nb-scraper/dist/index.mjs.map

Community scraper library by Newbie Scrape

{"version":3,"sources":["../app/utils.ts","../app/scrapers/blackbox.ts","../app/scrapers/threads.ts","../app/scrapers/pinterest.ts","../app/scrapers/exomlapi.ts","../app/scrapers/dreamanalysis.ts","../app/scrapers/pollinations.ts","../app/scrapers/soundcloud.ts","../app/scrapers/deepinfra.ts","../app/scrapers/animeindo.ts","../app/scrapers/facebook.ts","../app/scrapers/anydownloader.ts","../app/scrapers/youtube.ts","../app/scrapers/liputan6.ts","../app/scrapers/laratranslate.ts","../app/scrapers/savegram.ts","../app/scrapers/wheaterMaster.ts","../app/scrapers/youtube-post.ts","../app/scrapers/lyrics-generator.ts","../app/scrapers/apkpure.ts","../app/scrapers/writeCanvas.ts","../app/scrapers/bacakomik.ts","../app/scrapers/unaimytext.ts","../app/scrapers/ssyoutube.ts","../app/scrapers/ffstalk.ts","../app/scrapers/tiktok.ts","../app/scrapers/translate-image.ts","../app/scrapers/periksadata.ts","../app/scrapers/terabox.ts","../app/scrapers/tutwuri.ts","../app/scrapers/ytmp3mobi.ts","../app/scrapers/textcraft.ts","../app/scrapers/groupda.ts","../app/index.ts"],"sourcesContent":["/**\n * @fileoverview Utility functions for NB Scraper\n * @author Er Project\n * @version 1.0.0\n */\n\nimport axios, { AxiosError, AxiosRequestConfig, AxiosResponse } from 'axios';\nimport { NBScraperResponse, ScraperError, ScraperErrorType, RequestConfig } from './types';\n\n/**\n * Default configuration for the scraper\n */\nexport const DEFAULT_CONFIG = {\n  timeout: 30000,\n  retries: 3,\n  retryDelay: 1000,\n  userAgent: 'Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Mobile Safari/537.36'\n} as const;\n\n/**\n * Creator information\n */\nexport const CREATOR = 'nb-scraper';\n\n/**\n * Sleep function for delays\n * @param ms - Milliseconds to sleep\n * @returns Promise that resolves after the specified time\n */\nexport const sleep = (ms: number): Promise<void> => \n  new Promise(resolve => setTimeout(resolve, ms));\n\n/**\n * Validates if a string is a valid URL\n * @param url - The URL string to validate\n * @returns True if the URL is valid, false otherwise\n */\nexport function isValidUrl(url: string): boolean {\n  try {\n    new URL(url);\n    return true;\n  } catch {\n    return false;\n  }\n}\n\n/**\n * Sanitizes a string by removing potentially harmful characters\n * @param input - The input string to sanitize\n * @returns Sanitized string\n */\nexport function sanitizeString(input: string): string {\n  return input\n    .replace(/[<>'\"]/g, '') // Remove potential XSS characters\n    .trim()\n    .slice(0, 10000); // Limit length to prevent memory issues\n}\n\n/**\n * Creates a standardized error response\n * @param error - The error that occurred\n * @param context - Additional context about the error\n * @returns Standardized error response\n */\nexport function createErrorResponse(\n  error: ScraperError | Error | string,\n  context?: Record<string, unknown>\n): NBScraperResponse<never> {\n  let errorMessage: string;\n  let errorType: ScraperErrorType = ScraperErrorType.UNKNOWN_ERROR;\n\n  if (typeof error === 'string') {\n    errorMessage = error;\n  } else if (error instanceof Error) {\n    errorMessage = error.message;\n    \n    // Classify error type based on error properties\n    if (error.name === 'AxiosError' || error.message.includes('network')) {\n      errorType = ScraperErrorType.NETWORK_ERROR;\n    } else if (error.message.includes('timeout')) {\n      errorType = ScraperErrorType.NETWORK_ERROR;\n    } else if (error.message.includes('rate') || error.message.includes('limit')) {\n      errorType = ScraperErrorType.RATE_LIMITED;\n    }\n  } else {\n    errorMessage = error.message;\n    errorType = error.type;\n  }\n\n  return {\n    creator: CREATOR,\n    status: false,\n    error: `[${errorType}] ${errorMessage}${context ? ` | Context: ${JSON.stringify(context)}` : ''}`\n  };\n}\n\n/**\n * Creates a standardized success response\n * @param data - The data to include in the response\n * @returns Standardized success response\n */\nexport function createSuccessResponse<T>(data: T): NBScraperResponse<T> {\n  return {\n    creator: CREATOR,\n    status: true,\n    data\n  };\n}\n\n/**\n * Makes an HTTP request with retry logic and error handling\n * @param config - Axios request configuration\n * @param options - Additional options for the request\n * @returns Promise that resolves to the response data\n */\nexport async function makeRequest<T = unknown>(\n  config: AxiosRequestConfig,\n  options: RequestConfig = {}\n): Promise<AxiosResponse<T>> {\n  const {\n    timeout = DEFAULT_CONFIG.timeout,\n    retries = DEFAULT_CONFIG.retries,\n    retryDelay = DEFAULT_CONFIG.retryDelay,\n    headers = {}\n  } = options;\n\n  const requestConfig: AxiosRequestConfig = {\n    ...config,\n    timeout,\n    headers: {\n      'User-Agent': DEFAULT_CONFIG.userAgent,\n      'Accept': '*/*',\n      'Accept-Encoding': 'gzip, deflate, br',\n      'Accept-Language': 'id-ID,id;q=0.9,en;q=0.8',\n      ...headers,\n      ...config.headers\n    }\n  };\n\n  let lastError: Error | undefined;\n\n  for (let attempt = 0; attempt <= retries; attempt++) {\n    try {\n      const response = await axios(requestConfig);\n      return response;\n    } catch (error) {\n      lastError = error as Error;\n      \n      // Don't retry on certain error types\n      if (axios.isAxiosError(error)) {\n        const axiosError = error as AxiosError;\n        \n        // Don't retry on 4xx errors (except 429 - Too Many Requests)\n        if (axiosError.response?.status && \n            axiosError.response.status >= 400 && \n            axiosError.response.status < 500 && \n            axiosError.response.status !