import type {
  FieldPrediction,
  MLFieldFeatures,
} from "../shared/ml";

export type { FieldPrediction, MLFieldFeatures } from "../shared/ml";

export class ContentMLDetector {
  private static instance: ContentMLDetector;
  private initialized = false;

  static getInstance(): ContentMLDetector {
    if (!ContentMLDetector.instance) {
      ContentMLDetector.instance = new ContentMLDetector();
    }
    return ContentMLDetector.instance;
  }

  async init(): Promise<void> {
    if (this.initialized) return;
    const response = await chrome.runtime.sendMessage({ type: "ML_INIT" });
    this.initialized = Boolean((response as { ok?: boolean }).ok);
  }

  extractFeatures(input: HTMLInputElement): MLFieldFeatures {
    const inputType = input.type.toLowerCase();
    const matchScore = (text: string, patterns: RegExp[]): number => {
      if (!text) return 0;
      const matches = patterns.reduce(
        (count, pattern) => count + (pattern.test(text) ? 1 : 0),
        0
      );
      return Math.min((matches / patterns.length) * 3, 1);
    };

    const userPatterns = [
      /user/i,
      /login/i,
      /usr/i,
      /uname/i,
      /account/i,
      /acct/i,
      /signin/i,
      /sign-in/i,
      /session/i,
      /member/i,
      /alias/i,
    ];
    const emailPatterns = [/email/i, /e-mail/i, /mail/i];
    const passPatterns = [
      /pass/i,
      /password/i,
      /pwd/i,
      /secret/i,
      /passphrase/i,
      /key/i,
      /credential/i,
    ];

    const features: MLFieldFeatures = {
      type_text: inputType === "text" ? 1 : 0,
      type_email: inputType === "email" ? 1 : 0,
      type_password: inputType === "password" ? 1 : 0,
      type_tel: inputType === "tel" ? 1 : 0,
      type_number: inputType === "number" ? 1 : 0,
      type_search: inputType === "search" ? 1 : 0,
      type_url: inputType === "url" ? 1 : 0,
      type_other: [
        "text",
        "email",
        "password",
        "tel",
        "number",
        "search",
        "url",
      ].includes(inputType)
        ? 0
        : 1,
      auto_username: 0,
      auto_email: 0,
      auto_current_password: 0,
      auto_new_password: 0,
      auto_one_time_code: 0,
      auto_off: 0,
      auto_other: 0,
      name_has_user: matchScore(input.name, userPatterns),
      name_has_login: matchScore(input.name, [/login/i]),
      name_has_email: matchScore(input.name, emailPatterns),
      name_has_pass: matchScore(input.name, passPatterns),
      name_length: input.name.length / 50,
      id_has_user: matchScore(input.id, userPatterns),
      id_has_login: matchScore(input.id, [/login/i]),
      id_has_email: matchScore(input.id, emailPatterns),
      id_has_pass: matchScore(input.id, passPatterns),
      id_length: input.id.length / 50,
      placeholder_has_user: matchScore(input.placeholder, userPatterns),
      placeholder_has_email: matchScore(input.placeholder, emailPatterns),
      placeholder_has_pass: matchScore(input.placeholder, passPatterns),
      placeholder_length: input.placeholder.length / 100,
      aria_label_has_user: matchScore(
        input.getAttribute("aria-label") || "",
        userPatterns
      ),
      aria_label_has_email: matchScore(
        input.getAttribute("aria-label") || "",
        emailPatterns
      ),
      aria_label_has_pass: matchScore(
        input.getAttribute("aria-label") || "",
        passPatterns
      ),
      aria_label_length: (input.getAttribute("aria-label") || "").length / 100,
      parent_is_form: 0,
      parent_is_div: 0,
      parent_is_section: 0,
      sibling_count: 0,
      has_password_sibling: 0,
      has_email_sibling: 0,
      form_has_submit: 0,
      form_action_has_login: 0,
      is_required: input.required ? 1 : 0,
      has_placeholder: input.placeholder ? 1 : 0,
      has_aria_label: input.getAttribute("aria-label") ? 1 : 0,
      inputmode_numeric: input.inputMode === "numeric" ? 1 : 0,
    };

    const auto = (input.getAttribute("autocomplete") || "").toLowerCase();
    if (auto.includes("username")) features.auto_username = 1;
    else if (auto.includes("email")) features.auto_email = 1;
    else if (auto.includes("current-password")) features.auto_current_password = 1;
    else if (auto.includes("new-password")) features.auto_new_password = 1;
    else if (auto.includes("one-time-code")) features.auto_one_time_code = 1;
    else if (auto === "off") features.auto_off = 1;
    else features.auto_other = 1;

    const parent = input.parentElement;
    if (parent) {
      const parentName = parent.tagName.toLowerCase();
      features.parent_is_form = parentName === "form" ? 1 : 0;
      features.parent_is_div = parentName === "div" ? 1 : 0;
      features.parent_is_section = parentName === "section" ? 1 : 0;

      const siblings = Array.from(parent.children).filter(
        (el) => el.tagName === "INPUT"
      );
      features.sibling_count = siblings.length / 10;
      for (const sibling of siblings) {
        if (sibling === input) continue;
        const siblingType = (sibling as HTMLInputElement).type;
        if (siblingType === "password") features.has_password_sibling = 1;
        if (siblingType === "email") features.has_email_sibling = 1;
      }
    }

    const form = input.closest("form");
    if (form) {
      features.form_has_submit = form.querySelector(
        'button[type="submit"], input[type="submit"]'
      )
        ? 1
        : 0;
      const action = form.getAttribute("action") || "";
      features.form_action_has_login = /login|signin|auth|session/i.test(action)
        ? 1
        : 0;
    }

    return features;
  }

  async predictBatch(
    inputs: HTMLInputElement[]
  ): Promise<(FieldPrediction | null)[]> {
    try {
      const featuresArray = inputs.map((input) => this.extractFeatures(input));
      const response = await chrome.runtime.sendMessage({
        type: "ML_PREDICT_BATCH",
        payload: { featuresArray },
      });
      const data = (response as { ok?: boolean; data?: unknown }).data;
      return (response as { ok?: boolean }).ok && Array.isArray(data)
        ? (data as FieldPrediction[])
        : inputs.map(() => null);
    } catch {
      return inputs.map(() => null);
    }
  }
}

export const contentMLDetector = ContentMLDetector.getInstance();