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README.md

Gorilla APIBench Evaluation with OpenHands

This folder contains evaluation harness we built on top of the original Gorilla APIBench (paper).

Setup Environment and LLM Configuration

Please follow instruction here to setup your local development environment and LLM.

Run Inference on APIBench Instances

Make sure your Docker daemon is running, then run this bash script:

./evaluation/gorilla/scripts/run_infer.sh [model_config] [git-version] [agent] [eval_limit] [hubs]

where model_config is mandatory, while all other arguments are optional.

model_config, e.g. llm, is the config group name for your LLM settings, as defined in your config.toml.

git-version, e.g. HEAD, is the git commit hash of the OpenHands version you would like to evaluate. It could also be a release tag like 0.6.2.

agent, e.g. CodeActAgent, is the name of the agent for benchmarks, defaulting to CodeActAgent.

eval_limit, e.g. 10, limits the evaluation to the first eval_limit instances. By default, the script evaluates 1 instance.

hubs, the hub from APIBench to evaluate from. You could choose one or more from torch or th (which is abbreviation of torch), hf (which is abbreviation of huggingface), and tf (which is abbreviation of tensorflow), for hubs. The default is hf,torch,tf.

Note: in order to use eval_limit, you must also set agent; in order to use hubs, you must also set eval_limit.

For example,

./evaluation/gorilla/scripts/run_infer.sh llm 0.6.2 CodeActAgent 10 th