ToolACE is an automated agent pipeline dataset for tool learning tasks, released in 2024 by Shanghai Jiao Tong University in collaboration with the University of Science and Technology of China, Huawei Noah's Ark Lab, and other institutions. Related papers include... ToolACE: Winning the Points of LLM Function CallingIt aims to generate accurate, complex, and diverse tool learning data, and is designed to address real-world problems such as insufficient data quality and limited scenarios in tool learning. This dataset contains multi-step conversation examples, calling a total of 26,507 diverse APIs. The samples are generated through multi-agent interactions and undergo a two-layer quality assurance process of rule checking and model validation. Each dialogue represents a multi-step, multi-source information retrieval and analysis task, realistically simulating tool call scenarios and providing high-value training data for LLM (Low-Level Modeling).