YouTube AI Scraping Agent

YouTube AI Scraping Agent is listed in the CV as a Python project using Apify, OpenRouter, tokenization, and embeddings.

AI-assisted scraping workflows need to collect content, prepare it for model consumption, and structure the output so it can be searched, summarized, or analyzed.

I worked on the automation and AI processing flow, using scraping tools and model-routing infrastructure to process content.

• Python
• Apify
• OpenRouter
• Tokenization
• Embeddings

• Used Apify for scraping-oriented workflow support.
• Used OpenRouter for model access flexibility.
• Prepared content through tokenization and embedding-oriented processing.

• Keeping scraped content structured enough for downstream AI tasks.
• Managing token limits and model input preparation.
• Designing the project so it can be extended with retrieval or summarization features.

The project shows applied AI automation experience around scraping, language model workflows, and content processing.

Useful AI agents depend on reliable data preparation. The quality of scraping, chunking, and embeddings shapes the quality of the final model behavior.