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RAG Web Browser

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RAG Web Browser

RAG Web Browser

RAG Web Browser is a lightweight Python Actor that fetches any URL or search query, strips ads and clutter, and extracts clean, readable text from web pages. It returns structured, LLM-ready content optimized for retrieval-augmented generation pipelines and AI-powered applications.

Pricing

from $1.00 / 1,000 results

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0.0

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Developer

Biddut Hossain

Biddut Hossain

Maintained by Community

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0

Bookmarked

2

Total users

1

Monthly active users

3 days ago

Last modified

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RAG Web Browser is a lightweight Python Actor that fetches any URL or search query, strips ads and clutter, and extracts clean, readable text from web pages. It returns structured, LLM-ready content optimized for retrieval-augmented pipelines and AI chat apps needing accurate real-time context.

✨ Features

  • Accepts a direct URL or a plain text search query
  • Strips scripts, nav bars, footers, ads, and other noise
  • Returns clean, structured JSON output (title + text + char count)
  • Configurable character limit and CSS selectors to remove
  • Built on httpx + BeautifulSoup for fast, reliable scraping

📥 Input

FieldTypeDescriptionDefault
querystringA URL or search query(required)
maxCharsintegerMax characters of text to return5000
removeSelectorsarrayCSS selectors to strip before extraction["script","style","nav","footer","header","aside","iframe","noscript"]

Example input

{
"query": "https://en.wikipedia.org/wiki/Retrieval-augmented_generation",
"maxChars": 3000
}

📤 Output

Each run pushes one item to the dataset:

{
"query": "https://example.com",
"url": "https://example.com",
"title": "Example Domain",
"text": "This domain is for use in illustrative examples...",
"charCount": 214
}

🚀 Usage

  1. Set your query input (URL or search term).
  2. Run the Actor.
  3. Retrieve extracted text from the Dataset tab, or via the Apify API.

🧠 Use Cases

  • Feeding live web content into LLM prompts (RAG pipelines)
  • Building AI chatbots with up-to-date web knowledge
  • Content extraction and summarization pipelines
  • Lightweight alternative to full-page scrapers when only text is needed

🛠 Built With