== 429) {\n          throw error;\n        }\n      }\n\n      // If this is the last attempt, throw the error\n      if (attempt === retries) {\n        throw lastError;\n      }\n\n      // Wait before retrying\n      await sleep(retryDelay * (attempt + 1)); // Exponential backoff\n    }\n  }\n\n  throw lastError;\n}\n\n/**\n * Validates required parameters for scraper functions\n * @param params - Object containing parameters to validate\n * @param required - Array of required parameter names\n * @throws Error if any required parameter is missing or invalid\n */\nexport function validateRequiredParams(\n  params: Record<string, unknown>,\n  required: string[]\n): void {\n  for (const param of required) {\n    const value = params[param];\n    \n    if (value === undefined || value === null || value === '') {\n      throw new Error(`Parameter '${param}' is required and cannot be empty`);\n    }\n    \n    if (typeof value === 'string' && value.trim() === '') {\n      throw new Error(`Parameter '${param}' cannot be an empty string`);\n    }\n  }\n}\n\n/**\n * Safely parses JSON string, returning null if parsing fails\n * @param jsonString - The JSON string to parse\n * @returns Parsed object or null if parsing failed\n */\nexport function safeJsonParse<T = unknown>(jsonString: string): T | null {\n  try {\n    return JSON.parse(jsonString) as T;\n  } catch {\n    return null;\n  }\n}\n\n/**\n * Extracts domain from URL\n * @param url - The URL to extract domain from\n * @returns Domain string or null if invalid URL\n */\nexport function extractDomain(url: string): string | null {\n  try {\n    const urlObj = new URL(url);\n    return urlObj.hostname;\n  } catch {\n    return null;\n  }\n}\n\n/**\n * Formats bytes to human readable format\n * @param bytes - Number of bytes\n * @param decimals - Number of decimal places\n * @returns Formatted string\n */\nexport function formatBytes(bytes: number, decimals = 2): string {\n  if (bytes === 0) return '0 Bytes';\n\n  const k = 1024;\n  const dm = decimals < 0 ? 0 : decimals;\n  const sizes = ['Bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB', 'ZB', 'YB'];\n\n  const i = Math.floor(Math.log(bytes) / Math.log(k));\n\n  return parseFloat((bytes / Math.pow(k, i)).toFixed(dm)) + ' ' + sizes[i];\n}","/**\n * @fileoverview BlackBox AI scraper implementation\n * @author From NB\n * @version 1.0.0\n */\n\nimport { \n  NBScraperResponse, \n  BlackBoxAIData, \n  BlackBoxAIOptions, \n  BlackBoxSource,\n} from '../types';\nimport { \n  createErrorResponse, \n  createSuccessResponse, \n  makeRequest, \n  validateRequiredParams,\n  safeJsonParse\n} from '../utils';\n\n/**\n * Default BlackBox AI configuration\n */\nconst DEFAULT_BLACKBOX_CONFIG = {\n  maxTokens: 1024,\n  temperature: null,\n  webSearchMode: false,\n  memoryEnabled: false\n} as const;\n\n/**\n * Scrapes BlackBox AI for responses to queries\n * \n * @example\n * ```typescript\n * import { blackboxAi } from 'nb-scraper';\n * \n * const result = await blackboxAi('What is TypeScript?');\n * if (result.status) {\n *   console.log(result.data.response);\n *   console.log(result.data.source);\n * }\n * ```\n * \n * @param query - The query to send to BlackBox AI\n * @param options - Optional configuration for the request\n * @returns Promise resolving to the AI response with sources\n * \n * @throws Will not throw errors, returns error response instead\n * \n * @author Pratama\n */\nexport async function blackboxAi(\n  query: string,\n  options: BlackBoxAIOptions = {}\n): Promise<NBScraperResponse<BlackBoxAIData>> {\n  try {\n    // Validate input parameters\n    validateRequiredParams({ query }, ['query']);\n\n    // Sanitize and validate query\n    const sanitizedQuery = query.trim();\n    if (sanitizedQuery.length === 0) {\n      return createErrorResponse('Query cannot be empty', { query });\n    }\n\n    if (sanitizedQuery.length > 10000) {\n      return createErrorResponse('Query too long (max 10,000 characters)', { \n        queryLength: sanitizedQuery.length \n      });\n    }\n\n    // Merge options with defaults\n    const config = { ...DEFAULT_BLACKBOX_CONFIG, ...options };\n\n    // Prepare request headers\n    const headers = {\n      'Accept': '*/*',\n      'Accept-Encoding': 'gzip, deflate, br',\n      'Accept-Language': 'id-ID,id;q=0.9',\n      'Content-Type': 'application/json',\n      'Origin': 'https://www.blackbox.ai',\n      'Referer': 'https://www.blackbox.ai/',\n      'Sec-Ch-Ua': '\"Chromium\";v=\"137\", \"Not/A)Brand\";v=\"24\"',\n      'Sec-Ch-Ua-Mobile': '?1',\n      'Sec-Ch-Ua-Platform': '\"Android\"',\n      'Sec-Fetch-Dest': 'empty',\n      'Sec-Fetch-Mode': 'cors',\n      'Sec-Fetch-Site': 'same-origin',\n      ...options.headers\n    };\n\n    // Prepare request payload\n    const payload = {\n      messages: [{ \n        role: 'user', \n        content: sanitizedQuery, \n        id: generateRandomId() \n      }],\n      id: generateRandomId(),\n      previewToken: null,\n      userId: null,\n      codeModelMode: true,\n      trendingAgentMode: {},\n      isMicMode: false,\n      userSystemPrompt: null,\n      maxTokens: config.maxTokens,\n      playgroundTopP: null,\n      playgroundTemperature: config.temperature,\n      isChromeExt: false,\n      githubToken: '',\n      clickedAnswer2: false,\n      clickedAnswer3: false,\n      clickedForceWebSearch: config.webSearchMode,\n      visitFromDelta: false,\n      isMemoryEnabled: config.memoryEnabled,\n      mobileClient: false,\n      userSelectedModel: null,\n      validated: generateUUID(),\n      imageGenerationMode: false,\n      webSearchModePrompt: config.webSearchMode,\n      deepSearchMode: false,\n      domains: null,\n      vscodeClient: false,\n      codeInterpreterMode: false,\n      customProfile: {\n        name: '',\n        occupation: '',\n        traits: [],\n        additionalInfo: '',\n        enableNewChats: false\n      },\n      webSearchModeOption: {\n        autoMode: true,\n        webMode: config.webSearchMode,\n        offlineMode: !config.webSearchMode\n      },\n      session: null,\n      isPremium: false,\n      subscriptionCache: null,\n      beastMode: false,\n      reasoningMode: false,\n      designerMode: false,\n      workspaceId: '',\n      asyncMode: false,\n      isTaskPersistent: false\n    };\n\n    // Make the request\n    const response = await makeRequest(\n      {\n        method: 'POST',\n        url: 'https://www.blackbox.ai/api/chat',\n        data: payload,\n        headers\n      },\n      {\n        timeout: options.timeout,\n        retries: options.retries,\n        retryDelay: options.retryDelay\n      }\n    );\n\n    // Validate response\n    if (!response.data || typeof response.data !