57 lines
1.6 KiB
Markdown
57 lines
1.6 KiB
Markdown
# AnyTool
|
|
This is the implementation of the paper [AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls](https://arxiv.org/abs/2402.04253)
|
|

|
|
|
|
# Installation
|
|
## Dependencies
|
|
Require Python 3.9+
|
|
|
|
Quick install
|
|
```bash
|
|
pip install requirements.txt
|
|
```
|
|
|
|
# Data
|
|
**ToolBench**
|
|
|
|
Refer to [ToolBench](https://github.com/OpenBMB/ToolBench).
|
|
|
|
**AnyToolBench**
|
|
|
|
# AnyToolBench Generation
|
|
```
|
|
python data_generation_by_gpt4.py
|
|
```
|
|
|
|
We provide sample data in anytoolbench.json file.
|
|
|
|
|
|
|
|
# Run AnyTool
|
|
Fill your OpenAI config and toolbench key into the config.py.
|
|
|
|
Run ToolBench
|
|
```
|
|
python anytool.py --output_dir result/test_instruction/G1_instruction --query_path data/test_instruction/G1_instruction.json --max_api_number 64
|
|
```
|
|
Run AnyToolBench
|
|
```
|
|
python anytool.py --output_dir result/anytoolbench --query_path anytoolbench.json -max_api_number 64
|
|
```
|
|
# AnyToolBench Generation
|
|
```
|
|
python data_generation_by_gpt4.py
|
|
```
|
|
# Acknowledgement
|
|
This repo is built on [ToolBench](https://github.com/OpenBMB/ToolBench).
|
|
|
|
# Citation
|
|
If you find this project is helpful for your research, consider citing our paper
|
|
```
|
|
@article{du2024anytool,
|
|
title={AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls},
|
|
author={Du, Yu and Wei, Fangyun and Zhang, Hongyang},
|
|
journal={arXiv preprint arXiv:2402.04253},
|
|
year={2024}
|
|
}
|
|
```
|