Integrating BytesFlows into LangChain / LlamaIndex RAG Tools
Ensure your vector retrieval tool fetches fresh HTML without triggering CAPTCHAs or 403 Forbidden errors.
example.py
import requests
def retrieve_live_context(query_url: str) -> str:
# Use residential rotating IP to guarantee high freshness and no IP blocks
proxies = {
"http": "http://user-youraccount-rotate:password@proxy.bytesflows.com:31112",
"https": "http://user-youraccount-rotate:password@proxy.bytesflows.com:31112"
}
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"}
resp = requests.get(query_url, proxies=proxies, headers=headers, timeout=5)
resp.raise_for_status()
return resp.text
html_content = retrieve_live_context("https://example.com/latest-market-update")
print(f"Retrieved {len(html_content)} characters for RAG embedding.")