== 'string') {\n      return createErrorResponse('Invalid response format from BlackBox AI', {\n        responseType: typeof response.data,\n        status: response.status\n      });\n    }\n\n    // Parse response\n    const rawResponse = response.data;\n    const parsedData = parseBlackBoxResponse(rawResponse);\n\n    if (!parsedData) {\n      return createErrorResponse('Failed to parse BlackBox AI response', {\n        rawResponse: rawResponse.substring(0, 100) + '...'\n      });\n    }\n\n    return createSuccessResponse(parsedData);\n  } catch (error) {\n    return createErrorResponse(error as Error, { \n      query: query.substring(0, 100),\n      options: { ...options, headers: undefined } // Don't log headers for security\n    });\n  }\n}\n\n/**\n * Parses the raw response from BlackBox AI\n * @param rawResponse - The raw response string\n * @returns Parsed data or null if parsing failed\n * @internal\n */\nfunction parseBlackBoxResponse(rawResponse: string): BlackBoxAIData | null {\n  try {\n    const parsed = rawResponse.split('$~~~$');\n    \n    if (parsed.length === 1) {\n      // Simple response without sources\n      const response = parsed[0]?.trim();\n      if (!response) {\n        return null;\n      }\n      \n      return {\n        response,\n        source: []\n      };\n    } else if (parsed.length >= 3) {\n      // Response with sources\n      const response = parsed[2]?.trim();\n      const sourcesData = parsed[1];\n      \n      if (!response || !sourcesData) {\n        return null;\n      }\n\n      const sources = safeJsonParse<BlackBoxSource[]>(sourcesData);\n      if (!Array.isArray(sources)) {\n        // If sources parsing fails, return response without sources\n        return {\n          response,\n          source: []\n        };\n      }\n\n      // Validate and sanitize sources\n      const validSources = sources\n        .filter(source => \n          source && \n          typeof source === 'object' && \n          typeof source.link === 'string' &&\n          typeof source.title === 'string'\n        )\n        .map(source => ({\n          link: source.link,\n          title: source.title,\n          snippet: source.snippet || '',\n          position: typeof source.position === 'number' ? source.position : 0\n        }));\n\n      return {\n        response,\n        source: validSources\n      };\n    }\n\n    return null;\n  } catch {\n    return null;\n  }\n}\n\n/**\n * Generates a random ID for requests\n * @returns Random ID string\n * @internal\n */\nfunction generateRandomId(): string {\n  const chars = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789';\n  let result = '';\n  for (let i = 0; i < 7; i++) {\n    result += chars.charAt(Math.floor(Math.random() * chars.length));\n  }\n  return result;\n}\n\n/**\n * Generates a UUID v4\n * @returns UUID string\n * @internal\n */\nfunction generateUUID(): string {\n  return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, function(c) {\n    const r = Math.random() * 16 | 0;\n    const v = c === 'x' ? r : (r & 0x3 | 0x8);\n    return v.toString(16);\n  });\n}","/**\n * @fileoverview Threads media scraper implementation\n * @author NB Team\n * @version 1.0.0\n */\n\nimport { \n  NBScraperResponse, \n  ThreadsMediaData, \n  ThreadsOptions \n} from '../types.js';\nimport { \n  createErrorResponse, \n  createSuccessResponse, \n  makeRequest, \n  validateRequiredParams,\n  isValidUrl,\n  extractDomain\n} from '../utils.js';\n\n/**\n * @alpha\n * Scrapes media URLs from Threads posts\n * \n * @example\n * ```typescript\n * import { threads } from 'nb-scraper';\n * \n * const result = await threads('https://www.threads.net/@username/post/123456789');\n * if (result.status) {\n *   console.log('Images:', result.data.image_urls);\n *   console.log('Videos:', result.data.video_urls);\n * }\n * ```\n * \n * @param url - The Threads post URL to scrape\n * @param options - Optional configuration for the request\n * @returns Promise resolving to media URLs from the post\n * \n * @throws Will not throw errors, returns error response instead\n * \n * @author Rian\n */\nexport async function threads(\n  url: string,\n  options: ThreadsOptions = {}\n): Promise<NBScraperResponse<ThreadsMediaData>> {\n  try {\n    // Validate input parameters\n    validateRequiredParams({ url }, ['url']);\n\n    // Validate URL format\n    const sanitizedUrl = url.trim();\n    if (!isValidUrl(sanitizedUrl)) {\n      return createErrorResponse('Invalid URL format', { url: sanitizedUrl });\n    }\n\n    // Check if URL is from Threads\n    const domain = extractDomain(sanitizedUrl);\n    if (!domain?.includes('threads.net')) {\n      return createErrorResponse('URL must be from threads.net', { domain, url: sanitizedUrl });\n    }\n\n    // Prepare API URL\n    const apiUrl = `https://api.threadsphotodownloader.com/v2/media?url=${encodeURIComponent(sanitizedUrl)}`;\n\n    // Prepare request headers\n    const headers = {\n      'User-Agent': '5.0',\n      'Accept': 'application/json',\n      'Accept-Language': 'id-ID,id;q=0.9,en;q=0.8',\n      ...options.headers\n    };\n\n    // Make the request\n    const response = await makeRequest(\n      {\n        method: 'GET',\n        url: apiUrl,\n        headers\n      },\n      {\n        timeout: options.timeout,\n        retries: options.retries,\n        retryDelay: options.retryDelay\n      }\n    );\n\n    // Validate response\n    if (!response.data || typeof response.data !