import { buildMetaDescriptionPrompt, parseMetaDescriptionResponse } from '@power-seo/ai';

// 1. Build the prompt
const prompt = buildMetaDescriptionPrompt({
  title: 'Best Coffee Shops in New York City',
  content: 'Explore the top 15 coffee shops in NYC, from specialty espresso bars in Brooklyn...',
  focusKeyphrase: 'coffee shops nyc',
});

// 2. Send to your LLM of choice (example uses OpenAI)
import OpenAI from 'openai';
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

const response = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    { role: 'system', content: prompt.system },
    { role: 'user', content: prompt.user },
  ],
  max_tokens: prompt.maxTokens,
});

// 3. Parse the raw text response
const result = parseMetaDescriptionResponse(response.choices[0].message.content ?? '');
console.log(`"${result.description}" — ${result.charCount} chars, ~${result.pixelWidth}px`);
console.log(`Valid: ${result.isValid}`);

import { buildMetaDescriptionPrompt, parseMetaDescriptionResponse } from '@power-seo/ai';
import type { MetaDescriptionInput, MetaDescriptionResult } from '@power-seo/ai';

const input: MetaDescriptionInput = {
  title: 'How to Optimize React Apps for SEO',
  content: 'Full article HTML or plain text about React SEO strategies...',
  focusKeyphrase: 'react seo optimization',
};

const prompt = buildMetaDescriptionPrompt(input);
// { system: 'You are an expert SEO copywriter...', user: 'Write 3 meta descriptions...', maxTokens: 300 }

const rawResponse = await yourLLM.complete(prompt.system, prompt.user, prompt.maxTokens);
const result: MetaDescriptionResult = parseMetaDescriptionResponse(rawResponse);

console.log(`"${result.description}"`);
console.log(`  ${result.charCount} characters, ~${result.pixelWidth}px`);
console.log(`  Valid: ${result.isValid}`);
if (result.validationMessage) console.log(`  Message: ${result.validationMessage}`);

import { buildTitlePrompt, parseTitleResponse } from '@power-seo/ai';
import type { TitleInput, TitleResult } from '@power-seo/ai';

const input: TitleInput = {
  content: 'Article about the best tools for keyword research in 2026...',
  focusKeyphrase: 'keyword research tools',
  tone: 'informative',
};

const prompt = buildTitlePrompt(input);
const rawResponse = await yourLLM.complete(prompt.system, prompt.user, prompt.maxTokens);

const results: TitleResult[] = parseTitleResponse(rawResponse);
results.forEach(({ title, charCount, pixelWidth }, i) => {
  const status = charCount <= 60 ? 'OK' : 'TOO LONG';
  console.log(`${i + 1}. "${title}" — ${charCount} chars [${status}]`);
});

import { buildContentSuggestionsPrompt, parseContentSuggestionsResponse } from '@power-seo/ai';
import type { ContentSuggestionInput, ContentSuggestion } from '@power-seo/ai';

const input: ContentSuggestionInput = {
  title: 'React SEO Best Practices',
  content: '<h1>React SEO</h1><p>React is a JavaScript library...</p>',
  focusKeyphrase: 'react seo best practices',
  analysisResults: 'Current score: 58/100. Missing headings structure.',
};

const prompt = buildContentSuggestionsPrompt(input);
const rawResponse = await yourLLM.complete(prompt.system, prompt.user, prompt.maxTokens);

const suggestions: ContentSuggestion[] = parseContentSuggestionsResponse(rawResponse);
suggestions.forEach(({ type, suggestion, priority }) => {
  console.log(`[Priority ${priority}] ${type}: ${suggestion}`);
});

