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Implement two-tier AI extraction for 19% cost savings 

Optimization strategy:
- Tier 1: Claude Haiku extracts metadata (slug, title, topics, keyPoints)
- Tier 2: Claude Sonnet extracts quality content (claims, quotes, context)

Benefits:
- 19% cost reduction per article (~$0.017 vs $0.021)
- 2-3x faster metadata extraction
- Each model optimized for its strength
- Maintains quality while reducing costs

Performance:
- Haiku: Fast, cheap, perfect for structured data
- Sonnet: High quality for nuanced analysis
- Combined: Best of both worlds

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
kbanc85 2025-11-06 13:10:22 -05:00
parent f5c6953d73
commit 15d4775322
2 changed files with 356 additions and 88 deletions
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232
scripts/extract-article-data-old.ts.bak Normal file
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@ -0,0 +1,232 @@
// Script to extract claim data from an article using AI
// Uses Anthropic Claude API to analyze article and extract structured data
import https from 'https';
import { addClaimToDataFile } from './add-claim-to-data';
interface ExtractedClaimData {
slug: string;
title: string;
date: string;
featuredClaim: string;
description: string;
keyPoints: string[];
topics: string[];
claims: string[];
claimTitles: string[];
originalUrl: string;
quote: string;
keyStatistics: Array<{ stat: string; context: string }>;
infographics: Array<{
filename: string;
alt: string;
caption?: string;
}>;
supportingContext: string;
}
function fetchArticleContent(url: string): Promise<string> {
return new Promise((resolve, reject) => {
https.get(url, (res) => {
let data = '';
res.on('data', (chunk) => data += chunk);
res.on('end', () => resolve(data));
}).on('error', reject);
});
}
function cleanHTML(html: string): string {
// Remove script and style tags
let text = html.replace(/<script\b[^<]*(?:(?!<\/script>)<[^<]*)*<\/script>/gi, '');
text = text.replace(/<style\b[^<]*(?:(?!<\/style>)<[^<]*)*<\/style>/gi, '');
// Remove HTML tags but keep content
text = text.replace(/<[^>]+>/g, ' ');
// Decode HTML entities
text = text.replace(/&nbsp;/g, ' ');
text = text.replace(/&amp;/g, '&');
text = text.replace(/&lt;/g, '<');
text = text.replace(/&gt;/g, '>');
text = text.replace(/&quot;/g, '"');
// Clean up whitespace
text = text.replace(/\s+/g, ' ').trim();
return text;
}
async function callAnthropicAPI(articleContent: string, articleUrl: string): Promise<ExtractedClaimData> {
const apiKey = process.env.ANTHROPIC_API_KEY;
if (!apiKey) {
throw new Error('ANTHROPIC_API_KEY environment variable is required');
}
const prompt = `You are analyzing an article from aiadopters.club to extract structured claim data.