== 'object') {\n      return createErrorResponse('Invalid response format from Threads API', {\n        responseType: typeof response.data,\n        status: response.status\n      });\n    }\n\n    const rawData = response.data as Record<string, unknown>;\n\n    // Parse and validate media URLs\n    const imageUrls = parseMediaUrls(rawData.image_urls);\n    const videoUrls = parseMediaUrls(rawData.video_urls);\n\n    // Apply filters based on options\n    let filteredData: ThreadsMediaData = {\n      image_urls: imageUrls,\n      video_urls: videoUrls\n    };\n\n    if (options.imagesOnly) {\n      filteredData.video_urls = [];\n    } else if (options.videosOnly) {\n      filteredData.image_urls = [];\n    }\n\n    // Check if any media was found\n    if (filteredData.image_urls.length === 0 && filteredData.video_urls.length === 0) {\n      return createErrorResponse('No media found in the Threads post', { \n        url: sanitizedUrl,\n        rawImageCount: imageUrls.length,\n        rawVideoCount: videoUrls.length\n      });\n    }\n\n    return createSuccessResponse(filteredData);\n\n  } catch (error) {\n    return createErrorResponse(error as Error, { \n      url: url.substring(0, 100),\n      options: { ...options, headers: undefined }\n    });\n  }\n}\n\n/**\n * Parses and validates media URLs from API response\n * @param urls - Raw URLs data from API\n * @returns Array of valid URL strings\n * @internal\n */\nfunction parseMediaUrls(urls: unknown): string[] {\n  if (!Array.isArray(urls)) {\n    return [];\n  }\n\n  return urls\n    .filter((url): url is string => \n      typeof url === 'string' && \n      url.trim().length > 0 && \n      isValidUrl(url.trim())\n    )\n    .map(url => url.trim())\n    .slice(0, 50); // Limit to prevent memory issues\n}","/**\n * @fileoverview Pinterest Scraper\n * @author Wolep\n * @version 1.0.0\n */\n\nimport { NBScraperResponse, PinterestData, ScraperErrorType, RequestConfig } from '../types';\nimport { \n  createErrorResponse, \n  createSuccessResponse, \n  makeRequest, \n  validateRequiredParams\n} from '../utils';\n\n/**\n * @alpha\n * Search Pinterest from the given query\n * \n * @example\n * ```typescript\n * import { Pinterest } from 'nb-scraper';\n * \n * const result = await Pinterest('jagung');\n * if (result.status) {\n *   console.log(result.data.result);\n * }\n * ```\n * \n * @param query - The query to search content on Pinterest\n * @param options - Optional request configuration\n * @returns Promise resolving Array of image URLs\n * \n * @throws Returns error response\n * \n * @author Wolep\n */\nexport async function pinterest(\n  query: string,\n  options?: RequestConfig\n): Promise<NBScraperResponse<PinterestData>> {\n  try {\n    // Validate required parameters\n    validateRequiredParams({ query }, ['query']);\n\n    // Prepare the request\n    const searchUrl = \"https://www.pinterest.com/resource/BaseSearchResource/get/\";\n    const params = new URLSearchParams({\n      data: JSON.stringify({\n        options: {\n          query: query\n        }\n      })\n    });\n\n    const response = await makeRequest({\n      url: `${searchUrl}?${params.toString()}`,\n      method: 'HEAD',\n      headers: {\n        'screen-dpr': '4',\n        'x-pinterest-pws-handler': 'www/search/[scope].js',\n        ...options?.headers\n      }\n    }, options);\n\n    // Extract links from response headers\n    const linkHeader = response.headers.link;\n    if (!linkHeader) {\n      return createErrorResponse('No results found for the query', {\n        type: ScraperErrorType.INVALID_RESPONSE,\n        context: { query }\n      });\n    }\n\n    // Parse the links from the header\n    const links = [...linkHeader.matchAll(/<(.*?)>/gm)].map(v => v[1]);\n\n    return createSuccessResponse<PinterestData>({\n      result: links\n    });\n\n  } catch (error) {\n    return createErrorResponse(error as Error, {\n      type: ScraperErrorType.NETWORK_ERROR,\n      context: { query }\n    });\n  }\n}","/**\n * @fileoverview ExomlAPI - AI Text Completion Service\n * Base URL: https://exomlapi.com/\n * \n * Features:\n * - AI text completion with conversation support\n * - Multiple model support (GPT-4.1, GPT-4o, Llama, etc.)\n * - Text-only responses\n * \n * Note: Some models may hang with slow fetch times\n * \n * @author wolep\n * @version 1.0.0\n * @lastUpdated 2025-06-07\n */\n\nimport {\n  NBScraperResponse,\n  CharSetOptions,\n  ExomlAPIData,\n  ExomlAPIOptions,\n  ExomlAPIMessage,\n  ExomlAPIRandomData,\n  ScraperErrorType\n} from '../types';\nimport {\n  createErrorResponse,\n  createSuccessResponse,\n  makeRequest,\n  validateRequiredParams\n} from '../utils';\n\nconst BASE_URL = 'https://exomlapi.com/api/chat';\n\n// Available models\nexport const EXOML_MODELS = [\n  'llama',\n  'gemma',\n  'qwen-3-235b',\n  'gpt-4.1',\n  'gpt-4o',\n  'gpt-4o-mini',\n  'llama-4-scout',\n  'llama-4-maverick',\n  'deepseek-r1',\n  'qwq-32b'\n] as\nconst;\n\nexport type ExomlModel = typeof EXOML_MODELS[number];\n\n/**\n * Generate random IDs for API request\n */\nfunction generateRandomIds(): ExomlAPIRandomData {\n  const gen = (length: number, charSet: CharSetOptions = {}): string => {\n    const l = \"abcdefghijklmnopqrstuvwxyz\";\n    const u = l.toUpperCase();\n    const s = \"-_\";\n    const n = \"0123456789\";\n    \n    const {\n      lowerCase = false,\n        upperCase = false,\n        symbol = false,\n        number = false\n    } = charSet;\n    \n    // Build character set based on options\n    let cs = \"\";\n    if (!lowerCase && !upperCase && !symbol && !number) {\n      cs = l + u + s + n; // Default: include everything\n    } else {\n      if (lowerCase) cs += l;\n      if (upperCase) cs += u;\n      if (symbol) cs += s;\n      if (number) cs += n;\n    }\n    \n    // Generate random string\n    return Array.from({ length }, () =>\n      cs[Math.floor(Math.random() * cs.length)]\n    ).join(\"\");\n  };\n  \n  // Generate IDs with specific character sets\n  const id = gen(16, { upperCase: true, lowerCase: true, number: true });\n  const timestamp = new Date().getTime();\n  const chatId =\n    `chat-${timestamp}-${gen(9, { lowerCase: true, number: true })}`;\n  const userId =\n    `local-user-${timestamp}-${gen(9, { lowerCase: true, number: true })}`;\n  const antiBotId = `${gen(32)}-${gen(8, { number: true, lowerCase: true })}`;\n  \n  return { id, chatId, userId, antiBotId };\n}\n\n/**\n * @alpha\n * Create a conversation message\n * \n * @example\n * ```typescript\n * import { createExomlMessage } from 'nb-scraper';\n * \n * const message = createExomlMessage(\"user\", \"Hello, how are you?\");\n * ```\n * \n * @param role - Message role\n * @param content - Message content\n * @returns ExomlAPIMessage\n * @author Wolep\n */\nexport function createExomlMessage(\n  role: \"user\" | \"assistant\" | \"system\",\n  content: string\n): ExomlAPIMessage {\n  return { role, content };\n}\n\n/**\n * Generate AI response\n * \n * @example\n * ```typescript\n * import { generateExomlResponse } from 'nb-scraper';\n * \n * const result = await generateExomlResponse({\n *   messages: [\n *     createExomlMessage(\"user\", \"Hello, how are you?