mirror of
https://github.com/clucraft/PriceGhost.git
synced 2026-05-15 10:52:36 +02:00
259 lines
7.3 KiB
TypeScript
259 lines
7.3 KiB
TypeScript
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import Anthropic from '@anthropic-ai/sdk';
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import OpenAI from 'openai';
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import axios from 'axios';
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import { load } from 'cheerio';
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import { AISettings } from '../models';
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import { ParsedPrice } from '../utils/priceParser';
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import { StockStatus } from './scraper';
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export interface AIExtractionResult {
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name: string | null;
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price: ParsedPrice | null;
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imageUrl: string | null;
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stockStatus: StockStatus;
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confidence: number;
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}
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const EXTRACTION_PROMPT = `You are a price extraction assistant. Analyze the following HTML content from a product page and extract the product information.
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Return a JSON object with these fields:
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- name: The product name/title (string or null)
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- price: The current selling price as a number (not the original/crossed-out price)
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- currency: The currency code (USD, EUR, GBP, etc.)
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- imageUrl: The main product image URL (string or null)
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- stockStatus: One of "in_stock", "out_of_stock", or "unknown"
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- confidence: Your confidence in the extraction from 0 to 1
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Important:
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- Extract the CURRENT/SALE price, not the original price if there's a discount
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- If you can't find a price with confidence, set price to null
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- Only return valid JSON, no explanation text
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HTML Content:
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`;
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// Truncate HTML to fit within token limits while preserving important content
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function prepareHtmlForAI(html: string): string {
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const $ = load(html);
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// Remove script, style, and other non-content elements
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$('script, style, noscript, iframe, svg, path, meta, link, comment').remove();
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// Get the body content
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let content = $('body').html() || html;
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// Try to focus on product-related sections if possible
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const productSelectors = [
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'[itemtype*="Product"]',
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'[class*="product"]',
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'[id*="product"]',
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'[class*="pdp"]',
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'main',
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'[role="main"]',
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];
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for (const selector of productSelectors) {
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const section = $(selector).first();
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if (section.length && section.html() && section.html()!.length > 500) {
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content = section.html()!;
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break;
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}
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}
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// Also extract JSON-LD data which often contains product info
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const jsonLdScripts: string[] = [];
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$('script[type="application/ld+json"]').each((_, el) => {
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const scriptContent = $(el).html();
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if (scriptContent && scriptContent.includes('price')) {
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jsonLdScripts.push(scriptContent);
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}
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});
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// Combine content with JSON-LD data
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let finalContent = content;
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if (jsonLdScripts.length > 0) {
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finalContent = `JSON-LD Data:\n${jsonLdScripts.join('\n')}\n\nHTML Content:\n${content}`;
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}
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// Truncate to ~15000 characters to stay within token limits
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if (finalContent.length > 15000) {
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finalContent = finalContent.substring(0, 15000) + '\n... [truncated]';
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}
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return finalContent;
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}
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async function extractWithAnthropic(
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html: string,
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apiKey: string
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): Promise<AIExtractionResult> {
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const anthropic = new Anthropic({ apiKey });
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const preparedHtml = prepareHtmlForAI(html);
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const response = await anthropic.messages.create({
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model: 'claude-3-haiku-20240307',
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max_tokens: 1024,
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messages: [
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{
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role: 'user',
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content: EXTRACTION_PROMPT + preparedHtml,
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},
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],
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});
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const content = response.content[0];
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if (content.type !== 'text') {
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throw new Error('Unexpected response type from Anthropic');
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}
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return parseAIResponse(content.text);
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}
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async function extractWithOpenAI(
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html: string,
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apiKey: string
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): Promise<AIExtractionResult> {
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const openai = new OpenAI({ apiKey });
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const preparedHtml = prepareHtmlForAI(html);
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const response = await openai.chat.completions.create({
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model: 'gpt-4o-mini',
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max_tokens: 1024,
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messages: [
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{
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role: 'user',
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content: EXTRACTION_PROMPT + preparedHtml,
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},
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],
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});
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const content = response.choices[0]?.message?.content;
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if (!content) {
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throw new Error('No response from OpenAI');
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}
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return parseAIResponse(content);
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}
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function parseAIResponse(responseText: string): AIExtractionResult {
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// Try to extract JSON from the response
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let jsonStr = responseText.trim();
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// Handle markdown code blocks
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const jsonMatch = jsonStr.match(/```(?:json)?\s*([\s\S]*?)```/);
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if (jsonMatch) {
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jsonStr = jsonMatch[1].trim();
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}
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// Try to find JSON object in the response
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const objectMatch = jsonStr.match(/\{[\s\S]*\}/);
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if (objectMatch) {
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jsonStr = objectMatch[0];
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}
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try {
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const data = JSON.parse(jsonStr);
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let price: ParsedPrice | null = null;
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if (data.price !== null && data.price !== undefined) {
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const priceNum = typeof data.price === 'string'
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? parseFloat(data.price.replace(/[^0-9.]/g, ''))
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: data.price;
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if (!isNaN(priceNum) && priceNum > 0) {
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price = {
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price: priceNum,
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currency: data.currency || 'USD',
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};
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}
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}
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let stockStatus: StockStatus = 'unknown';
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if (data.stockStatus) {
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const status = data.stockStatus.toLowerCase().replace(/[^a-z_]/g, '');
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if (status === 'in_stock' || status === 'instock') {
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stockStatus = 'in_stock';
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} else if (status === 'out_of_stock' || status === 'outofstock') {
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stockStatus = 'out_of_stock';
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}
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}
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return {
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name: data.name || null,
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price,
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imageUrl: data.imageUrl || data.image || null,
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stockStatus,
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confidence: data.confidence || 0.5,
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};
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} catch (error) {
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console.error('Failed to parse AI response:', responseText);
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return {
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name: null,
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price: null,
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imageUrl: null,
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stockStatus: 'unknown',
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confidence: 0,
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};
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}
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}
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export async function extractWithAI(
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url: string,
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settings: AISettings
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): Promise<AIExtractionResult> {
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// Fetch the page HTML
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const response = await axios.get<string>(url, {
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headers: {
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'User-Agent':
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'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36',
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Accept:
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'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8',
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},
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timeout: 20000,
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});
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const html = response.data;
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// Use the configured provider
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if (settings.ai_provider === 'anthropic' && settings.anthropic_api_key) {
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return extractWithAnthropic(html, settings.anthropic_api_key);
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} else if (settings.ai_provider === 'openai' && settings.openai_api_key) {
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return extractWithOpenAI(html, settings.openai_api_key);
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}
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throw new Error('No valid AI provider configured');
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}
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// Export for use in scraper as fallback
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export async function tryAIExtraction(
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url: string,
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html: string,
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userId: number
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): Promise<AIExtractionResult | null> {
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try {
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// Import dynamically to avoid circular dependencies
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const { userQueries } = await import('../models');
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const settings = await userQueries.getAISettings(userId);
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if (!settings?.ai_enabled) {
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return null;
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}
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// Use the configured provider
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if (settings.ai_provider === 'anthropic' && settings.anthropic_api_key) {
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console.log(`[AI] Using Anthropic for ${url}`);
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return await extractWithAnthropic(html, settings.anthropic_api_key);
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} else if (settings.ai_provider === 'openai' && settings.openai_api_key) {
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console.log(`[AI] Using OpenAI for ${url}`);
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return await extractWithOpenAI(html, settings.openai_api_key);
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}
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return null;
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} catch (error) {
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console.error(`[AI] Extraction failed for ${url}:`, error);
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return null;
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}
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}
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