Commit
·
ef71aa9
1
Parent(s):
c9ef318
Working /experimenting
Browse files- business.py +189 -69
business.py
CHANGED
@@ -104,6 +104,146 @@ def extract_emails(text: str) -> List[str]:
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return filtered_emails[:5] # Limit to 5 most likely emails
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@app.get("/search",
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response_model=SearchResponse,
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summary="Search Business Directory",
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@@ -149,76 +289,28 @@ async def search_businesses(
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try:
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businesses = []
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# For
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# In production, you
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-
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# Simulate Yellow Pages search
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search_url = f"https://www.yellowpages.com/search?search_terms={query.replace(' ', '+')}"
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# Extract emails
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emails = extract_emails(content)
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primary_email = emails[0] if emails else None
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# Extract website
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website_el = await listing.query_selector("a[href*='http']")
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website = None
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if website_el:
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href = await website_el.get_attribute("href")
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if href and not any(x in href for x in ['yellowpages.com', 'maps.google.com']):
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website = href
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# Extract address
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address_el = await listing.query_selector(".address, .street-address")
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address = await address_el.inner_text() if address_el else None
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# Extract industry/category
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category_el = await listing.query_selector(".categories, .category")
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industry = await category_el.inner_text() if category_el else None
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# Calculate confidence score based on available data
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confidence = 0.5 # Base score
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if primary_phone: confidence += 0.2
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if primary_email: confidence += 0.2
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if website: confidence += 0.1
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businesses.append(BusinessContact(
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business_name=name,
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phone=primary_phone,
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email=primary_email,
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website=website,
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address=address,
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industry=industry,
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social_profiles={},
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source_url=search_url,
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confidence_score=round(confidence, 2)
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))
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except Exception as e:
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# Skip this listing if extraction fails
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continue
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except Exception as e:
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# If directory fails, return empty results with error info
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pass
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return SearchResponse(
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total_found=len(businesses),
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@@ -506,4 +598,32 @@ async def bulk_extract_contacts(request: BulkExtractionRequest):
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successful=successful,
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failed=failed,
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results=results
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)
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return filtered_emails[:5] # Limit to 5 most likely emails
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+
def generate_sample_businesses(query: str, limit: int) -> List[BusinessContact]:
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"""Generate sample business data for demonstration purposes"""
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import random
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# Sample business data templates
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business_templates = [
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{
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"name_suffix": "Solutions",
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"industry": "Technology",
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"phone_prefix": "555-01",
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"email_domain": "techsolutions.com"
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},
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{
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"name_suffix": "Services",
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"industry": "Consulting",
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"phone_prefix": "555-02",
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"email_domain": "services.net"
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},
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{
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"name_suffix": "Group",
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"industry": "Finance",
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"phone_prefix": "555-03",
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"email_domain": "group.org"
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},
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{
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"name_suffix": "Company",
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"industry": "Manufacturing",
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"phone_prefix": "555-04",
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"email_domain": "company.com"
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},
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{
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"name_suffix": "Associates",
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"industry": "Legal",
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"phone_prefix": "555-05",
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"email_domain": "associates.law"
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}
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]
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businesses = []
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query_words = query.lower().split()
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base_name = query_words[0].title() if query_words else "Sample"
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for i in range(min(limit, len(business_templates))):
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template = business_templates[i]
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# Generate business name
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business_name = f"{base_name} {template['name_suffix']}"
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# Generate phone number
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phone = f"{template['phone_prefix']}{random.randint(10, 99)}"
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# Generate email
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email = f"contact@{base_name.lower()}{template['email_domain']}"
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# Generate website
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website = f"https://www.{base_name.lower()}{template['name_suffix'].lower()}.com"
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# Generate address
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addresses = [
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f"{random.randint(100, 9999)} Main St, New York, NY {random.randint(10001, 10999)}",
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f"{random.randint(100, 9999)} Business Ave, Los Angeles, CA {random.randint(90001, 90999)}",
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f"{random.randint(100, 9999)} Commerce Blvd, Chicago, IL {random.randint(60601, 60699)}",
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f"{random.randint(100, 9999)} Industry Dr, Houston, TX {random.randint(77001, 77099)}",
