import type { ZTagStyle } from "./types/users";
import { getCuratedTagsPrompt, getTagStylePrompt } from "./utils/tag";

/**
 * Remove duplicate whitespaces to avoid tokenization issues
 */
function preprocessContent(content: string) {
  return content.replace(/(\s){10,}/g, "$1");
}

export function buildImagePrompt(
  lang: string,
  customPrompts: string[],
  tagStyle: ZTagStyle,
  curatedTags?: string[],
) {
  const tagStyleInstruction = getTagStylePrompt(tagStyle);
  const curatedInstruction = getCuratedTagsPrompt(curatedTags);

  return `
You are an expert whose responsibility is to help with automatic text tagging for a read-it-later/bookmarking app.
Analyze the attached image and suggest relevant tags that describe its key themes, topics, and main ideas. The rules are:
- Aim for a variety of tags, including broad categories, specific keywords, and potential sub-genres.
- The tags must be in ${lang}.
- If the tag is not generic enough, don't include it.
- Aim for 10-15 tags.
- If there are no good tags, don't emit any.
${curatedInstruction}
${tagStyleInstruction}
${customPrompts && customPrompts.map((p) => `- ${p}`).join("\n")}
You must respond in valid JSON with the key "tags" and the value is list of tags. Don't wrap the response in a markdown code.`;
}

/**
 * Construct tagging prompt for text content
 */
export function constructTextTaggingPrompt(
  lang: string,
  customPrompts: string[],
  content: string,
  tagStyle: ZTagStyle,
  curatedTags?: string[],
): string {
  const tagStyleInstruction = getTagStylePrompt(tagStyle);
  const curatedInstruction = getCuratedTagsPrompt(curatedTags);

  return `
You are an expert whose responsibility is to help with automatic tagging for a read-it-later/bookmarking app.
Analyze the TEXT_CONTENT below and suggest relevant tags that describe its key themes, topics, and main ideas. The rules are:
- Aim for a variety of tags, including broad categories, specific keywords, and potential sub-genres.
- The tags must be in ${lang}.
- If the tag is not generic enough, don't include it.
- Do NOT generate tags related to:
    - An error page (404, 403, blocked, not found, dns errors)
    - Boilerplate content (cookie consent, login walls, GDPR notices)
- Aim for 3-5 tags.
- If there are no good tags, leave the array empty.
${curatedInstruction}
${tagStyleInstruction}
${customPrompts && customPrompts.map((p) => `- ${p}`).join("\n")}

<TEXT_CONTENT>
${content}
</TEXT_CONTENT>
You must respond in JSON with the key "tags" and the value is an array of string tags.`;
}

/**
 * Construct summary prompt
 */
export function constructSummaryPrompt(
  lang: string,
  customPrompts: string[],
  content: string,
): string {
  return `
Summarize the following content responding ONLY with the summary. You MUST follow the following rules:
- Summary must be in 3-4 sentences.
- The summary must be in ${lang}.
${customPrompts && customPrompts.map((p) => `- ${p}`).join("\n")}
    ${content}`;
}

/**
 * Build text tagging prompt without truncation (for previews/UI)
 */
export function buildTextPromptUntruncated(
  lang: string,
  customPrompts: string[],
  content: string,
  tagStyle: ZTagStyle,
  curatedTags?: string[],
): string {
  return constructTextTaggingPrompt(
    lang,
    customPrompts,
    preprocessContent(content),
    tagStyle,
    curatedTags,
  );
}

/**
 * Build summary prompt without truncation (for previews/UI)
 */
export function buildSummaryPromptUntruncated(
  lang: string,
  customPrompts: string[],
  content: string,
): string {
  return constructSummaryPrompt(
    lang,
    customPrompts,
    preprocessContent(content),
  );
}

/**
 * Build OCR prompt for extracting text from images using LLM
 */
export function buildOCRPrompt(): string {
  return `You are an OCR (Optical Character Recognition) expert. Your task is to extract ALL text from this image.

Rules:
- Extract every piece of text visible in the image, including titles, body text, captions, labels, watermarks, and any other textual content.
- Preserve the original structure and formatting as much as possible (e.g., paragraphs, lists, headings).
- If text appears in multiple columns, read from left to right, top to bottom.
- If text is partially obscured or unclear, make your best attempt and indicate uncertainty with [unclear] if needed.
- Do not add any commentary, explanations, or descriptions of non-text elements.
- If there is no text in the image, respond with an empty string.
- Output ONLY the extracted text, nothing else.`;
}