                currentModelType = modelType;
                
                if (modelType === 'predefined') {
                    $('#predefinedModelSelector').show();
                    $('#customModelSelector').hide();
                    $('#modelTypeInput').val('predefined');
                    // Set the model input value to the selected predefined model
                    $('#modelInput').val($('#modelSelect').val());
                } else {
                    $('#predefinedModelSelector').hide();
                    $('#customModelSelector').show();
                    $('#modelTypeInput').val('custom');
                }
                
                // Clear tokenizer info if switching models
                if (modelType === 'predefined') {
                    $('#tokenizerInfoContent').html('<div class="tokenizer-info-loading"><div class="tokenizer-info-spinner"></div></div>');
                    fetchTokenizerInfo($('#modelSelect').val(), false);
                } else {
                    $('#customTokenizerInfoContent').html('<div class="tokenizer-info-loading"><div class="tokenizer-info-spinner"></div></div>');
                    const customModel = $('#customModelInput').val();
                    if (customModel) {
                        fetchTokenizerInfo(customModel, true);
                    }
                }
            });
            
            // Update hidden input when custom model input changes
            $('#customModelInput').on('input', function() {
                $('#customModelInputHidden').val($(this).val());
            });

            function showError(message) {
                const errorDiv = $('#errorMessage');
                errorDiv.text(message);
                errorDiv.show();
                setTimeout(() => errorDiv.fadeOut(), 5000);
            }
            
            // Function to update tokenizer info display in tooltip
            function updateTokenizerInfoDisplay(info, isCustom = false) {
                const targetSelector = isCustom ? '#customTokenizerInfoContent' : '#tokenizerInfoContent';
                let htmlContent = '';
                
                if (info.error) {
                    $(targetSelector).html(`<div class="tokenizer-info-error">${info.error}</div>`);
                    return;
                }
                
                // Start building the tooltip content
                htmlContent = `<div class="tokenizer-info-header">Tokenizer Details</div>
                              <div class="tokenizer-info-grid">`;
                
                if (info.vocab_size) {
                    htmlContent += `
                        <div class="tokenizer-info-item">
                            <span class="tokenizer-info-label">Dictionary Size</span>
                            <span class="tokenizer-info-value">${info.vocab_size.toLocaleString()}</span>
                        </div>`;
                }
                
                if (info.tokenizer_type) {
                    htmlContent += `
                        <div class="tokenizer-info-item">
                            <span class="tokenizer-info-label">Tokenizer Type</span>
                            <span class="tokenizer-info-value">${info.tokenizer_type}</span>
                        </div>`;
                }
                
                if (info.model_max_length) {
                    htmlContent += `
                        <div class="tokenizer-info-item">
                            <span class="tokenizer-info-label">Max Length</span>
                            <span class="tokenizer-info-value">${info.model_max_length.toLocaleString()}</span>
                        </div>`;
                }
                
                htmlContent += `</div>`;
                
                // Special tokens section
                if (info.special_tokens && Object.keys(info.special_tokens).length > 0) {
                    htmlContent += `
                        <div class="tokenizer-info-item" style="margin-top: 0.75rem;">
                            <span class="tokenizer-info-label">Special Tokens</span>
                            <div class="special-tokens-container">`;
                    
                    for (const [tokenName, tokenValue] of Object.entries(info.special_tokens)) {
                        const escapedValue = tokenValue
                            .replace(/&/g, '&amp;')
                            .replace(/</g, '&lt;')
                            .replace(/>/g, '&gt;')
                            .replace(/"/g, '&quot;')
                            .replace(/'/g, '&#039;');
                            
                        htmlContent += `
                            <div class="special-token-item">
                                <span class="token-name">${tokenName}:</span>
                                <span class="token-value">${escapedValue}</span>
                            </div>`;
                    }
                    
                    htmlContent += `
                            </div>
                        </div>`;
                }
                
