📄 中文摘要
隐私已成为一项基本人权，尤其是在医疗数据方面。传统上，进行健康报告的语义分析需要将敏感数据发送到云服务提供商，如 OpenAI 或 Anthropic。然而，如果模型可以直接在浏览器中运行呢？本教程将深入探讨边缘人工智能和隐私优先应用的领域，构建一个完全离线的健康报告解释器，使用 WebLLM、WASM 和 React。通过利用 WebGPU，能够在客户端硬件上直接运行一个 7B 参数的模型（如 Llama-3 或 Mistral），确保医疗历史的任何字节都不会离开用户的设备。
告别服务器成本：在 Chrome 中运行 7B LLM 进行私密健康分析 🚀
📄 English Summary
Say Goodbye to Server Costs: Run a 7B LLM in Chrome for Private Health Analytics 🚀
Privacy is increasingly recognized as a fundamental human right, particularly concerning medical data. Traditionally, performing semantic analysis on health reports required sending sensitive information to cloud providers like OpenAI or Anthropic. This tutorial explores the realm of Edge AI and Privacy-First applications by building a fully offline health report interpreter using WebLLM, WASM, and React. By leveraging WebGPU, it enables the execution of a 7B parameter model (such as Llama-3 or Mistral) directly on the client’s hardware, ensuring that no byte of medical history ever leaves the user's device.