JSON Processor

This is the repo for the paper How Good Are LLMs at Processing Tool Outputs?

This work was also integrated into the Agent Lifecycle Toolkit (ALTK) and Langflow.

Quick Start

Local install:

pip install .

QA data

The directory generate_qa_pairs contains the dataset creation code. Specifically, generate_qa_pairs/tasks has Python scripts to create the QA pairs for each of the API endpoints. The source API responses for all the booking.com endpoints are derived from ComplexFuncBench.

Experiments

All the experiment settings can be run by executing experimental_scripts/qa_inference.py

To determine the accuracy of the predictions, run experimental_scripts/qa_evaluation.py

Setups

• Answer generation in the paper refers to the direct_prompting_* setup type in the code.
• Code generation in the paper refers to the code_generation_* setup type in the code.
• Results in the Simplify JSON subsection in the paper are obtained by setting setup_type to direct_prompting_schema_cfx2 and code_generation_schema_cfx2

Cite as

@misc{kate2025how,
      title={How Good Are LLMs at Processing Tool Outputs?}, 
      author={Kiran Kate and Yara Rizk and Poulami Ghosh and Ashu Gulati and Tathagata Chakraborti and Zidane Wright and Mayank Agarwal},
      year={2025},
      eprint={},
      archivePrefix={arXiv},
      primaryClass={},
      url={}, 
}