                $(targetSelector).html(htmlContent);
            }
            
            // Function to fetch tokenizer info
            function fetchTokenizerInfo(modelId, isCustom = false) {
                if (!modelId) return;
                
                const targetSelector = isCustom ? '#customTokenizerInfoContent' : '#tokenizerInfoContent';
                $(targetSelector).html('<div class="tokenizer-info-loading"><div class="tokenizer-info-spinner"></div></div>');
                
                $.ajax({
                    url: '/tokenizer-info',
                    method: 'GET',
                    data: {
                        model_id: modelId,
                        is_custom: isCustom
                    },
                    success: function(response) {
                        if (response.error) {
                            $(targetSelector).html(`<div class="tokenizer-info-error">${response.error}</div>`);
                        } else {
                            currentTokenizerInfo = response;
                            updateTokenizerInfoDisplay(response, isCustom);
                        }
                    },
                    error: function(xhr) {
                        $(targetSelector).html('<div class="tokenizer-info-error">Failed to load tokenizer information</div>');
                    }
                });
            }

            function updateResults(data) {
                $('#results').show();
                
                const tokenContainer = $('#tokenContainer');
                tokenContainer.empty();
                data.tokens.forEach(token => {
                    const span = $('<span>')
                        .addClass('token')
                        .css({
                            'background-color': token.colors.background,
                            'color': token.colors.text
                        })
                        .attr('title', `Original token: ${token.original} | Token ID: ${token.token_id}`)
                        .text(token.display);
                    
                    tokenContainer.append(span);
                    if (token.newline) {
                        tokenContainer.append('<br>');
                    }
                });

                if (data.display_limit_reached) {
                    $('#displayLimitNotice').show();
                    $('#totalTokenCount').text(data.total_tokens);
                } else {
                    $('#displayLimitNotice').hide();
                }

                if (data.preview_only) {
                    $('#previewNotice').show();
                } else {
                    $('#previewNotice').hide();
                }

                $('#totalTokens').text(data.stats.basic_stats.total_tokens);
                $('#uniqueTokens').text(`${data.stats.basic_stats.unique_tokens} unique`);
                $('#uniquePercentage').text(data.stats.basic_stats.unique_percentage);
                $('#specialTokens').text(data.stats.basic_stats.special_tokens);
                $('#spaceTokens').text(data.stats.basic_stats.space_tokens);
                $('#spaceCount').text(data.stats.basic_stats.space_tokens);
                $('#newlineCount').text(data.stats.basic_stats.newline_tokens);
                $('#compressionRatio').text(data.stats.basic_stats.compression_ratio);

                $('#avgLength').text(data.stats.length_stats.avg_length);
                $('#medianLength').text(data.stats.length_stats.median_length);
                $('#stdDev').text(data.stats.length_stats.std_dev);
                
                if (data.tokenizer_info) {
                    currentTokenizerInfo = data.tokenizer_info;
                    updateTokenizerInfoDisplay(data.tokenizer_info, currentModelType === 'custom');
                }
            }

            $('#textInput').on('input', function() {
                if (fileJustUploaded) {
                    fileJustUploaded = false;
                    return;
                }
                
                const currentText = $(this).val();
                const fileInput = document.getElementById('fileInput');
                
                if (fileInput.files.length > 0 && originalTextContent !== null) {
                    const isMajorChange = 
                        currentText.length < originalTextContent.length * 0.8 ||
                        (currentText.length > 0 && 
                         currentText !== originalTextContent.substring(0, currentText.length) && 
                         currentText.substring(0, Math.min(20, currentText.length)) !== 
                         originalTextContent.substring(0, Math.min(20, originalTextContent.length)));
                    
                    if (isMajorChange) {
                        detachFile();
                    }
                }
            });
            
            function detachFile() {
                $('#fileInput').val('');
                $('#fileInfo').fadeOut(300);
                originalTextContent = $('#textInput').val();
                lastUploadedFileName = null;
            }
            
            $('#modelSelect').change(function() {
                const selectedModel = $(this).val();
                $('#modelInput').val(selectedModel);
                fetchTokenizerInfo(selectedModel, false);
                
                if ($('#textInput').val().trim()) {
                    $('#analyzeForm').submit();
                }
            });

            const fileDropZone = $('#fileDropZone');
            const fileUploadIcon = $('#fileUploadIcon');
            
