ToolFactory: Automating Tool Generation by Leveraging LLM to Understand REST API Documentations
Xinyi Ni (1), Qiuyang Wang (1), Yukun Zhang (1), Pengyu Hong, (1) ((1) Brandeis University)

TL;DR
ToolFactory is an open-source pipeline that automates the generation of AI-compatible tools from unstructured REST API documentation, addressing inconsistencies and incomplete info to streamline AI agent development.
Contribution
It introduces an automated tool generation pipeline, an error diagnosis method, and a verified knowledge base, improving reliability and handling poorly documented APIs.
Findings
Effective tool generation demonstrated on diverse API documents.
Created a comprehensive API extraction benchmark with 167 documents.
Significant potential for integrating scientific REST APIs into AI workflows.
Abstract
LLM-based tool agents offer natural language interfaces, enabling users to seamlessly interact with computing services. While REST APIs are valuable resources for building such agents, they must first be transformed into AI-compatible tools. Automatically generating AI-compatible tools from REST API documents can greatly streamline tool agent development and minimize user learning curves. However, API documentation often suffers from a lack of standardization, inconsistent schemas, and incomplete information. To address these issues, we developed \textbf{ToolFactory}, an open-source pipeline for automating tool generation from unstructured API documents. To enhance the reliability of the developed tools, we implemented an evaluation method to diagnose errors. Furthermore, we built a knowledge base of verified tools, which we leveraged to infer missing information from poorly documented…
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Scientific Computing and Data Management · Service-Oriented Architecture and Web Services
MethodsBalanced Selection