\")\n *   ],\n *   model: \"gpt-4.1\"\n * });\n * \n * if (result.status) {\n *   console.log(result.data.content);\n * }\n * ```\n * \n * @param options - Configuration for the AI request\n * @returns Promise<NBScraperResponse<ExomlAPIData>>\n * @author Wolep\n */\nexport async function generateExomlResponse(\n  options: ExomlAPIOptions\n): Promise < NBScraperResponse < ExomlAPIData >> {\n  try {\n    validateRequiredParams(options, ['messages']);\n    \n    const { messages, systemPrompt = \"\", model = \"gpt-4.1\" } = options;\n    \n    if (!EXOML_MODELS.includes(model as ExomlModel)) {\n      return createErrorResponse(\n        `Invalid model. Available models: ${EXOML_MODELS.join(', ')}`, {\n          type: ScraperErrorType.INVALID_PARAMETER,\n          context: { model }\n        });\n    }\n    \n    const body = JSON.stringify({\n      messages,\n      systemPrompt,\n      model,\n      isAuthenticated: true,\n      ...generateRandomIds()\n    });\n    \n    const response = await makeRequest < { data: string } > ({\n      url: BASE_URL,\n      method: 'POST',\n      headers: {\n        'Content-Type': 'application/json'\n      },\n      data: body\n    });\n    \n    if (typeof response.data !== 'string') {\n      return createErrorResponse('Invalid response format from server', {\n        type: ScraperErrorType.INVALID_RESPONSE,\n        context: { rawResponse: response.data }\n      });\n    }\n    \n    // Parse response (parsing might be imperfect)\n    const data = response.data as string;\n    const content = [...data.matchAll(/^0:\"(.*?)\"$/gm)]\n      .map(v => v[1])\n      .join(\"\")\n      .replaceAll(\"\\\\n\", \"\\n\")\n      .replaceAll(\"\\\\\\\"\", \"\\\"\");\n    \n    if (!content) {\n      return createErrorResponse('Failed to parse message from server', {\n        type: ScraperErrorType.PARSE_ERROR,\n        context: { rawResponse: data }\n      });\n    }\n    \n    return createSuccessResponse < ExomlAPIData > ({ content });\n  } catch (error) {\n    return createErrorResponse(error as Error, {\n      type: ScraperErrorType.API_ERROR,\n      context: { service: 'ExomlAPI' }\n    });\n  }\n}","/**\n * @fileoverview DreamAnalysis - Dream Interpretation Service\n * Base URL: https://safe-coast-53976-cd772af9b056.herokuapp.com/\n * \n * Features:\n * - Analyze and interpret dreams from text descriptions\n * - Premium analysis features available\n * - Returns detailed interpretation with symbols, emotions, and themes\n * \n * @author NB Team\n * @version 1.0.0\n */\n\nimport {\n  NBScraperResponse,\n  DreamAnalysisData,\n  DreamAnalysisOptions,\n  ScraperErrorType\n} from '../types';\nimport {\n  createErrorResponse,\n  createSuccessResponse,\n  makeRequest,\n  validateRequiredParams\n} from '../utils';\n\nconst BASE_URL = 'https://safe-coast-53976-cd772af9b056.herokuapp.com/';\n\nfunction parseDreamResponse(raw: unknown): DreamAnalysisData | null {\n  if (typeof raw !== 'string') return null;\n  \n  try {\n    const data = JSON.parse(raw);\n    return {\n      analysis: data.analysis,\n      interpretation: data.interpretation,\n      symbols: data.symbols || [],\n      emotions: data.emotions || [],\n      themes: data.themes || [],\n      metadata: data.metadata || {}\n    };\n  } catch {\n    return null;\n  }\n}\n\n/**\n * Analyze dream text and get interpretation\n * \n * @example\n * ```typescript\n * import { analyzeDream } from 'nb-scraper';\n * \n * const result = await analyzeDream({\n *   text: \"I dreamed I was flying over mountains\",\n *   isPremium: true\n * });\n * \n * if (result.status) {\n *   console.log(result.data.interpretation);\n * }\n * ```\n * \n * @param options - Configuration for dream analysis\n * @returns Promise<NBScraperResponse<DreamAnalysisData>>\n * @author NajmyW\n */\nexport async function analyzeDream(\n  options: DreamAnalysisOptions\n): Promise < NBScraperResponse < DreamAnalysisData >> {\n  try {\n    validateRequiredParams(options, ['text']);\n    \n    const { text, isPremium = true } = options;\n    \n    const response = await makeRequest({\n      url: BASE_URL,\n      method: 'POST',\n      headers: {\n        'Accept-Encoding': 'gzip',\n        'Connection': 'Keep-Alive',\n        'Content-Type': 'application/json',\n        'Host': 'safe-coast-53976-cd772af9b056.herokuapp.com',\n        'User-Agent': 'okhttp/4.9.2'\n      },\n      data: JSON.stringify({ text, isPremium })\n    });\n    \n    const rawResponse = response.data;\n    \n    // Type guard untuk rawResponse\n    if (typeof rawResponse !== 'string') {\n      return createErrorResponse('Invalid response format', {\n        type: ScraperErrorType.INVALID_RESPONSE,\n        context: {\n          service: 'DreamAnalysis',\n          rawResponse: String(rawResponse).substring(0, 100) + '...'\n        }\n      });\n    }\n    \n    const parsedData = parseDreamResponse(rawResponse);\n    \n    if (!parsedData) {\n      return createErrorResponse('Failed to parse Dream response', {\n        type: ScraperErrorType.PARSE_ERROR,\n        context: {\n          rawResponse: rawResponse.substring(0, 100) + '...'