vector-crawl-engine

An enterprise-grade, high-throughput Python engine designed for pre-rendering client-side web pages, optimizing vector content extraction, and calculating semantic density for Generative Engine Optimization (GEO).

Vector Crawl Engine ⚙️ Vector-First Content Extraction & Indexation Parser

Overview

Vector Crawl Engine is a high-performance, asynchronous Python engine engineered to eliminate client-side rendering bottlenecks, calculate semantic vector density, and validate JSON-LD schemas for modern Generative Engine Optimization (GEO) pipelines.

Built for technical SEO engineers and enterprise teams, it provides real-time insights into crawler latency, rendering friction, and entity extraction efficiency.

Key Features

• Async Edge Execution: High-throughput concurrent crawling with strict semaphore limits.
• Information Density Scoring: Mathematical calculation of text-to-code ratios for AI vector readiness.
• Schema Validation: Automated parsing of JSON-LD, TechArticle, and structured microdata.
• Pydantic Data Models: Strict typing for robust integration into data pipelines.

Installation

# Clone the repository
git clone [https://github.com/YOUR_USERNAME/vector-crawl-engine.git](https://github.com/YOUR_USERNAME/vector-crawl-engine.git)

# Navigate to project directory
cd vector-crawl-engine

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt