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This folder contains evaluation harness for evaluating agents on the AgentBench: Evaluating LLMs as Agents. We currently only support running on the osbench subset.
Please follow instruction here to setup your local development environment and LLM.
./evaluation/agent_bench/scripts/run_infer.sh [model_config] [git-version] [agent] [eval_limit]
model_config, e.g. eval_gpt4_1106_preview, 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 the entire SWE-bench_Lite test set (300 issues). Note:
in order to use eval_limit, you must also set agent.Following is the basic command to start the evaluation.
You can update the arguments in the script evaluation/agent_bench/scripts/run_infer.sh, such as --max-iterations, --eval-num-workers and so on.
--agent-cls, the agent to use. For example, CodeActAgent.--llm-config: the LLM configuration to use. For example, eval_gpt4_1106_preview.--max-iterations: the number of iterations to run the evaluation. For example, 30.--eval-num-workers: the number of workers to use for evaluation. For example, 5.--eval-n-limit: the number of examples to evaluate. For example, 100.
./evaluation/agent_bench/scripts/run_infer.sh eval_gpt35_turbo HEAD CodeActAgent 1