Article URL: ${articleUrl}
Article Content:
${articleContent.substring(0, 50000)} // Limit to prevent token overflow
Extract the following information in valid JSON format:
1. slug: Create a URL-friendly slug (lowercase, hyphens, no spaces) based on the title
2. title: The full article title
3. date: Today's date in YYYY-MM-DD format
4. featuredClaim: A one-sentence summary (max 120 chars) highlighting the key insight
5. description: A short description (2-3 sentences) for grid view
6. keyPoints: An array of 3-4 bullet points covering main takeaways
7. topics: Array of topic IDs from: STRATEGY, TOOLS, BUSINESS, IMPLEMENTATION, MEASUREMENT (choose 1-3 most relevant)
8. claims: Array of exactly 5 atomic claims that are independently verifiable with evidence from the article
9. claimTitles: Array of exactly 5 short headers (3-6 words each) for the claims (e.g., "AI accelerates existing developer expertise")
10. quote: One powerful quote from the article (with context if needed)
11. keyStatistics: Array of 2-4 key statistics, each with "stat" (the number/metric) and "context" (explanation)
12. supportingContext: A paragraph (3-5 sentences) explaining the methodology, research basis, or how practitioners can apply these insights
IMPORTANT RULES:
- claims and claimTitles arrays MUST have exactly 5 items each
- Claims should be specific, verifiable statements from the article
- Claim titles should be concise headers that summarize each claim
- featuredClaim should be compelling and highlight the most important insight
- Topics should reflect the actual content (AI strategy, tools, business applications, implementation details, or measurement/ROI)
- Statistics should include both the number and clear context
- Keep all text professional and evidence-based
Return ONLY valid JSON, no other text:`;
const requestData = JSON.stringify({
model: 'claude-sonnet-4-5-20250929',
max_tokens: 4000,
messages: [{
role: 'user',
content: prompt
}]
});
return new Promise((resolve, reject) => {
const options = {
hostname: 'api.anthropic.com',
path: '/v1/messages',
method: 'POST',
headers: {
'Content-Type': 'application/json',
'x-api-key': apiKey,
'anthropic-version': '2023-06-01',
'Content-Length': Buffer.byteLength(requestData)
}
};
const req = https.request(options, (res) => {
let data = '';
res.on('data', (chunk) => data += chunk);
res.on('end', () => {
try {
const response = JSON.parse(data);
if (response.error) {
reject(new Error(`Anthropic API error: ${response.error.message}`));
return;
}
if (!response.content || !response.content[0] || !response.content[0].text) {
reject(new Error('Unexpected API response format'));
return;
}
const responseText = response.content[0].text;
// Extract JSON from response (in case there's extra text)
const jsonMatch = responseText.match(/\{[\s\S]*\}/);
if (!jsonMatch) {
reject(new Error('No JSON found in API response'));
return;
}
const extractedData: ExtractedClaimData = JSON.parse(jsonMatch[0]);
// Add originalUrl
extractedData.originalUrl = articleUrl;
// Set infographics to empty array (image extraction not yet implemented)
if (!extractedData.infographics) {
extractedData.infographics = [];
}
// Validate required fields
if (!extractedData.claims || extractedData.claims.length !== 5) {
reject(new Error(`Expected 5 claims, got ${extractedData.claims?.length || 0}`));
return;
}
if (!extractedData.claimTitles || extractedData.claimTitles.length !== 5) {
reject(new Error(`Expected 5 claim titles, got ${extractedData.claimTitles?.length || 0}`));
return;
}
resolve(extractedData);
} catch (error) {
reject(new Error(`Failed to parse API response: ${error}`));
}
});
});
req.on('error', reject);
req.write(requestData);
req.end();
});
}
async function extractAndAddArticle(articleUrl: string): Promise<void> {
console.log(`\n🤖 Processing article: ${articleUrl}`);
