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README.md

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> This is a public version of the AutoCodeRover project. Check the latest results on our [website](https://autocoderover.dev/).
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## 📣 Updates
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- [July 18, 2024] Added support for fix localization output mode and requirements.txt
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- [June 20, 2024] AutoCodeRover now achieves **30.67%** efficacy (pass@1) on SWE-bench-lite!
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- [August 14, 2024] On the SWE-bench Verified dataset released by OpenAI, AutoCodeRover(v20240620) achieves **38.40%** efficacy, and AutoCodeRover(v20240408) achieves 28.8% efficacy. More details in the [blog post](https://openai.com/index/introducing-swe-bench-verified/) from OpenAI and [SWE-bench leaderboard](https://www.swebench.com/).
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- [July 18, 2024] AutoCodeRover now supports a new mode that outputs the list of potential fix locations.
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- [June 20, 2024] AutoCodeRover(v20240620) now achieves **30.67%** efficacy (pass@1) on SWE-bench-lite!
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- [June 08, 2024] Added support for Gemini, Groq (thank you [KasaiHarcore](https://github.com/KasaiHarcore) for the contribution!) and Anthropic models through AWS Bedrock (thank you [JGalego](https://github.com/JGalego) for the contribution!).
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- [April 29, 2024] Added support for Claude and Llama models. Find the list of supported models [here](#using-a-different-model)! Support for more models coming soon.
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- [April 19, 2024] AutoCodeRover now supports running on [GitHub issues](#github-issue-mode-set-up-and-run-on-new-github-issues) and [local issues](#local-issue-mode-set-up-and-run-on-local-repositories-and-local-issues)! Feel free to try it out and we welcome your feedback!
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AutoCodeRover is a fully automated approach for resolving GitHub issues (bug fixing and feature addition) where LLMs are combined with analysis and debugging capabilities to prioritize patch locations ultimately leading to a patch.
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[Update on June 20, 2024] AutoCodeRover now resolves **30.67%** of issues (pass@1) in SWE-bench lite! AutoCodeRover achieved this efficacy while being economical - each task costs **less than $0.7** and is completed within **7 mins**!
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[Update on June 20, 2024] AutoCodeRover(v20240620) now resolves **30.67%** of issues (pass@1) in SWE-bench lite! AutoCodeRover achieved this efficacy while being economical - each task costs **less than $0.7** and is completed within **7 mins**!
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<p align="center">
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<img src=https://github.com/nus-apr/auto-code-rover/assets/16000056/78d184b2-f15c-4408-9eac-cfd3a11a503a width=500/>
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<img src=https://github.com/nus-apr/auto-code-rover/assets/16000056/83253ae9-8789-474e-942d-708495b5b310 width=500/>
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</p>
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[April 08, 2024] First release of AutoCodeRover resolves **19%** of issues in [SWE-bench lite](https://www.swebench.com/lite.html) (pass@1), improving over the current state-of-the-art efficacy of AI software engineers.
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[April 08, 2024] First release of AutoCodeRover(v20240408) resolves **19%** of issues in [SWE-bench lite](https://www.swebench.com/lite.html) (pass@1), improving over the current state-of-the-art efficacy of AI software engineers.
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AutoCodeRover works in two stages:

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