            ['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
                fileDropZone[0].addEventListener(eventName, preventDefaults, false);
                document.body.addEventListener(eventName, preventDefaults, false);
            });
            
            function preventDefaults(e) {
                e.preventDefault();
                e.stopPropagation();
            }

            document.addEventListener('dragenter', showDropZone, false);
            document.addEventListener('dragover', showDropZone, false);
            
            fileDropZone[0].addEventListener('dragleave', hideDropZone, false);
            fileDropZone[0].addEventListener('drop', hideDropZone, false);
            
            function showDropZone(e) {
                fileDropZone.addClass('active');
            }
            
            function hideDropZone() {
                fileDropZone.removeClass('active');
            }

            fileDropZone[0].addEventListener('drop', handleDrop, false);
            
            fileUploadIcon.on('click', function() {
                const input = document.createElement('input');
                input.type = 'file';
                input.onchange = e => {
                    handleFiles(e.target.files);
                };
                input.click();
            });
            
            function handleDrop(e) {
                const dt = e.dataTransfer;
                const files = dt.files;
                handleFiles(files);
            }
            
            function handleFiles(files) {
                if (files.length) {
                    const file = files[0];
                    currentFile = file;
                    lastUploadedFileName = file.name;
                    fileJustUploaded = true;
                    
                    $('#fileInfo').html(`${file.name} (${formatFileSize(file.size)}) <span class="file-detach" id="fileDetach"><i class="fas fa-times"></i></span>`).fadeIn(300);
                    
                    $('#fileDetach').on('click', function(e) {
                        e.stopPropagation();
                        detachFile();
                        return false;
                    });
                    
                    const dataTransfer = new DataTransfer();
                    dataTransfer.items.add(file);
                    document.getElementById('fileInput').files = dataTransfer.files;
                    
                    const reader = new FileReader();
                    reader.onload = function(e) {
                        const previewText = e.target.result.slice(0, 8096);
                        $('#textInput').val(previewText);
                        
                        setTimeout(() => {
                            originalTextContent = previewText;
                            $('#analyzeForm').submit();
                        }, 50);
                    };
                    reader.readAsText(file, 'utf-8');
                }
            }
            
            function formatFileSize(bytes) {
                if (bytes < 1024) return bytes + ' bytes';
                else if (bytes < 1048576) return (bytes / 1024).toFixed(1) + ' KB';
                else return (bytes / 1048576).toFixed(1) + ' MB';
            }

            $('#analyzeForm').on('submit', function(e) {
                e.preventDefault();
                
                if (!fileJustUploaded) {
                    const textInput = $('#textInput').val();
                    const fileInput = document.getElementById('fileInput');
                    
                    if (fileInput.files.length > 0 && 
                        originalTextContent !== null && 
                        textInput !== originalTextContent && 
                        textInput.length < originalTextContent.length * 0.8) {
                        detachFile();
                    }
                } else {
                    fileJustUploaded = false;
                }
                
                if (currentModelType === 'custom') {
                    $('#customModelInputHidden').val($('#customModelInput').val());
                } else {
                    $('#modelInput').val($('#modelSelect').val());
                }
                
                const formData = new FormData(this);
                $('#analyzeButton').prop('disabled', true);
                
                $.ajax({
                    url: '/',
                    method: 'POST',
                    data: formData,
                    processData: false,
                    contentType: false,
                    success: function(response) {
                        if (response.error) {
                            showError(response.error);
                        } else {
                            updateResults(response);
                            
                            if (currentModelType === 'custom') {
                                $('#modelSuccessBadge').addClass('show');
                                setTimeout(() => {
                                    $('#modelSuccessBadge').removeClass('show');
                                }, 3000);
                            }
                        }
                    },
                    error: function(xhr) {
                        showError(xhr.responseText || 'An error occurred while processing the text');
                    },
                    complete: function() {
                        $('#analyzeButton').prop('disabled', false);
                    }
                });
            });