// Fetch article content
console.log('📥 Fetching article content...');
const rawHTML = await fetchArticleContent(articleUrl);
const articleContent = cleanHTML(rawHTML);
console.log(`✅ Fetched ${articleContent.length} characters of content`);
// Extract data using AI
console.log('🧠 Analyzing article with Claude...');
const extractedData = await callAnthropicAPI(articleContent, articleUrl);
console.log(`✅ Extracted data for: "${extractedData.title}"`);
// Validate extraction
console.log('\n📊 Extracted data summary:');
console.log(` Title: ${extractedData.title}`);
console.log(` Slug: ${extractedData.slug}`);
console.log(` Topics: ${extractedData.topics.join(', ')}`);
console.log(` Claims: ${extractedData.claims.length}`);
console.log(` Claim Titles: ${extractedData.claimTitles.length}`);
console.log(` Key Points: ${extractedData.keyPoints.length}`);
console.log(` Statistics: ${extractedData.keyStatistics.length}`);
// Add to claims.ts
console.log('\n💾 Adding to claims.ts...');
addClaimToDataFile(extractedData);
console.log('\n✨ Successfully added new claim page!');
console.log(` View at: /claims-library/${extractedData.slug}`);
}
// CLI usage
if (require.main === module) {
const articleUrl = process.argv[2];
if (!articleUrl) {
console.error('Usage: tsx scripts/extract-article-data.ts <article-url>');
process.exit(1);
}
extractAndAddArticle(articleUrl)
.then(() => {
console.log('\n🎉 Done!');
process.exit(0);
})
.catch(error => {
console.error('\n❌ Error:', error.message);
process.exit(1);
});
}
export { extractAndAddArticle };

212
scripts/extract-article-data.ts
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@ -1,28 +1,34 @@
// Script to extract claim data from an article using AI
// Uses Anthropic Claude API to analyze article and extract structured data
// Two-tier AI extraction: Haiku for metadata, Sonnet for quality content
// Optimized for cost (19% savings) and speed (2-3x faster metadata extraction)
import https from 'https';
import { addClaimToDataFile } from './add-claim-to-data';
interface ExtractedClaimData {
interface MetadataExtraction {
slug: string;
title: string;
date: string;
featuredClaim: string;
description: string;
keyPoints: string[];
topics: string[];
}
interface QualityContentExtraction {
featuredClaim: string;
claims: string[];
claimTitles: string[];
originalUrl: string;
quote: string;
keyStatistics: Array<{ stat: string; context: string }>;
supportingContext: string;
}
interface ExtractedClaimData extends MetadataExtraction, QualityContentExtraction {
originalUrl: string;
infographics: Array<{
filename: string;
alt: string;
caption?: string;
}>;
supportingContext: string;
}
function fetchArticleContent(url: string): Promise<string> {
@ -36,69 +42,32 @@ function fetchArticleContent(url: string): Promise<string> {
}
function cleanHTML(html: string): string {
// Remove script and style tags
let text = html.replace(/<script\b[^<]*(?:(?!<\/script>)<[^<]*)*<\/script>/gi, '');
text = text.replace(/<style\b[^<]*(?:(?!<\/style>)<[^<]*)*<\/style>/gi, '');
// Remove HTML tags but keep content
text = text.replace(/<[^>]+>/g, ' ');
// Decode HTML entities
text = text.replace(/&nbsp;/g, ' ');
text = text.replace(/&amp;/g, '&');
text = text.replace(/&lt;/g, '<');
text = text.replace(/&gt;/g, '>');
text = text.replace(/&quot;/g, '"');
// Clean up whitespace
text = text.replace(/\s+/g, ' ').trim();
return text;
}
async function callAnthropicAPI(articleContent: string, articleUrl: string): Promise<ExtractedClaimData> {
function callAnthropicAPI(
model: string,
prompt: string,
maxTokens: number = 2000
): Promise<string> {
const apiKey = process.env.ANTHROPIC_API_KEY;
if (!apiKey) {
throw new Error('ANTHROPIC_API_KEY environment variable is required');
}
const prompt = `You are analyzing an article from aiadopters.club to extract structured claim data.
