diff --git a/cognee/tasks/web_scraper/models.py b/cognee/tasks/web_scraper/models.py
index 8d5f32f43..12ac91166 100644
--- a/cognee/tasks/web_scraper/models.py
+++ b/cognee/tasks/web_scraper/models.py
@@ -2,8 +2,10 @@ from cognee.infrastructure.engine.models import DataPoint
 from typing import Optional, Dict, Any, List
 from datetime import datetime
 
+
 class WebPage(DataPoint):
     """Represents a scraped web page with metadata"""
+
     url: str
     title: Optional[str]
     content: str
@@ -16,8 +18,10 @@ class WebPage(DataPoint):
     extraction_rules: Dict[str, Any]  # CSS selectors, XPath rules used
     metadata: dict = {"index_fields": ["url", "title", "scraped_at"]}
 
+
 class WebSite(DataPoint):
     """Represents a website or domain being scraped"""
+
     domain: str
     base_url: str
     robots_txt: Optional[str]
@@ -27,13 +31,14 @@ class WebSite(DataPoint):
     scraping_config: Dict[str, Any]
     metadata: dict = {"index_fields": ["domain", "base_url"]}
 
+
 class ScrapingJob(DataPoint):
     """Represents a scraping job configuration"""
+
     job_name: str
     urls: List[str]
-    scraping_rules: Dict[str, Any]
     schedule: Optional[str]  # Cron-like schedule for recurring scrapes
     status: str  # "active", "paused", "completed", "failed"
     last_run: Optional[datetime]
     next_run: Optional[datetime]
-    metadata: dict = {"index_fields": ["job_name", "status"]}
\ No newline at end of file
+    metadata: dict = {"index_fields": ["job_name", "status"]}
diff --git a/cognee/tasks/web_scraper/utils.py b/cognee/tasks/web_scraper/utils.py
new file mode 100644
index 000000000..bcf12ac32
--- /dev/null
+++ b/cognee/tasks/web_scraper/utils.py
@@ -0,0 +1,39 @@
+from tavily import AsyncTavilyClient
+from bs4 import BeautifulSoup
+import os
+import requests
+from typing import Dict, Any, List, Union
+
+
+async def fetch_page_content(urls: Union[str, List[str]], extraction_rules: Dict[str, Any]) -> str:
+    if os.getenv("TAVILY_API_KEY") is not None:
+        return await fetch_with_tavily(urls)
+    else:
+        return await fetch_with_bs4(urls, extraction_rules)
+
+
+async def fetch_with_tavily(urls: Union[str, List[str]]) -> Dict[str, str]:
+    client = AsyncTavilyClient()
+    results = await client.extract(urls, include_images=False)
+    result_dict = {}
+    for result in results["results"]:
+        result_dict[result["url"]] = result["raw_content"]
+    return result_dict
+
+
+async def fetch_with_bs4(urls: Union[str,List[str]], extraction_rules: Dict) -> Dict[str]:
+    result_dict = {}
+    if isinstance(urls,str):
+        urls = [urls]
+    for url in urls:
+        response = requests.get(url, headers={"User-Agent": "Cognee-Scraper"})
+        response.raise_for_status()
+
+        soup = BeautifulSoup(response.text, "html.parser")
+        extracted_data = ""
+
+        for field, selector in extraction_rules.items():
+            element = soup.select_one(selector)
+            extracted_data += element.get_text(strip=True) if element else ""
+
+    return result_dict