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https://github.com/R0m1k3/Priceflow.git
synced 2026-10-11 17:29:14 +02:00
feat: Add improved search and AI price extraction services, update Docker Compose, and introduce benchmark verification script.
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@@ -31,9 +31,9 @@ class AIPriceExtractor:
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logger.warning("No OpenRouter API key found for AI Price Extraction")
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return None
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# Smart truncation: keep first 3000 chars which usually contain the price
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# and product info.
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clean_html = html_content[:3000]
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# Smart truncation: keep first 15000 chars to ensure we capture the price
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# (3000 was too short for B&M)
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clean_html = html_content[:15000]
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prompt = f"""
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You are a price extraction expert.
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@@ -52,13 +52,13 @@ class AIPriceExtractor:
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try:
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# Try Primary Model (Gemma 3)
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# Note: Removed response_format={"type": "json_object"} as it's not supported by all models
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response = await acompletion(
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model=cls.PRIMARY_MODEL,
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messages=[{"role": "user", "content": prompt}],
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api_key=api_key,
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api_base="https://openrouter.ai/api/v1",
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temperature=0.1,
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response_format={"type": "json_object"}
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temperature=0.1
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)
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except Exception as e:
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logger.warning(f"Primary model {cls.PRIMARY_MODEL} failed ({e}), trying fallback {cls.FALLBACK_MODEL}...")
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@@ -68,24 +68,28 @@ class AIPriceExtractor:
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messages=[{"role": "user", "content": prompt}],
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api_key=api_key,
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api_base="https://openrouter.ai/api/v1",
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temperature=0.1,
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response_format={"type": "json_object"}
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temperature=0.1
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)
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content = response.choices[0].message.content
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content = response.choices[0].message.content
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if not content:
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return None
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data = json.loads(content)
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price = data.get("price")
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if price:
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# Handle string price "24,95" or "24.95"
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if isinstance(price, str):
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price = price.replace(',', '.').replace('€', '').strip()
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return float(price)
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# Clean markdown code blocks if present (common with LLMs)
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content = content.replace("```json", "").replace("```", "").strip()
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try:
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data = json.loads(content)
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price = data.get("price")
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if price and str(price).lower() != "null":
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# Handle string price "24,95" or "24.95"
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if isinstance(price, str):
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price = price.replace(',', '.').replace('€', '').strip()
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return float(price)
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except json.JSONDecodeError:
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logger.warning(f"Failed to parse AI response as JSON: {content}")
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return None
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return None
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@@ -467,7 +467,7 @@ class ImprovedSearchService:
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@staticmethod
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async def _extract_price(page: Page) -> float | None:
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"""Extract price using Hybrid Strategy: JSON-LD -> AI -> CSS"""
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"""Extract price using Hybrid Strategy: JSON-LD -> AI -> Strict CSS -> Loose CSS"""
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import re
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# STRATEGY 1: JSON-LD (Most reliable)
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@@ -499,7 +499,8 @@ class ImprovedSearchService:
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# STRATEGY 2: AI Extraction (Priority over CSS as requested)
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try:
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logger.info(" 🤖 Attempting AI extraction (Priority Strategy)...")
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# Only try AI if API key is configured (check implicitly via helper)
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# We log info but don't block if it fails
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html_content = await page.content()
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title = await page.title()
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@@ -510,9 +511,60 @@ class ImprovedSearchService:
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except Exception as e:
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logger.error(f" AI extraction failed: {e}")
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# STRATEGY 3: CSS Selectors (Fallback)
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# STRATEGY 3: Strict CSS Selectors (High Confidence)
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# These selectors usually point to the main product price.
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# If found, we trust them and return immediately.
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strict_selectors = [
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'[itemprop="price"]', # Schema.org standard
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'.current-price-value',
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'.product-price .price',
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'meta[property="product:price:amount"]',
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'meta[name="twitter:data1"]', # Sometimes used for price
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]
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# PRIORITY 1: Selectors for sale/promotional prices (highest priority)
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for selector in strict_selectors:
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try:
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# Check meta tags first
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if selector.startswith('meta'):
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element = await page.query_selector(selector)
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if element:
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content = await element.get_attribute('content')
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if content:
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try:
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price_val = float(content.strip().replace(',', '.'))
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logger.debug(f" ✅ Found price via Meta Tag {selector}: {price_val}€")
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return price_val
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except:
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pass
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continue
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# Standard elements
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elements = await page.query_selector_all(selector)
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for elem in elements:
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# Skip hidden
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if not await elem.is_visible():
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continue
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price_text = await elem.inner_text()
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if price_text:
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cleaned = price_text.strip().replace('€', '').replace('EUR', '').strip()
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cleaned = cleaned.replace(' ', '').replace('\xa0', '').replace(',', '.')
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match = re.search(r'(\d+\.?\d*)', cleaned)
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if match:
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try:
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price_val = float(match.group(1))
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if 0.01 < price_val < 100000:
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logger.debug(f" ✅ Found price via Strict CSS {selector}: {price_val}€")
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return price_val
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except:
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continue
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except:
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continue
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# STRATEGY 4: Loose CSS Selectors (Fallback - Lowest Price Logic)
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# Used when strict selectors fail. We collect ALL prices and pick the lowest.