\n        }\n      });\n    }\n    \n    return createSuccessResponse < DreamAnalysisData > (parsedData);\n  } catch (error) {\n    return createErrorResponse(error as Error, {\n      type: ScraperErrorType.API_ERROR,\n      context: { service: 'DreamAnalysis' }\n    });\n  }\n}\n\n/**\n * Quick analysis with basic interpretation\n * \n * @example\n * ```typescript\n * import { quickDreamAnalysis } from 'nb-scraper';\n * \n * const result = await quickDreamAnalysis(\"I dreamed of being chased\");\n * if (result.status) {\n *   console.log(result.data);\n * }\n * ```\n * \n * @param text - Dream description text\n * @returns Promise<NBScraperResponse<DreamAnalysisData>>\n * @author NajmyW\n */\nexport async function quickDreamAnalysis(\n  text: string\n): Promise < NBScraperResponse < DreamAnalysisData >> {\n  return analyzeDream({ text, isPremium: false });\n}\n\n/**\n * Premium analysis with detailed interpretation\n * \n * @example\n * ```typescript\n * import { premiumDreamAnalysis } from 'nb-scraper';\n * \n * const result = await premiumDreamAnalysis(\"I dreamed I could breathe underwater\");\n * if (result.status) {\n *   console.log(result.data.symbols);\n * }\n * ```\n * \n * @param text - Dream description text\n * @returns Promise<NBScraperResponse<DreamAnalysisData>>\n * @author NajmyW\n */\nexport async function premiumDreamAnalysis(\n  text: string\n): Promise < NBScraperResponse < DreamAnalysisData >> {\n  return analyzeDream({ text, isPremium: true });\n}","/**\n * @fileoverview Pollinations AI Image Generation Service\n * Base URL: https://image.pollinations.ai/\n * \n * Features:\n * - Generate images from text prompts\n * - Upload generated images to Catbox.moe for permanent hosting\n * - No logo option available\n * \n * @author NB Team\n * @version 1.0.1\n */\n\nimport { Readable } from 'stream';\nimport FormData from 'form-data';\nimport fs from 'fs';\nimport path from 'path';\nimport os from 'os';\nimport { \n  NBScraperResponse, \n  PollinationsData, \n  PollinationsOptions,\n  ScraperErrorType\n} from '../types';\nimport { \n  createErrorResponse, \n  createSuccessResponse, \n  makeRequest, \n  validateRequiredParams,\n} from '../utils';\n\nconst BASE_URL = 'https://image.pollinations.ai/prompt/';\nconst UPLOAD_URL = 'https://catbox.moe/user/api.php';\n\n/**\n * @alpha\n * Generate image from prompt and upload to Catbox\n * \n * @example\n * ```typescript\n * import { generatePollinationsImage } from 'nb-scraper';\n * \n * const result = await generatePollinationsImage({\n *   prompt: \"a beautiful sunset over mountains\",\n *   nologo: true\n * });\n * \n * if (result.status) {\n *   console.log(result.data.url); // Catbox.moe URL\n * }\n * ```\n * \n * @param options - Configuration for image generation\n * @returns Promise<NBScraperResponse<PollinationsData>>\n * @author Jul\n */\nexport async function generatePollinationsImage(\n  options: PollinationsOptions\n): Promise<NBScraperResponse<PollinationsData>> {\n  try {\n    // Validate required parameters\n    validateRequiredParams(options, ['prompt']);\n\n    const { prompt, nologo = true } = options;\n    const encodedPrompt = encodeURIComponent(prompt);\n    const imageUrl = `${BASE_URL}${encodedPrompt}${nologo ? '?nologo=true' : ''}`;\n    const tempPath = path.join(os.tmpdir(), `pollinations_${Date.now()}.jpg`);\n\n    // Download image to temporary file\n    const response = await makeRequest<ArrayBuffer>({\n      url: imageUrl,\n      responseType: 'arraybuffer'\n    });\n\n    // Create stream from buffer and write to file\n    const buffer = Buffer.from(response.data);\n    const readable = new Readable();\n    readable.push(buffer);\n    readable.push(null);\n\n    const writer = fs.createWriteStream(tempPath);\n    readable.pipe(writer);\n\n    // Wait for download to complete\n    await new Promise<void>((resolve, reject) => {\n      writer.on('finish', () => resolve());\n      writer.on('error', (err) => reject(err));\n    });\n\n    // Upload to Catbox.moe\n    const form = new FormData();\n    form.append('reqtype', 'fileupload');\n    form.append('fileToUpload', fs.createReadStream(tempPath));\n\n    const upload = await makeRequest<string>({\n      method: 'POST',\n      url: UPLOAD_URL,\n      data: form,\n      headers: form.getHeaders()\n    });\n\n    // Clean up temporary file\n    fs.unlinkSync(tempPath);\n\n    if (typeof upload.data !== 'string') {\n      throw new Error('Invalid upload response');\n    }\n\n    return createSuccessResponse<PollinationsData>({\n      url: upload.data,\n      directUrl: imageUrl\n    });\n  } catch (error) {\n    return createErrorResponse(error as Error, {\n      type: ScraperErrorType.IMAGE_GENERATION_ERROR,\n      context: { service: 'Pollinations' }\n    });\n  }\n}\n\n/**\n * Get direct image URL (without upload to Catbox)\n * \n * @example\n * ```typescript\n * import { getPollinationsDirectUrl } from 'nb-scraper';\n * \n * const url = getPollinationsDirectUrl({\n *   prompt: \"a beautiful sunset over mountains\",\n *   nologo: true\n * });\n * \n * console.log(url); // Direct Pollinations image URL\n * ```\n * \n * @param options - Configuration for image generation\n * @returns string - Direct image URL\n * @author Jul\n */\nexport function getPollinationsDirectUrl(options: PollinationsOptions): string {\n  validateRequiredParams(options, ['prompt']);\n  \n  const { prompt, nologo = true } = options;\n  const encodedPrompt = encodeURIComponent(prompt);\n  return `${BASE_URL}${encodedPrompt}${nologo ? '?nologo=true' : ''}`;\n}","/**\n * @fileoverview SoundCloud Music Search and Track Information\n * Base URL: https://soundcloud.com/\n * \n * Features:\n * - Search tracks with detailed information\n * - Auto client_id extraction and caching\n * - Format duration, numbers, and dates\n * - Track metadata including plays, likes, downloads\n * \n * @author NB Team\n * @version 1.0.0\n */\n\nimport {\n  NBScraperResponse,\n  SoundCloudData,\n  SoundCloudSearchOptions,\n  SoundCloudTrack,\n  SoundCloudCache,\n  SoundCloudApiResponse,\n  SoundCloudApiTrack,\n  ScraperErrorType\n} from '../types';\nimport {\n  createErrorResponse,\n  createSuccessResponse,\n  makeRequest,\n  validateRequiredParams,\n  formatBytes\n} from '../utils';\n\nconst BASE_URL = 'https://soundcloud.com/';\nconst API_URL = 'https://api-v2.soundcloud.com/search/tracks';\n\n// Module-level cache\nlet cache: SoundCloudCache = { version: '', id: '' };\n\n/**\n * Format duration from milliseconds to MM:SS\n * @param ms - Duration in milliseconds\n * @returns Formatted duration string\n */\nfunction formatDuration(ms: number): string {\n  const sec = Math.floor(ms / 1000);\n  const min = Math.floor(sec / 60);\n  const remainder = sec % 60;\n  return `${min}:${remainder.toString().padStart(2, '0')}`;\n}\n\n/**\n * Format large numbers with K/M suffixes\n * @param n - Number to format\n * @returns Formatted number string\n */\nfunction formatNumber(n: number): string {\n  if (n >= 1e6) return (n / 1e6).toFixed(1).replace(/\\.0$/, '') + 'M';\n  if (n >= 1e3) return (n / 1e3).toFixed(1).replace(/\\.0$/, '') + 'K';\n  return n.toString();\n}\n\n/**\n * Format date to YYYY-MM-DD\n * @param dateStr - Date string to format\n * @returns Formatted date string or null\n */\nfunction formatDate(dateStr: string | null): string | null {\n  if (!dateStr) return null;\n  const d = new Date(dateStr);\n  return d.toISOString().split('T')[0];\n}\n\n/**\n * Get SoundCloud client ID by parsing website\n * @returns Promise<string | null>\n */\nasync function getClientID(): Promise < string | null > {\n  try {\n    const response = await makeRequest({\n      url: BASE_URL,\n      method: 'GET'\n    });\n    \n    if (typeof response.data !