Osllm.AI

As part of my PhD research and dissertation, I am currently developing advanced open-source applications that focus on optimizing information extraction and ensuring the safety of large language models (LLMs). My contributions include: Indox for Retrieval Augmentation: A cutting-edge, open-source application designed to simplify the extraction of relevant data from various document formats, including text files, PDFs, HTML, Markdown, and LaTeX. Indox efficiently handles both structured and unstructured data with precision. IndoxJudge: A free, open-source tool created specifically for evaluating LLMs and ensuring their safety. It provides essential metrics to assess model performance and reliability. Phoenix: A multi-platform, open-source application built with Qt QML. It features a chatbot interface that interacts with documents locally, eliminating the need for an internet connection or a GPU. Phoenix leverages Indox and IndoxJudge to deliver high accuracy and eliminate hallucinations, ensuring reliable results, particularly in the healthcare field. Phoenix_CLI: A versatile, multi-platform, open-source command-line tool that operates on Windows, Linux, and Mac. It supports running LLaMA models with up to eight concurrent tasks using advanced multithreading techniques, optimizing performance and efficiency. All these tools are open source and completely free, reflecting my commitment to accessibility and community-driven innovation. These projects represent the core of my PhD work, contributing to both academic research and practical applications in the field. For more details, you can visit my website at osllm.ai or explore my projects on GitHub: GitHub: https://github.com/osllmai/ indox: https://github.com/osllmai/inDox indoxJudge: https://github.com/osllmai/indoxJudge Phoenix: https://github.com/osllmai/phoenix Phoenix_cli: https://github.com/osllmai/phoenix_cli Contact me: https://www.linkedin.com/in/ali-nemati/ Email: alinemati@osllm.ai