RE-GAINS & EnCHANT: Intelligent Tool Manipulation Systems For Enhanced Query Responses

Girhepuje, Sahil, Sajeev, Siva Sankar, Jain, Purvam, Sikder, Arya, Varma, Adithya Rama, George, Ryan, Srinivasan, Akshay Govind, Kurup, Mahendra, Sinha, Ashmit, Mondal, Sudip

arXiv.org Artificial Intelligence 

Despite the remarkable success of LLMs, they still suffer from tool invocation and tool chaining due to inadequate input queries and/or tool argument descriptions. We propose two novel frameworks, RE-GAINS and EnCHANT, enabling LLMs to tackle tool manipulation for solving complex user queries by making API calls. EnCHANT is an open-source solution that makes use of an LLM format enforcer, an LLM(OpenChat 3.5) and a retriever(ToolBench's API Retriever). RE-GAINS is based on OpenAI models and embeddings using a special prompt based on the RAP paper. Both solutions cost less than $0.01 per query with minimal latency, therefore showcasing the usefulness of the frameworks.