Gene Library Courses Download Pricing Contact Sign in
Gene Library
GENE-WEBACCESS Data Integration

GENE-WebAccess: Fetch and Process Web Content in AI Workflows

By Feluda.ai team

Overview

GENE-WebAccess is a web content retrieval gene that provides a straightforward way for AI agents and automated workflows to fetch and process content from the internet. It performs HTTP GET requests to retrieve web pages, text files, or API responses, stores the results in the Feluda dataspace, and enables chunk-based reading for efficient handling of large content.

This Gene is essential for any workflow that needs to incorporate external data from websites, APIs, or public content without manual intervention.

Key Capabilities

  • Fetch and Store: Performs an HTTP GET request to a specified URL, stores the complete response in the Feluda dataspace, and returns a unique result_id and HTTP status code.
  • Read in Chunks: Retrieves stored content using the result_id from the fetch action, supports configurable chunk sizes (start position and length), and provides pagination helpers: next_start, total_chars, and has_more.
  • Flexible Output Formats: Returns content in either Raw format (preserves original HTML or text) or Markdown format (converts content to clean, readable Markdown).
  • Configurable User-Agent: Customize the User-Agent string sent with each request to properly identify your automation and comply with website policies.

How It Works

The gene provides a single tool, webAccessTool, which can be controlled with an action parameter to access the different capabilities. No API keys are required.

Action Description API Key Required
fetch Performs an HTTP GET request and stores the result. No
read_chunk Reads a previously stored result in chunks. No

Use in Feluda Flows

GENE-WebAccess is a valuable addition to any data integration or automation workflow in Feluda Flows.

  • Automatically fetch API data, documentation, or public content at scheduled intervals.
  • Retrieve and analyze web content for changes and generate reports.
  • Gather information from multiple web sources for research and knowledge base population.
  • Fetch external datasets and prepare them for AI model training.

Who Should Use GENE-WebAccess

  • Data Engineers: For building automated data collection pipelines.
  • AI Developers: For preparing training data from web sources.
  • Researchers: For automating research tasks and gathering information.
  • Operations Teams: For monitoring web content changes and generating alerts.

Important Limitations

  • GET-Only Requests: The Gene only performs HTTP GET requests. It cannot submit forms, handle POST requests, or interact with APIs that require other HTTP methods.
  • No JavaScript Execution: The Gene fetches raw HTML content without executing JavaScript, so single-page applications and JavaScript-rendered content will return incomplete results.
  • No DOM Rendering: There's no browser environment involved. Content that relies on client-side rendering will not be captured.
  • No Interactive Flows: The Gene cannot handle login flows, captcha challenges, cookies, or interactive browser-based processes.

For interactive web automation that requires JavaScript execution, DOM manipulation, or user interaction, consider using the Feluda Browser Automation Gene instead.

Getting Started

  1. Deploy GENE-WebAccess to Feluda.
  2. Configure settings (optional): Set User-Agent and Response Type.
  3. Call the Gene with action=fetch and your target URL.
  4. Retrieve results with action=read_chunk using the result_id.
  5. Process the data in your AI automation workflows.

Resources

Media

webaccess-feluda.png
webaccess-feluda.png

Frequently Asked Questions

Do I need any API keys to use GENE-WebAccess?
No. GENE-WebAccess performs standard HTTP GET requests to retrieve web content and requires no API keys or authentication tokens. You can start using the gene immediately after deployment.
Can the Web Access Gene handle JavaScript-heavy websites?
No. The Gene performs static HTTP GET requests without executing JavaScript or rendering a DOM. JavaScript-dependent pages (single-page applications, infinite-scroll sites) may return incomplete content. For interactive browsing, use the Feluda Browser Automation Gene instead.
How are large web pages handled?
The Gene stores the full response in the Feluda dataspace and provides chunk-based reading. You can retrieve content in configurable chunks (default 1000 characters), with pagination helpers (next_start, total_chars, has_more) for easy navigation.
What content formats can the Gene retrieve?
The Gene can retrieve any content accessible via HTTP GET, including HTML pages, text files, CSV files, JSON data, and markdown documents. The response can be returned in either raw format or converted to clean Markdown.
What settings can I configure?
You can configure two settings: WebAccess.UserAgent (customize the User-Agent string) and WebAccess.ResponseType (choose between 'Raw' HTML or 'Markdown' conversion). These settings help you adapt to different websites and processing needs.