// Example output:
// [Priority 5] heading: Add h2 subheadings for "Server-Side Rendering" topic
// [Priority 4] paragraph: Expand "React Hooks" section with more examples
// [Priority 3] keyword: Increase usage of "react seo best practices" by 1-2 more mentions
// [Priority 2] link: Link to related article on Next.js SSR optimization

import { buildSerpPredictionPrompt, parseSerpPredictionResponse } from '@power-seo/ai';
import type { SerpFeatureInput, SerpFeaturePrediction } from '@power-seo/ai';

const input: SerpFeatureInput = {
  title: 'How to Make Cold Brew Coffee at Home',
  content: '<h1>Cold Brew Coffee</h1><h2>Step 1: Grind the Coffee</h2><p>...</p>',
  schema: ['HowTo', 'Recipe'],
  contentType: 'guide',
};

const prompt = buildSerpPredictionPrompt(input);
const rawResponse = await yourLLM.complete(prompt.system, prompt.user, prompt.maxTokens);

const predictions: SerpFeaturePrediction[] = parseSerpPredictionResponse(rawResponse);
predictions.forEach(({ feature, likelihood, requirements, met }) => {
  console.log(`${feature}: ${(likelihood * 100).toFixed(0)}% likelihood`);
  console.log(`  Requirements: ${requirements.join(', ')}`);
  console.log(`  Met: ${met.join(', ')}`);
});

import { analyzeSerpEligibility } from '@power-seo/ai';

// HowTo — detected by step-structured headings and HowTo schema
const result = analyzeSerpEligibility({
  title: 'How to Install Node.js on Ubuntu',
  content: '<h2>Step 1: Update apt</h2><p>...</p><h2>Step 2: Install nvm</h2><p>...</p>',
  schema: ['HowTo'],
});
// Returns array with SerpFeaturePrediction objects, including:
// { feature: 'how-to', likelihood: 0.8, requirements: [...], met: [...] }

// FAQ — detected by FAQPage schema
const faqResult = analyzeSerpEligibility({
  title: 'React SEO FAQ',
  content: '<h2>Does React hurt SEO?</h2><p>...</p><h2>How do I add meta tags?</h2><p>...</p>',
  schema: ['FAQPage'],
});
// Returns array including:
// { feature: 'faq-rich-result', likelihood: 0.9, requirements: [...], met: [...] }

// OpenAI
import OpenAI from 'openai';
import { buildMetaDescriptionPrompt, parseMetaDescriptionResponse } from '@power-seo/ai';

const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const prompt = buildMetaDescriptionPrompt({
  title: 'My Article',
  content: '...',
  focusKeyphrase: 'my topic',
});

const openaiResponse = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    { role: 'system', content: prompt.system },
    { role: 'user', content: prompt.user },
  ],
  max_tokens: prompt.maxTokens,
});
const result = parseMetaDescriptionResponse(openaiResponse.choices[0].message.content ?? '');

// Anthropic Claude
import Anthropic from '@anthropic-ai/sdk';
const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

const claudeResponse = await anthropic.messages.create({
  model: 'claude-opus-4-6',
  system: prompt.system,
  messages: [{ role: 'user', content: prompt.user }],
  max_tokens: prompt.maxTokens,
});
const result2 = parseMetaDescriptionResponse(
  claudeResponse.content[0].type === 'text' ? claudeResponse.content[0].text : '',
);

// Google Gemini
import { GoogleGenerativeAI } from '@google/generative-ai';
const genai = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);
const model = genai.getGenerativeModel({ model: 'gemini-1.5-pro' });
const geminiResponse = await model.generateContent(`${prompt.system}\n\n${prompt.user}`);
const result3 = parseMetaDescriptionResponse(geminiResponse.response.text());

import type {
  PromptTemplate, // { system: string; user: string; maxTokens?: number }
  MetaDescriptionInput, // { title, content, focusKeyphrase?, maxLength?, tone? }
  MetaDescriptionResult, // { description, charCount, pixelWidth, isValid, validationMessage? }
  ContentSuggestionInput, // { title, content, focusKeyphrase?, analysisResults? }
  ContentSuggestionType, // 'heading' | 'paragraph' | 'keyword' | 'link'
  ContentSuggestion, // { type: ContentSuggestionType; suggestion: string; priority: number }
  SerpFeature, // 'featured-snippet' | 'faq-rich-result' | 'how-to' | 'product' | 'review' | 'video' | 'image-pack' | 'local-pack' | 'sitelinks'
  SerpFeatureInput, // { title, content, schema?, contentType? }
  SerpFeaturePrediction, // { feature: SerpFeature; likelihood: number; requirements: string[]; met: string[] }
  TitleInput, // { content, focusKeyphrase?, tone? }
  TitleResult, // { title: string; charCount: number; pixelWidth: number }
} from '@power-seo/ai';