Hey everyone,
I’m working on extracting contact emails from a bunch of company websites. I have a list of URLs and need to find email addresses on each site. The o3 model does a great job when I manually paste 20-30 URLs and ask it to check those websites for emails.
Using the OpenAI API isn’t ideal because it can’t browse websites directly. I’d have to scrape all the content first which gets expensive. I tried some Python scripts but they often grab the wrong emails or miss them completely.
I’m wondering if anyone has tried using headless browsers to automate this process? Like having the browser visit ChatGPT and submit the URL search requests automatically through the o3 model?
Has anyone built something similar? I know OpenAI probably has detection systems for this kind of automation. Any suggestions on how to make it work reliably?
Thanks for any help!
puppeteer is good, but yeah, those rate limits can be a pain. i used selenium in stealth mode last month and got blocked after just 50 hits. might be worth looking into residential proxies with rotating user agents, or maybe trying playwright with some random delays to avoid detection.
Been there, done that - headless browsers don’t scale for this. OpenAI’s gotten smart about blocking automation. They track everything: mouse movements, typing patterns, even your screen size. I wasted weeks tweaking my setup and kept getting shadowbanned. What actually worked? I built a lightweight scraper with regex patterns for common email formats, then hit the API only when my parser couldn’t handle something. Yeah, the API costs more upfront, but factor in dev time and all the reliability headaches with browser automation - it’s actually cheaper. The o3 model on their web interface looks tempting because it’s so accurate, but you’ll spend forever fighting their detection. Go hybrid instead of betting everything on browser automation.
I tried this exact thing about six months ago for lead gen. Used Chrome DevTools Protocol with custom fingerprinting to dodge bot detection. Rate limiting isn’t the real problem - OpenAI’s session management goes nuts if you’re hammering their web interface with automated requests. Hit around 100-150 requests in a day and those verification challenges started popping up constantly. My workaround was running multiple instances with different residential IPs and keeping sessions alive by mixing in real human-like interactions between automated requests. Success rate tanked to maybe 60% after a few hours though. Honestly? Ended up being way more hassle than just building a proper email extraction pipeline with regex and WHOIS lookups. The o3 model crushes it for accuracy, but the automation overhead makes it useless for bulk processing.
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