Agents IA
SWE-agent
Give it a GitHub issue and it tries to fix the code for you - the original SWE-bench agent
★ 20,5 k étoilesMIT
Voir le guide →SWE-bench est un projet de agents IA open source, créé par SWE-bench (SWE-bench/SWE-bench sur GitHub). Il compte 5 986 étoiles sur GitHub et 1 004 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 18 septembre 2026.
The benchmark that grades AI on real GitHub issues.
Pick one concrete task so you can judge whether the project fits.
Clone the repo and check the prerequisites listed in the README.
Install what it needs and configure credentials or model access.
Run a minimal example end to end before wiring it into your stack.
Built from genuine GitHub issues, not toy problems.
Widely cited for coding-agent evaluation.
Resolves are verified with real test suites.
Accompanied by published methodology.
Harness and datasets in Python.
Permissive licensing.
Install the SWE-bench package.
pip install swebenchPull the task instances you want to evaluate on.
# see docs for dataset optionsEvaluate a model per the documentation.
swebench --help
# see docs for eval commandsIt is maintained by the SWE-bench organization at SWE-bench/SWE-bench, with 1,004 forks.
Yes. It is released under the MIT license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
Running evals needs model access and compute; the benchmark itself is free.
It targets real-world software engineering; compare with AgentBench or GPQA for different agent capabilities.
Read the paper and site docs, install the harness, and run a small evaluation.
Give it a GitHub issue and it tries to fix the code for you - the original SWE-bench agent
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.