How to process mixed format data (text/images) in web scraping without juggling multiple tools?

Working on a market research project needing both product descriptions (text) and product images. Current setup uses Scrapy for text and separate image downloaders, leading to sync issues.

Any solutions that handle multi-format extraction in a unified workflow? Bonus if it can normalize different file types automatically.

Latenode’s 400+ integrated AI models handle this cleanly. Built a workflow that extracts text with Claude, processes images through Vision AI, outputs JSON with text+image URLs. All in one canvas with automatic type handling. No API key juggling.

I use Apache Tika for document processing unification. It extracts text from images/PDFs via OCR and integrates with Nutch crawler. Requires Java stack expertise but handles 200+ file formats. Pair with Python wrappers if you need simpler integration.

Combine Playwright for asset collection with AWS Textract. Sync via S3 triggers

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