Hazumi News | Show HN: 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 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!

Summary

The linked article is about llmware - a unified framework for developing LLM-based application patterns including Retrieval Augmented Generation (RAG) that provides an integrated set of tools for building industrial-grade, knowledge-based enterprise LLM applications. It supports a wide range of open source and proprietary models and supports several vector and text index databases. There is also an option for Postgres integration with PGVector support. Currently, the latest version available is llmware v0.2.0.

Story

Show HN: LLMWare – Small Specialized Function Calling 1B LLMs for Multi-Step RAG