Web Scraping with GLM: Text and Visual Data Extraction

GLM-5.3 and multimodal GLM-5.3-Flash can support more resilient web data extraction by using prompts and structured JSON outputs instead of brittle CSS selectors or XPath rules, with the Flash model additionally analyzing page screenshots for visual details. The workflow described uses Bright Data’s Web Unlocker API to retrieve JavaScript-rendered pages while handling CAPTCHAs, fingerprinting, IP rotation, rate limits, and other anti-bot measures, returning either token-efficient Markdown for text extraction or screenshots for vision-based extraction. In a Python example targeting an IKEA product page, the API delivers page content, GLM is accessed through Z.ai’s OpenAI-compatible interface, and a Pydantic schema defines, validates, and saves extracted product fields as JSON. The text-based approach with GLM-5.3 can capture detailed page information such as pricing, materials, reviews, and product metadata, while the screenshot-based GLM-5.3-Flash workflow can identify visible attributes such as promotional badges, delivery options, and physical product characteristics.

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