quchangle1/DRAFT
The implementation for ICLR 2025 Oral: From Exploration to Mastery: Enabling LLMs to Master Tools via Self-Driven Interactions.
This project helps developers and researchers improve how Large Language Models (LLMs) use external software tools. It takes existing tool documentation and, through simulated LLM interactions, automatically refines it. The output is optimized documentation, enabling LLMs to understand and utilize tools more effectively, making them more powerful assistants.
No commits in the last 6 months.
Use this if you are a developer working with LLMs and frequently encounter problems with them misinterpreting or failing to properly use external APIs or software tools.
Not ideal if you are an end-user simply looking to use an LLM for general tasks and are not involved in its underlying development or tool integration.
Stars
54
Forks
3
Language
Python
License
MIT
Category
Last pushed
Aug 09, 2025
Commits (30d)
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