== 'string') {\n      throw new Error('invalid html data')\n    }\n    \n    const html = response.data;\n    const version = html.match(\n      /<script>window\\.__sc_version=\"(\\d{10})\"<\\/script>/)?.[1];\n    if (!version) return null;\n    \n    // Return cached ID if version matches\n    if (cache.version === version) return cache.id;\n    \n    // Extract script URLs and find client_id\n    const scriptMatches = [...html.matchAll(\n      /<script.*?src=\"(https:\\/\\/a-v2\\.sndcdn\\.com\\/assets\\/[^\"]+)\"/g)];\n    \n    for (const [, scriptUrl] of scriptMatches) {\n      const { data: js } = await makeRequest({\n        url: scriptUrl,\n        method: 'GET'\n      });\n      \n      if (typeof js !== 'string') {\n        continue;\n      }\n      \n      const idMatch = js.match(/client_id:\"([a-zA-Z0-9]{32})\"/);\n      if (idMatch) {\n        cache = { version, id: idMatch[1] };\n        return idMatch[1];\n      }\n    }\n  } catch (error) {\n    throw new Error(\n      `Failed to get client_id: ${error instanceof Error ? error.message : 'Unknown error'}`\n      );\n  }\n  \n  return null;\n}\n\n/**\n * Search SoundCloud tracks\n * \n * @example\n * ```typescript\n * import { searchSoundCloud } from 'nb-scraper';\n * \n * const result = await searchSoundCloud({\n *   query: \"lofi chill\",\n *   limit: 10\n * });\n * \n * if (result.status) {\n *   console.log(result.data.tracks);\n * }\n * ```\n * \n * @param options - Search configuration\n * @returns Promise<NBScraperResponse<SoundCloudData>>\n * @author Rian\n */\nexport async function searchSoundCloud(\n  options: SoundCloudSearchOptions\n): Promise < NBScraperResponse < SoundCloudData >> {\n  \n  const { query, limit = 3 } = options;\n  let clientId: string | null = null;\n  \n  try {\n    validateRequiredParams(options, ['query']);\n    \n    const clientId = await getClientID();\n    \n    if (!clientId) {\n      return createErrorResponse('Failed to obtain client_id', {\n        type: ScraperErrorType.AUTH_ERROR,\n        context: { service: 'SoundCloud' }\n      });\n    }\n    \n    const response = await makeRequest < SoundCloudApiResponse > ({\n      url: API_URL,\n      method: 'GET',\n      params: {\n        q: query,\n        client_id: clientId,\n        limit\n      }\n    });\n    \n    if (!response.data?.collection) {\n      return createErrorResponse('Invalid SoundCloud API response', {\n        type: ScraperErrorType.INVALID_RESPONSE\n      });\n    }\n    \n    const tracks: SoundCloudTrack[] = response.data.collection.map(track => {\n      const durationMs = track.duration;\n      const duration = formatDuration(durationMs);\n      \n      const likeCount = formatNumber(track.likes_count);\n      const playCount = formatNumber(track.playback_count);\n      const downloadCount = formatNumber(track.download_count);\n      \n      const releaseDate = track.release_date || track.created_at;\n      \n      return {\n        id: track.id,\n        title: track.title,\n        url: track.permalink_url,\n        duration,\n        thumbnail: track.artwork_url,\n        author: {\n          name: track.user.username,\n          url: track.user.permalink_url\n        },\n        like_count: likeCount,\n        download_count: downloadCount,\n        play_count: playCount,\n        release_date: formatDate(releaseDate)\n      };\n    });\n    \n    return createSuccessResponse < SoundCloudData > ({ tracks });\n  } catch (error) {\n    return createErrorResponse(error as Error, {\n      type: ScraperErrorType.API_ERROR,\n      context: { service: 'SoundCloud', query: query, clientId: clientId ? '*****' : 'null' }\n    });\n  }\n}\n\n/**\n * @alpha\n * Get cached client ID and version info\n * \n * @example\n * ```typescript\n * import { getSoundCloudCacheInfo } from 'nb-scraper';\n * \n * const cacheInfo = getSoundCloudCacheInfo();\n * console.log(cacheInfo);\n * ```\n * \n * @returns Current cache state\n * @author Rian\n */\nexport function getSoundCloudCacheInfo(): SoundCloudCache {\n  return { ...cache };\n}","/**\n * @fileoverview DeepInfra AI Chat Service\n * Base URL: https://ai-sdk-starter-deepinfra.vercel.app/api/chat\n * \n * Features:\n * - AI text generation with multiple model support\n * - Handles various response formats\n * - Fallback for empty responses\n * \n * @author Woi\n * @version 1.0.0\n */\n\nimport {\n  NBScraperResponse,\n  DeepInfraAIData,\n  DeepInfraAIOptions,\n  DeepInfraAIMessage,\n  DeepInfraAIModel,\n  DeepInfraAIRequest,\n  DeepInfraAIResponse,\n  ScraperErrorType\n} from '../types';\nimport {\n  createErrorResponse,\n  createSuccessResponse,\n  makeRequest,\n  validateRequiredParams\n} from '../utils';\n\nconst BASE_URL = 'https://ai-sdk-starter-deepinfra.vercel.app/api/chat';\n\n/**\n * Available DeepInfra AI models\n */\nexport const DEEPINFRA_MODELS = [\n  'meta-llama/Llama-3.3-70B-Instruct-Turbo',\n  'deepseek-ai/DeepSeek-R1',\n  'Qwen/Qwen2.5-72B-Instruct'\n] as\nconst;\n\n/**\n * Generate AI response using DeepInfra\n * \n * @example\n * ```typescript\n * import { generateDeepInfraResponse } from 'nb-scraper';\n * \n * const result = await generateDeepInfraResponse({\n *   prompt: \"Explain JavaScript in simple terms\",\n *   model: \"deepseek-ai/DeepSeek-R1\"\n * });\n * \n * if (result.status) {\n *   console.log(result.data.response);\n * }\n * ```\n * \n * @param options - Configuration for the AI request\n * @returns Promise<NBScraperResponse<DeepInfraAIData>>\n * @author Woi\n */\nexport async function generateDeepInfraResponse(\n  options: DeepInfraAIOptions\n): Promise < NBScraperResponse < DeepInfraAIData >> {\n  try {\n    validateRequiredParams(options, ['prompt']);\n    \n    const { prompt, model = 'meta-llama/Llama-3.3-70B-Instruct-Turbo' } =\n    options;\n    \n    const body = {\n      id: Math.random().toString(36).slice(2),\n      selectedModel: model,\n      messages: [{\n        role: 'user',\n        content: prompt,\n        parts: [{ type: 'text', text: prompt }]\n      }]\n    };\n    \n    const response = await makeRequest < DeepInfraAIResponse > ({\n      url: BASE_URL,\n      method: 'POST',\n      headers: {\n        'Content-Type': 'application/json'\n      },\n      data: body\n    });\n    \n    // Process response parts\n    const parts: string[] = [];\n    const responseData = response.data;\n    \n    if (responseData && typeof responseData === 'object') {\n      const data = responseData as DeepInfraAIResponse;\n      \n      if (data.g) {\n        parts.push(...