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In this post, I explore how modern web apps like RAGflow handle long-running tasks (such as OCR or keyword extraction) without relying on time-limited HTTP API methods. Instead, tasks are processed in the background by worker processes, with progress updates communicated to the frontend via Redis. I demonstrate this design with a simple app built using FastAPI, Vue 3, and Redis, where tasks are submitted, processed in the background, and their statuses are periodically updated on the frontend...
Private LLM Integration with RAGFlow: A Step-by-Step Guide
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If you’ve found your way here, you’re probably already excited about the potential of the RAGFlow project and eager to see it in action. I was in the same position, so I delved into the codebase to see how it could work with custom large language models (LLMs). This post will walk you through my findings and show you how to get RAGFlow running with your own LLM.
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Predictive underwriting is revolutionizing the insurance industry by harnessing data analytics and machine learning. This innovative approach streamlines risk assessment, enhances customer experience, and tackles critical challenges like non-disclosure. By analyzing vast amounts of data from various sources, including wearable devices, insurers can make faster, more accurate decisions. This leads to quicker approvals, fairer pricing, and personalized products. As the insurance landscape evolv...
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A Singapore PR Application Profile Evaluator built with Vue.js
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