Filter URLs with AI-powered robots.txt compliance & source verification

URL Officer - Respect robots.txt and Avoid Undesirable Sources

🎬 Overview Version : 1.0

The URL Officer workflow automates the filtering of URLs by checking them against a database of forbidden sources and the rules defined in robots.txt files. It proactively respects robot exclusion protocols and user-defined banned sources to aid in lawful and ethical web automation. Designed primarily as a sub-workflow, it serves automation pipelines with robust URL validation to avoid undesirable or restricted sources.

✨ Features

- Dual-layer URL Filtering: Checks URLs against a manually maintained forbidden sources list and robots.txt restrictions. - Automated robots.txt Retrieval & Update: Automatically fetches and updates robots.txt content for new or outdated sources (older than 3 days). - AI-backed robots.txt Interpretation: Uses AI models to interpret robots.txt comments and restrictions, ensuring nuanced compliance. - Configurable User-Agent Identification: Allows customization of User-Agent strings that are checked against robots.txt directives. - Sub-Workflow Ready: Easily integrates as a sub-workflow for link validation in larger automation pipelines. - Multi-Model AI Support: Supports mistral, groq, and gemini AI models for enhanced robots.txt compliance checks. - Detailed Diagnostic Outputs: Returns comprehensive link allowance statuses and metadata for use in downstream processing. - Database Integration: Utilizes PostgreSQL to store and manage robots.txt content and banned source lists.

👤 Who is this for?

Ideal for developers, data engineers, researchers, or businesses implementing web crawlers, scrapers, or any automation that processes URLs. This workflow helps your compliance with source restrictions and avoids content from blacklisted sites, reducing legal exposure and promoting ethical data use.

💡 What problem does this solve?