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# PRIORITY 1: Selectors for sale/promotional prices
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sale_price_selectors = [
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'.price-current',
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'.prix-actuel',
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@@ -527,7 +579,6 @@ class ImprovedSearchService:
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price_selectors = [
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'.price',
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'[data-testid="price"]',
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'[itemprop="price"]',
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'.product-price',
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'.a-price .a-offscreen',
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'.a-price-whole',
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@@ -563,7 +614,6 @@ class ImprovedSearchService:
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# Fallback to standard price selectors
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# Collect ALL valid prices and return the lowest (usually the promotional price)
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all_prices = []
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for selector in price_selectors:
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@@ -573,14 +623,10 @@ class ImprovedSearchService:
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# Skip if element is strikethrough (old price)
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try:
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parent_html = await elem.evaluate('el => el.parentElement.outerHTML')
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# Check for strikethrough in parent
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if 'text-decoration: line-through' in parent_html or 'text-decoration-line: line-through' in parent_html:
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logger.debug(f" Skipping strikethrough price from {selector}")
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continue
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# Also check the element itself
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elem_style = await elem.evaluate('el => window.getComputedStyle(el).textDecoration')
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if 'line-through' in elem_style:
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logger.debug(f" Skipping element with line-through style")
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continue
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except:
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pass
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@@ -603,7 +649,7 @@ class ImprovedSearchService:
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logger.debug(f" Error with selector {selector}: {e}")
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continue
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# Return the LOWEST price found (promotional price is usually lower)
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# Return the LOWEST price found
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if all_prices:
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lowest_price = min(all_prices)
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logger.debug(f"Selected lowest price from {len(all_prices)} candidates: {lowest_price}€")
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@@ -15,6 +15,7 @@ services:
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- BROWSERLESS_URL=ws://browserless:3000
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- LOG_LEVEL=INFO
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- CORS_ORIGINS=*
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- OPENROUTER_API_KEY=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
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depends_on:
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db:
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condition: service_healthy
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@@ -0,0 +1,91 @@
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import asyncio
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import logging
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import sys
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from playwright.async_api import async_playwright
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from app.services.ai_price_extractor import AIPriceExtractor
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from app.services.improved_search_service import ImprovedSearchService
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from app.core.search_config import SITE_CONFIGS
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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async def verify_bm():
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=True)
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page = await browser.new_page()
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# 1. Perform Search to get a product URL
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logger.info("--- Step 1: Searching for 'Chaise pliante pu creme' on B&M ---")
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# Use specific search to find the problematic product
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search_url = "https://bmstores.fr/module/ambjolisearch/jolisearch?s=Chaise+pliante+pu+creme"
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await page.goto(search_url)
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await page.wait_for_load_state("networkidle")
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# Take screenshot of search results
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await page.screenshot(path="bm_search_results.png")
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logger.info("Screenshot saved: bm_search_results.png")
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# Get first product link
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product_link = await page.get_attribute("a.thumbnail.product-thumbnail", "href")
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if not product_link:
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logger.error("No product found in search")
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return
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if not product_link.startswith("http"):
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product_link = "https://www.bmstores.fr" + product_link
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logger.info(f"Testing Product URL: {product_link}")
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# 2. Go to Product Page
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await page.goto(product_link)
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await page.wait_for_load_state("networkidle")
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await page.screenshot(path="bm_product_page.png")
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logger.info("Screenshot saved: bm_product_page.png")
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# 3. Dump HTML snippet (price area)
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content = await page.content()
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logger.info(f"HTML Content Length: {len(content)}")
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# Check for 12.95
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if "12,95" in content or "12.95" in content:
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logger.info("✅ Price 12.95 found in raw HTML")
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else:
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logger.warning("❌ Price 12.95 NOT found in raw HTML")
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# 4. Test JSON-LD
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logger.info("\n--- Step 2: Testing JSON-LD ---")
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json_ld_scripts = await page.query_selector_all('script[type="application/ld+json"]')
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for i, script in enumerate(json_ld_scripts):
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text = await script.inner_text()
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logger.info(f"JSON-LD #{i}: {text[:500]}...")
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# 5. Test CSS Selectors
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logger.info("\n--- Step 3: Testing CSS Selectors ---")
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selectors = [
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'.price-current', '.prix-actuel', '.sale-price', '.promo-price',
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'.price', '[data-testid="price"]', '[itemprop="price"]', '.product-price',
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'.current-price-value'
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]
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for sel in selectors:
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elements = await page.query_selector_all(sel)
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for el in elements:
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text = await el.inner_text()
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logger.info(f"Selector '{sel}': {text.strip()}")
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# 6. Test AI Extraction
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logger.info("\n--- Step 4: Testing AI Extraction (Gemma 3) ---")
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title = await page.title()
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# Ensure API key is available
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import os
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if not os.getenv("OPENROUTER_API_KEY"):
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logger.warning("OPENROUTER_API_KEY not set in env, AI might fail")
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ai_price = await AIPriceExtractor.extract_price(content, title)
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logger.info(f"AI Extracted Price: {ai_price}")
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await browser.close()
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if __name__ == "__main__":
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asyncio.run(verify_bm())
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