Draft Issue: Please provide further details

[linkpellow]

This issue was created as a draft. Please provide additional information or context to help refine and complete this issue.
I just pulled this repo https://github.com/ScrapeGraphAI/Scrapegraph-ai what does this do? Can I scrape lead emails and phone numbers with this?

[dosubot]

Hi @linkpellow! I'm Dosu and I’m helping the Scrapegraph-ai team.

Scrapegraph-ai is an open-source Python library that lets you scrape content from websites or local HTML files using large language models (LLMs) and natural language prompts. You can tell it what to extract (like articles, lists, or specific fields) just by describing your needs in plain English, and you can optionally define a schema to structure the output (for example, using Pydantic models) example.

There’s no built-in or dedicated workflow specifically for scraping emails or phone numbers, but you can absolutely do this by crafting the right prompt and (optionally) a schema. For example, you could use the SmartScraperGraph workflow with a prompt like:
Extract all email addresses and phone numbers from this page.
If you want structured output, you could define a schema like:

class Lead(BaseModel):
    email: Optional[str]
    phone: Optional[str]

class Leads(BaseModel):
    leads: List[Lead]

and set your prompt to:
Extract all leads with their email addresses and phone numbers from this page.

The extraction is entirely LLM- and prompt-driven—there are no hard-coded or regex-based detectors for emails or phones, so results depend on how you phrase your prompt and the quality of the underlying LLM example.

Be mindful of legal and ethical considerations when scraping personal contact information, as privacy and compliance rules may apply.

You can find more about usage and examples in the examples directory and the docs.

To reply, just mention @dosu.

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