LLMWare – Small Specialized Function Calling 1B LLMs for Multi-Step RAG
Hi, I was a corporate lawyer for many years working with a lot of financial services and insurance companies. In practicing law, I noticed there was a lot of repetition in the tasks I was working on even as a highly paid attorney that could be automated. I wanted to solve the problem of dealing with a lot information and data in a practical way, using AI. This motivated me to start AI Bloks/LLMWare with my husband, who had a deep background in software and is a very early adopter of AI. We have been on this journey with our open source project LLMWare for the past 4 months, producing a…
In plain words
LLMWare is an open-source RAG framework featuring specialized 1B language models designed for multi-step retrieval-augmented generation workflows. It targets developers and enterprises handling large volumes of documents and data who need practical AI automation for repetitive information processing tasks. The framework includes approximately 50 models available on Hugging Face and focuses on using smaller, specialized models rather than large general-purpose ones for improved efficiency in document-heavy workflows.
written from the facts on this page · September 2026
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In the maker’s words, at launch
Hi, I was a corporate lawyer for many years working with a lot of financial services and insurance companies. In practicing law, I noticed there was a lot of repetition in the tasks I was working on even as a highly paid attorney that could be automated. I wanted to solve the problem of dealing with a lot information and data in a practical way, using AI. This motivated me to start AI Bloks/LLMWare with my husband, who had a deep background in software and is a very early adopter of AI. We have been on this journey with our open source project LLMWare for the past 4 months, producing a RAG framework in GH and about 50 models in Hugging Face. https://huggingface.co/llmware Our latest models are designed to re-imagine the way we use small specialized models in multi-step RAG workflow (SLIMs). I would love for you to check it out and give us some feedback. Thank you!
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