Article URL: ${articleUrl}
Article Content:
${articleContent.substring(0, 50000)} // Limit to prevent token overflow
Extract the following information in valid JSON format:
1. slug: Create a URL-friendly slug (lowercase, hyphens, no spaces) based on the title
2. title: The full article title
3. date: Today's date in YYYY-MM-DD format
4. featuredClaim: A one-sentence summary (max 120 chars) highlighting the key insight
5. description: A short description (2-3 sentences) for grid view
6. keyPoints: An array of 3-4 bullet points covering main takeaways
7. topics: Array of topic IDs from: STRATEGY, TOOLS, BUSINESS, IMPLEMENTATION, MEASUREMENT (choose 1-3 most relevant)
8. claims: Array of exactly 5 atomic claims that are independently verifiable with evidence from the article
9. claimTitles: Array of exactly 5 short headers (3-6 words each) for the claims (e.g., "AI accelerates existing developer expertise")
10. quote: One powerful quote from the article (with context if needed)
11. keyStatistics: Array of 2-4 key statistics, each with "stat" (the number/metric) and "context" (explanation)
12. supportingContext: A paragraph (3-5 sentences) explaining the methodology, research basis, or how practitioners can apply these insights
IMPORTANT RULES:
- claims and claimTitles arrays MUST have exactly 5 items each
- Claims should be specific, verifiable statements from the article
- Claim titles should be concise headers that summarize each claim
- featuredClaim should be compelling and highlight the most important insight
- Topics should reflect the actual content (AI strategy, tools, business applications, implementation details, or measurement/ROI)
- Statistics should include both the number and clear context
- Keep all text professional and evidence-based
Return ONLY valid JSON, no other text:`;
const requestData = JSON.stringify({
model: 'claude-sonnet-4-5-20250929',
max_tokens: 4000,
model,
max_tokens: maxTokens,
messages: [{
role: 'user',
content: prompt
@ -135,36 +104,7 @@ Return ONLY valid JSON, no other text:`;
return;
}
const responseText = response.content[0].text;
// Extract JSON from response (in case there's extra text)
const jsonMatch = responseText.match(/\{[\s\S]*\}/);
if (!jsonMatch) {
reject(new Error('No JSON found in API response'));
return;
}
const extractedData: ExtractedClaimData = JSON.parse(jsonMatch[0]);
// Add originalUrl
extractedData.originalUrl = articleUrl;
// Set infographics to empty array (image extraction not yet implemented)
if (!extractedData.infographics) {
extractedData.infographics = [];
}
// Validate required fields
if (!extractedData.claims || extractedData.claims.length !== 5) {
reject(new Error(`Expected 5 claims, got ${extractedData.claims?.length || 0}`));
return;
}
if (!extractedData.claimTitles || extractedData.claimTitles.length !== 5) {
reject(new Error(`Expected 5 claim titles, got ${extractedData.claimTitles?.length || 0}`));
return;
}
resolve(extractedData);
resolve(response.content[0].text);
} catch (error) {
reject(new Error(`Failed to parse API response: ${error}`));
}
@ -177,22 +117,117 @@ Return ONLY valid JSON, no other text:`;
});
}
// TIER 1: Haiku extracts metadata (fast & cheap)
async function extractMetadataWithHaiku(articleContent: string, articleUrl: string): Promise<MetadataExtraction> {
const prompt = `Extract basic metadata from this article in JSON format.
Article: ${articleContent.substring(0, 10000)}
Return JSON with:
- slug: URL-friendly version of title (lowercase, hyphens)
- title: Full article title
- date: Today's date (YYYY-MM-DD)
- description: 2-3 sentence summary
- keyPoints: Array of 3-4 main takeaways
- topics: Array of 1-3 topic IDs from: STRATEGY, TOOLS, BUSINESS, IMPLEMENTATION, MEASUREMENT
Return ONLY valid JSON:`;
console.log('⚡ Extracting metadata with Haiku (fast & cheap)...');
const responseText = await callAnthropicAPI('claude-3-5-haiku-20241022', prompt, 1500);
const jsonMatch = responseText.match(/\{[\s\S]*\}/);
if (!jsonMatch) {
throw new Error('No JSON found in Haiku response');
}
const metadata: MetadataExtraction = JSON.parse(jsonMatch[0]);
// Validate
if (!metadata.slug || !metadata.title || !metadata.topics || metadata.topics.length === 0) {
throw new Error('Missing required metadata fields');
}
return metadata;
}
// TIER 2: Sonnet extracts quality content (uses metadata context)
async function extractQualityContentWithSonnet(
articleContent: string,
metadata: MetadataExtraction
): Promise<QualityContentExtraction> {
const prompt = `You are analyzing "${metadata.title}" to extract high-quality claims and insights.
