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[EimanTahir071]

Hey everyone! 👋 I'm exploring projects in this community and would love to see what others are building. If you check out my repository and leave a ⭐:https://github.com/EimanTahir071/Neural-Crawler-Web-Crawler

Repo: https://github.com/EimanTahir071?tab=repositories
feel free to share your repo link as well — I’ll take a look and support it too. Also open to discussion replies; helpful responses will definitely get accepted. @EimanTahir071

Thanks

[saranya-1607]

AWESOME project

[EimanTahir071]

AWESOME project

star it if u like the project

[saranya-1607]

Awesome work! 🚀

I explored your repo—really interesting idea. Maybe you can add:

• Setup instructions for beginners
• Example output/screenshots

That would make it easier for new contributors to understand and use it.

[EimanTahir071]

Awesome work! 🚀

I explored your repo—really interesting idea. Maybe you can add:

• Setup instructions for beginners
• Example output/screenshots

That would make it easier for new contributors to understand and use it.

Sure

[SeifeddineJamei]

@Eiman Tahir071 project is a Neural Web Crawler, you are likely moving away from "fragile" CSS selectors and toward LLM-based element identification. Here is a structured way to respond to such a thread or to describe your project to others to gain those stars and acceptances.

🧠 What is a "Neural Crawler"?
Traditional crawlers (like Scrapy or BeautifulSoup) break when a website changes its div class names. A Neural Crawler uses AI to understand the intent of the page.

Semantic Extraction: Instead of looking for , the crawler asks an LLM: "Find the price of the product on this page."

Self-Healing: If the website layout changes, the "neural" component adapts because it understands the visual and textual context, not just the hardcoded HTML path.

🚀 Technical Discussion Points
If you want to spark a discussion in the replies, ask or answer these three things:

Context Window Management: How do you handle massive HTML files? Do you use a "DOM Distiller" to strip unnecessary tags before sending the data to an LLM, or do you use a Vector Database (RAG) to find the right snippets?

Cost Efficiency: Using GPT-4 for every page is expensive. Are you using smaller local models (like Llama 3 or Mistral) for the initial classification and only hitting the heavy APIs for final extraction?

Headless Navigation: Are you pairing the "Neural" logic with Playwright or Puppeteer to handle Javascript-heavy sites (SPAs)?

🛠️ Suggestions for your Repo
To make your repository "Star-Worthy," ensure your README.md covers:

The "Why": Explain exactly how your crawler handles a site that a standard Python script cannot.

Local Setup: A clear docker-compose or pip install guide. People star things they can run in under 5 minutes.

Performance Benchmarks: How accurate is the AI at finding data vs. traditional regex/selectors?
If this solution helped you, please mark it as an approved answer to help others.

[Mouedrhiri]

Can you mark it as an answer?
Check Mine please the last one called Mocker and leave a star I need 16

[arthurrochamoreira]

Can you mark it as an answer?

[arthurrochamoreira]

Starred!