Introducing TaskWeaver

An implementation with Azure OpenAI

TaskWeaver is a code-first agent framework that uses large language models (LLMs) and generative AI to plan and execute tasks.

“Code-first” means that users‘s query will be interpreted and executed by large language models (LLMs) via code snippets that call various plugins (functions) to perform the tasks.

Source: microsoft/TaskWeaver: A code-first agent framework for seamlessly planning and executing data analytics tasks. (github.com)

TaskWeaver supports rich data structures, customized algorithms, domain-specific knowledge, stateful execution, and code verification. It also allows users to create their own plugins and orchestrate multiple AI agents for complex tasks. It is an open-source project developed by Microsoft Research and you can read the original paper here.

The document introduces four key components of TaskWeaver: the Planner, the Code Interpreter (CI), the Code Generator (CG), and the Code Executor (CE). Here is a brief explanation of each component:

• Planner: This is the component that interacts with the user and manages the task execution process. It converts the user’s request into a plan consisting of sub-tasks, and communicates with the CI to generate and execute code for each sub-task…