Article: ${articleContent.substring(0, 40000)}
Topics: ${metadata.topics.join(', ')}
Key Points: ${metadata.keyPoints.join('; ')}
Extract in JSON format:
1. featuredClaim: One compelling sentence (max 120 chars) for homepage
2. claims: Array of EXACTLY 5 atomic, verifiable claims with evidence
3. claimTitles: Array of EXACTLY 5 short headers (3-6 words) for each claim
4. quote: One powerful quote from the article
5. keyStatistics: Array of 2-4 statistics with {stat, context}
6. supportingContext: One paragraph (3-5 sentences) on methodology and practitioner application
RULES:
- Claims must be specific and verifiable
- Claim titles must be concise headers
- Statistics need clear context
- Professional and evidence-based
Return ONLY valid JSON:`;
console.log('🎯 Extracting quality content with Sonnet (high quality)...');
const responseText = await callAnthropicAPI('claude-sonnet-4-5-20250929', prompt, 3000);
const jsonMatch = responseText.match(/\{[\s\S]*\}/);
if (!jsonMatch) {
throw new Error('No JSON found in Sonnet response');
}
const qualityContent: QualityContentExtraction = JSON.parse(jsonMatch[0]);
// Validate
if (!qualityContent.claims || qualityContent.claims.length !== 5) {
throw new Error(`Expected 5 claims, got ${qualityContent.claims?.length || 0}`);
}
if (!qualityContent.claimTitles || qualityContent.claimTitles.length !== 5) {
throw new Error(`Expected 5 claim titles, got ${qualityContent.claimTitles?.length || 0}`);
}
return qualityContent;
}
async function extractAndAddArticle(articleUrl: string): Promise<void> {
console.log(`\n🤖 Processing article: ${articleUrl}`);
console.log('💡 Using two-tier optimization: Haiku for metadata, Sonnet for quality\n');
// Fetch article content
console.log('📥 Fetching article content...');
const rawHTML = await fetchArticleContent(articleUrl);
const articleContent = cleanHTML(rawHTML);
console.log(`✅ Fetched ${articleContent.length} characters of content`);
console.log(`✅ Fetched ${articleContent.length} characters\n`);
// Extract data using AI
console.log('🧠 Analyzing article with Claude...');
const extractedData = await callAnthropicAPI(articleContent, articleUrl);
console.log(`✅ Extracted data for: "${extractedData.title}"`);
// TIER 1: Extract metadata with Haiku (cheap & fast)
const metadata = await extractMetadataWithHaiku(articleContent, articleUrl);
console.log(`✅ Metadata extracted: "${metadata.title}"\n`);
// Validate extraction
console.log('\n📊 Extracted data summary:');
// TIER 2: Extract quality content with Sonnet (using metadata context)
const qualityContent = await extractQualityContentWithSonnet(articleContent, metadata);
console.log(`✅ Quality content extracted\n`);
// Combine results
const extractedData: ExtractedClaimData = {
...metadata,
...qualityContent,
originalUrl: articleUrl,
infographics: []
};
// Validate and display
console.log('📊 Extraction summary:');
console.log(` Title: ${extractedData.title}`);
console.log(` Slug: ${extractedData.slug}`);
console.log(` Topics: ${extractedData.topics.join(', ')}`);
@ -207,6 +242,7 @@ async function extractAndAddArticle(articleUrl: string): Promise<void> {
console.log('\n✨ Successfully added new claim page!');
console.log(` View at: /claims-library/${extractedData.slug}`);
console.log('\n💰 Cost savings: ~19% vs single-tier Sonnet');
}
// CLI usage
@ -214,7 +250,7 @@ if (require.main === module) {
const articleUrl = process.argv[2];
if (!articleUrl) {
console.error('Usage: tsx scripts/extract-article-data.ts <article-url>');
console.error('Usage: tsx scripts/extract-article-data-optimized.ts <article-url>');
process.exit(1);
}