TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage

Understand

With recent advancements in natural language processing, Large Language Models (LLMs) have emerged as powerful tools for various real-world applications.

• Despite their prowess, the intrinsic generative abilities of LLMs may prove insufficient for handling complex tasks which necessitate a combination of task planning and the usage of external tools.
• In this paper, we first propose a structured framework tailored for LLM-based AI Agents and discuss the crucial capabilities necessary for tackling intricate problems.
• Within this framework, we design two distinct types of agents (i.e., one-step agent and sequential agent) to execute the inference process.