TaskWeaver

I think this is a great primer on how to make LLMs enterprise/domain specific, but is still couching this technology's main use-case in the context of "question-answer" machine toward the service of a user. While this may be the (brilliant) hook that enabled the massive conceptual adoption of the tech it is not going to be the value proposition of it. In the next 6 months we're going to see the deployment of Agency-based solutions completely powered by LLM[1][2]. The real value LLM provide will be that they replace the "humans-as-integrations" and RPA automations. 1. https://github.com/microsoft/UFO 2. https://github.com/microsoft/TaskWeaver

Paper: https://arxiv.org/pdf/2311.17541.pdf Abstract: Language Language Models (LLMs) have shown impressive abilities in natural language understanding and generation, leading to their use in applications such as chatbots and virtual assistants. However, existing LLM frameworks face limitations in handling domain-specific data analytics tasks with rich data structures. Moreover, they struggle with flexibility to meet diverse user requirements. To address these issues, TaskWeaver is proposed as a code-first framework for building LLM- powered autonomous agents. It converts user requests into executable code and treats user-defined plugins as callable functions. TaskWeaver provides support for rich data structures, flexible plugin usage, and dynamic plugin selection, and leverages LLM coding capabilities for complex logic. It also incorpora