Build a Self-Scaling OCR Pipeline with Qwen 3.5 and Kubernetes

This project offers a comprehensive guide to building a production-ready OCR pipeline. It leverages the capabilities of Qwen 3.5 for accurate text recognition and extraction tasks. The architecture

This project offers a comprehensive guide to building a production-ready OCR pipeline. It leverages the capabilities of Qwen 3.5 for accurate text recognition and extraction tasks. The architecture utilizes Kubernetes to ensure the system can scale automatically based on demand. Users will learn how to containerize the application components for efficient deployment. The tutorial covers the integration of the machine learning model with orchestration tools. It addresses common challenges in deploying OCR systems at scale in cloud environments. The repository includes configuration files and code examples to facilitate immediate implementation. This resource is ideal for engineers looking to automate document processing workflows reliably.