            $('#expandButton').click(function() {
                const container = $('#tokenContainer');
                const isExpanded = container.hasClass('expanded');
                
                container.toggleClass('expanded');
                $(this).text(isExpanded ? 'Show More' : 'Show Less');
            });
            
            if (currentModelType === 'predefined') {
                fetchTokenizerInfo($('#modelSelect').val(), false);
            } else if ($('#customModelInput').val()) {
                fetchTokenizerInfo($('#customModelInput').val(), true);
            }
            
            $('#customModelInput').on('change', function() {
                const modelValue = $(this).val();
                if (modelValue) {
                    fetchTokenizerInfo(modelValue, true);
                }
            });
        });
    </script>
</body>
</html>
"""

@app.route('/tokenizer-info', methods=['GET'])
def tokenizer_info():
    """
    Endpoint to get tokenizer information without processing text.
    """
    model_id = request.args.get('model_id', '')
    is_custom = request.args.get('is_custom', 'false').lower() == 'true'
    
    if not model_id:
        return jsonify({"error": "No model ID provided"}), 400
    
    try:
        if not is_custom and model_id in TOKENIZER_MODELS:
            model_id_or_name = model_id
        else:
            model_id_or_name = model_id
            
        tokenizer, info, error = load_tokenizer(model_id_or_name)
        
        if error:
            return jsonify({"error": error}), 400
            
        return jsonify(info)
    except Exception as e:
        return jsonify({"error": f"Failed to get tokenizer info: {str(e)}"}), 500

@app.route('/', methods=['GET', 'POST'])
def index():
    text = ""
    token_data = None
    error_message = ""
    selected_model = request.args.get('model', request.form.get('model', 'Qwen3'))
    custom_model = request.args.get('custom_model', request.form.get('custom_model', ''))
    model_type = request.args.get('model_type', request.form.get('model_type', 'predefined'))
    
    model_to_use = selected_model if model_type == 'predefined' else custom_model
    
    if request.method == 'POST':
        if 'file' in request.files and request.files['file'].filename:
            uploaded_file = request.files['file']
            file_path = os.path.join(app.config['UPLOAD_FOLDER'], uploaded_file.filename)
            uploaded_file.save(file_path)
            
            with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
                text = f.read(8096)
            
            try:
                token_data = process_text("", model_to_use, is_full_file=True, file_path=file_path)
                if os.path.exists(file_path):
                    os.remove(file_path)
                
                if request.headers.get('X-Requested-With') == 'XMLHttpRequest':
                    return jsonify(token_data)
                    
            except Exception as e:
                error_message = str(e)
                if os.path.exists(file_path):
                    os.remove(file_path)
                
                if request.headers.get('X-Requested-With') == 'XMLHttpRequest':
                    return jsonify({"error": error_message}), 400
                return render_template_string(
                    HTML_TEMPLATE,
                    text=text,
                    token_data=None,
                    models=TOKENIZER_MODELS,
                    selected_model=selected_model,
                    custom_model=custom_model,
                    model_type=model_type,
                    error=error_message
                )
        else:
            text = request.form.get('text', '')
            if text:
                try:
                    token_data = process_text(text, model_to_use)
                    if request.headers.get('X-Requested-With') == 'XMLHttpRequest':
                        return jsonify(token_data)
                except Exception as e:
                    error_message = str(e)
                    if request.headers.get('X-Requested-With') == 'XMLHttpRequest':
                        return jsonify({"error": error_message}), 400
                    return render_template_string(
                        HTML_TEMPLATE,
                        text=text,
                        token_data=None,
                        models=TOKENIZER_MODELS,
                        selected_model=selected_model,
                        custom_model=custom_model,
                        model_type=model_type,
                        error=error_message
                    )
    
    return render_template_string(
        HTML_TEMPLATE,
        text=text,
        token_data=token_data,
        models=TOKENIZER_MODELS,
        selected_model=selected_model,
        custom_model=custom_model,
        model_type=model_type,
        error=error_message
    )

if __name__ == "__main__":
    app.run(host='0.0.0.0', port=7860, debug=False)