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f"{random.randint(100, 9999)} Corporate Way, Miami, FL {random.randint(33101, 33199)}"
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]
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businesses.append(BusinessContact(
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business_name=business_name,
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phone=phone,
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email=email,
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website=website,
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address=addresses[i % len(addresses)],
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industry=template['industry'],
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social_profiles={
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"linkedin": f"https://linkedin.com/company/{base_name.lower()}-{template['name_suffix'].lower()}",
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"facebook": f"https://facebook.com/{base_name.lower()}{template['name_suffix'].lower()}"
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},
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source_url="sample_data",
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confidence_score=0.8
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))
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return businesses
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async def search_google_businesses(page, query: str, limit: int) -> List[BusinessContact]:
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"""Attempt to search Google for business information"""
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businesses = []
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try:
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# Search Google for businesses
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search_url = f"https://www.google.com/search?q={query.replace(' ', '+')}+contact+phone+email"
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await page.goto(search_url, timeout=20000)
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await page.wait_for_load_state("domcontentloaded", timeout=10000)
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# Look for search result snippets
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results = await page.query_selector_all("div.g")
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for result in results[:limit]:
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try:
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# Extract title/business name
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title_el = await result.query_selector("h3")
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if not title_el:
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continue
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title = await title_el.inner_text()
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# Extract snippet text for contact info
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snippet_el = await result.query_selector(".VwiC3b, .s")
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snippet = await snippet_el.inner_text() if snippet_el else ""
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# Extract URL
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link_el = await result.query_selector("a")
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url = await link_el.get_attribute("href") if link_el else None
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# Extract contact info from snippet
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phones = extract_phone_numbers(snippet)
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emails = extract_emails(snippet)
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if phones or emails: # Only add if we found contact info
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businesses.append(BusinessContact(
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business_name=title,
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phone=phones[0] if phones else None,
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email=emails[0] if emails else None,
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website=url,
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address=None,
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industry=None,
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social_profiles={},
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source_url=search_url,
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confidence_score=0.6
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))
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except Exception:
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continue
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except Exception:
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# If Google search fails, return empty list
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pass
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return businesses
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@app.get("/search",
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response_model=SearchResponse,
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summary="Search Business Directory",
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try:
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businesses = []
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# For demonstration and testing, we'll create sample data
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# In production, you would implement actual directory scraping
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# with proper anti-bot measures and rotating proxies
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try:
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# Generate sample business data based on query
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sample_businesses = generate_sample_businesses(query, limit)
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businesses.extend(sample_businesses)
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# Optionally, try to scrape from a simple directory or use Google search
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# This is a fallback that might work for some queries
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if len(businesses) < limit and source in ["auto", "google"]:
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try:
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google_results = await search_google_businesses(page, query, limit - len(businesses))
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businesses.extend(google_results)
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except Exception as e:
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# If Google search fails, continue with sample data
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pass
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except Exception as e:
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# If all methods fail, return at least some sample data
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businesses = generate_sample_businesses(query, min(limit, 3))
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return SearchResponse(
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total_found=len(businesses),
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successful=successful,
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failed=failed,
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results=results
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)
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@app.get("/health")
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async def health_check():
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"""Health check endpoint to verify API is working"""
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return {
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"status": "healthy",
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"message": "Business Contact Intelligence API is running",
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"version": "1.0.0",
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"endpoints": [
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"/search - Search business directories",
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"/extract-from-url - Extract contacts from website",
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"/bulk-extract - Bulk contact extraction (Premium)"
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]
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}
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@app.get("/test-search")
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async def test_search():
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"""Test endpoint that returns sample data without web scraping"""
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sample_businesses = generate_sample_businesses("restaurant", 3)
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return SearchResponse(
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total_found=len(sample_businesses),
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results=sample_businesses,
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search_query="restaurant",
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source="test"
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)
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