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22<div align =" center " >
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4- ![ AgentLab Banner] ( https://github.com/user-attachments/assets/a23b3cd8-b5c4-4918-817b-654ae6468cb4 )
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86[ ![ pypi] ( https://badge.fury.io/py/agentlab.svg )] ( https://pypi.org/project/agentlab/ )
2119[ 🤖 Build Your Agent] ( #-implement-a-new-agent )   ; |  ;
2220[ ↻ Reproducibility] ( #-reproducibility )
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23+ <img src =" https://github.com/user-attachments/assets/47a7c425-9763-46e5-be54-adac363be850 " alt =" agentlab-diagram " width =" 700 " />
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26+ Demo solving tasks:
2427https://github.com/ServiceNow/BrowserGym/assets/26232819/e0bfc788-cc8e-44f1-b8c3-0d1114108b85
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2629</div >
@@ -240,7 +243,7 @@ dynamic benchmarks.
240243 version and commit hash
241244* The ` Study ` class allows automatic upload of your results to
242245 [ ` reproducibility_journal.csv ` ] ( reproducibility_journal.csv ) . This makes it easier to populate a
243- large amount of reference points.
246+ large amount of reference points. For this feature, you need to ` git clone ` the repository and install via ` pip install -e . ` .
244247* ** Reproduced results in the leaderboard** . For agents that are repdocudibile, we encourage users
245248 to try to reproduce the results and upload them to the leaderboard. There is a special column
246249 containing information about all reproduced results of an agent on a benchmark.
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