Browser-based document pipeline runs PDF OCR in 30 lines with no server needed

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A developer tutorial published on September 3, 2026 demonstrates how to build a fully client-side document processing pipeline using the @stabrise/scaledp library at version 0.1.1. The pipeline converts PDF pages to images and runs optical character recognition entirely in the browser using WebAssembly and ONNX Runtime, requiring no server, API key, or file upload. Only one core package is a hard dependency, with ML engine packages installed optionally based on what the pipeline actually uses, keeping bundle sizes lean. Configuration requires a single configure() call where developers explicitly set asset URLs and caching preferences, with IndexedDB caching available to speed up repeat visits by storing model weights locally. The pipeline accepts various input formats including File, Blob, and URL, and returns one structured row per PDF page containing recognized text and word-level bounding boxes.

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