(Array.isArray(data.g) ? data.g : [data.g]));\n      }\n      if (data.f) {\n        parts.push(...(Array.isArray(data.f) ? data.f : [data.f]));\n      }\n      if (data['0']) {\n        parts.push(...(Array.isArray(data['0']) ? data['0'] : [data['0']]));\n      }\n    } else if (typeof responseData === 'string') {\n      parts.push(responseData);\n    }\n    \n    const result = parts.join('').trim() || 'No response generated';\n    \n    return createSuccessResponse < DeepInfraAIData > ({\n      response: result\n    });\n    \n  } catch (error) {\n    return createErrorResponse(error as Error, {\n      type: ScraperErrorType.API_ERROR,\n      context: {\n        service: 'DeepInfraAI',\n        model: options.model\n      }\n    });\n  }\n}","/**\n * @fileoverview Anime Indo Scraper\n * Base URL: https://anime-indo.lol\n * \n * Features:\n * - Search anime\n * - Get anime details\n * - Download episodes\n * \n * @author Jul\n * @version 1.0.1\n */\n\nimport axios from 'axios';\nimport { URL } from 'url';\nimport * as cheerio from 'cheerio';\nimport {\n  NBScraperResponse,\n  AnimeIndoSearchResult,\n  AnimeIndoDetail,\n  AnimeIndoDownloadInfo,\n  AnimeIndoEpisode,\n  ScraperErrorType\n} from '../types';\nimport { \n  createErrorResponse, \n  createSuccessResponse, \n  makeRequest,\n  validateRequiredParams\n} from '../utils';\n\nconst BASE_URL = 'https://anime-indo.lol';\n\nexport const animeIndo = {\n  /**\n   * Search anime\n   * \n   * @example\n   * ```typescript\n   * const result = await animeIndo.search(\"Naruto\");\n   * if (result.status) {\n   *   console.log(result.data);\n   * }\n   * ```\n   * @author Jul\n   */\n  async search(query: string): Promise<NBScraperResponse<AnimeIndoSearchResult[]>> {\n    try {\n      validateRequiredParams({ query }, ['query']);\n\n      const url = `${BASE_URL}/search/${encodeURIComponent(query)}/`;\n      const response = await makeRequest<string>({ url });\n\n      const $ = cheerio.load(response.data);\n      const results: AnimeIndoSearchResult[] = [];\n\n      $(\"table.otable\").each((_index: number, el: cheerio.Element) => {\n        const element = $(el);\n        const title = element.find(\".videsc a\").text().trim();\n        const link = BASE_URL + element.find(\".videsc a\").attr(\"href\");\n        const image = BASE_URL + element.find(\"img\").attr(\"src\");\n        const description = element.find(\"p.des\").text().trim();\n        const labelEls = element.find(\".label\");\n        const year = labelEls.last().text().trim();\n\n        results.push({\n          title,\n          link,\n          image,\n          year,\n          description,\n        });\n      });\n\n      return createSuccessResponse(results);\n    } catch (error) {\n      return createErrorResponse(error as Error, {\n        type: ScraperErrorType.API_ERROR,\n        context: { service: 'AnimeIndo', query }\n      });\n    }\n  },\n\n  /**\n   * Get anime details\n   * \n   * @example\n   * ```typescript\n   * const result = await animeIndo.detail(\"https://anime-indo.lol/anime/naruto\");\n   * if (result.status) {\n   *   console.log(result.data);\n   * }\n   * ```\n   * @author Jul\n   */\n  async detail(url: string): Promise<NBScraperResponse<AnimeIndoDetail>> {\n    try {\n      validateRequiredParams({ url }, ['url']);\n\n      const response = await makeRequest<string>({ url });\n      const $ = cheerio.load(response.data);\n\n      const title = $(\"h1.title\").text().trim();\n\n      let imageSrc = $(\".detail img\").attr(\"src\") || \"\";\n      if (imageSrc.startsWith(\"/\")) {\n        imageSrc = BASE_URL + imageSrc;\n      }\n\n      const genres: string[] = [];\n      $(\".detail li a\").each((_index: number, el: cheerio.Element) => {\n        genres.push($(el).text().trim());\n      });\n\n      const description = $(\".detail p\").text().trim();\n\n      const episodes: AnimeIndoEpisode[] = [];\n      $(\".ep a\").each((_index: number, el: cheerio.Element) => {\n        let epLink = $(el).attr(\"href\");\n        if (epLink && epLink.startsWith(\"/\")) {\n          epLink = BASE_URL + epLink;\n        }\n        episodes.push({\n          episode: $(el).text().trim(),\n          link: epLink || \"\",\n        });\n      });\n\n      return createSuccessResponse({\n        title,\n        image: imageSrc,\n        genres,\n        description,\n        episodes,\n      });\n    } catch (error) {\n      return createErrorResponse(error as Error, {\n        type: ScraperErrorType.API_ERROR,\n        context: { service: 'AnimeIndo', url }\n      });\n    }\n  },\n\n  /**\n   * Download episode\n   * \n   * @example\n   * ```typescript\n   * const result = await animeIndo.download(\"https://anime-indo.lol/episode/naruto-1\");\n   * if (result.status) {\n   *   console.log(result.data.downloadUrl);\n   * }\n   * ```\n   * @author Jul\n   */\n  async download(episodeUrl: string): Promise<NBScraperResponse<AnimeIndoDownloadInfo>> {\n    try {\n      validateRequiredParams({ episodeUrl }, ['episodeUrl']);\n\n      // Get episode page\n      const { data: episodeHtml } = await makeRequest<string>({\n        url: episodeUrl,\n        headers: { 'User-Agent': 'Mozilla/5.0' }\n      });\n      const $ = cheerio.load(episodeHtml);\n\n      const title = $('h1.title').first().text().trim();\n      const description = $('.detail p').text().trim();\n\n      //