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[Fauxpilot](https://github.com/fauxpilot/fauxpilot): Code completion server with *CodeGen*. 15 | - [CodeGPT.nvim](https://github.com/dpayne/CodeGPT.nvim): ChatGPT in neovim. 16 | - [Vibe Compiler (vibec)](https://github.com/Strawberry-Computer/vibe-compiler): A self-compiling tool that transforms markdown-based prompt stacks into code and tests using LLM generation via OpenRouter. 17 | - [org-ai](https://github.com/rksm/org-ai): Emacs org-mode with OpenAI APIs. 18 | - [Autodoc](https://github.com/context-labs/autodoc): Generate codebase documentation use LLM (OpenAI / Alpaca) 19 | - [CodeAlpaca](https://github.com/sahil280114/codealpaca): LLaMA trained on code instruction following. 20 | - [🐾 Tabby](https://github.com/TabbyML/tabby): An opensource / on-prem alternative to GitHub Copilot. 21 | - [promptr](https://github.com/ferrislucas/promptr): CLI tool to operating on your codebase using GPT. 22 | - [ChatIDE](https://github.com/yagil/ChatIDE): Extension let you talk to ChatGPT inside VSCode. 23 | - [PromptMate](https://github.com/MateusZitelli/PromptMate): VSCode extension embed ChatGPT. 24 | - [TurboPilot](https://github.com/ravenscroftj/turbopilot): CPU based copilot clone 25 | - [CodeCapybara](https://github.com/FSoft-AI4Code/CodeCapybara): Open Source LLaMA Model that Follow Instruction-Tuning for Code Generation. 26 | - [CodeTF](https://github.com/salesforce/CodeTF): A One-stop Transformer Library for State-of-the-art Code LLM 27 | - [Rift](https://github.com/morph-labs/rift): A opensource LSP leveraging edge language model. 28 | - [Octopack](https://github.com/bigcode-project/octopack) 29 | + [OctoPack: Instruction Tuning Code Large Language Models 30 | ](https://arxiv.org/abs/2308.07124) 31 | + Instruct fine-tuning Code LLMs on large scale github commit dataset. 32 | - [Bloop](https://github.com/BloopAI/bloop): bloop is a (AI-powered) fast code search engine written in Rust. 33 | + Pivot to AI powered legacy code migration: https://bloop.ai/ 34 | - [Twinny](https://github.com/rjmacarthy/twinny): ollama based AI code completion plugin 35 | - [MutahunterAI](https://github.com/codeintegrity-ai/mutahunter): Accelerate developer productivity and code security with our open-source AI. 36 | - [code-collator](https://github.com/tawandakembo/code-collator): Creates a single markdown file that describes your entire codebase to language models. 37 | - [batchai](https://github.com/qiangyt/batchai): A supplement to Copilot and Cursor - utilizes AI for batch processing of project codes 38 | - [Berrry](https://berrry.app): AI-powered platform that transforms social media posts into functional web applications using LLM code generation. 39 | 40 | ## Datasets 41 | 42 | - [The Pile](https://huggingface.co/datasets/the_pile) 43 | - [The Stack](https://huggingface.co/datasets/bigcode/the-stack) 44 | - [CodeContests](https://github.com/deepmind/code_contests) 45 | - [CodeSearchNet](https://github.com/github/CodeSearchNet) 46 | - [The Vault](https://github.com/FSoft-AI4Code/TheVault) 47 | 48 | ## LLM Models 49 | 50 | - [PolyCoder 160M/400M/2.7B](https://github.com/VHellendoorn/Code-LMs) 51 | - [CodeGen 350M/2B/6B/16B](https://github.com/salesforce/CodeGen) 52 | - [TransCoder](https://github.com/facebookresearch/CodeGen) 53 | - [CodeGeeX 13B](https://github.com/THUDM/CodeGeeX) 54 | - [SantaCoder 1.1B](https://huggingface.co/bigcode/santacoder) 55 | - [InCoder 1B/6B](https://github.com/dpfried/incoder) 56 | - [replit-code-v1-3b](https://huggingface.co/replit/replit-code-v1-3b) 57 | - [StarCoder 15B](https://huggingface.co/bigcode/starcoder) 58 | - [CodeGen2](https://github.com/salesforce/CodeGen2) 59 | - [CodeT5 / CodeT5+](https://github.com/salesforce/CodeT5) 60 | - [CodeLlama](https://github.com/facebookresearch/codellama) 61 | 62 | ## Embedding Models 63 | - [CodeBERTa](https://huggingface.co/huggingface/CodeBERTa-small-v1) 64 | 65 | ## Papers & Blogs 66 | 67 | - [Competition-level code generation with AlphaCode](https://deepmind.com/blog/article/Competitive-programming-with-AlphaCode) 68 | - [RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation](https://arxiv.org/abs/2303.12570) 69 | * Combined LLM completion and CodeSearch 70 | * CodeGen-350M + BoW based snippet search beat Codex 71 | - [Repository-Level Prompt Generation for Large Language Models of Code](https://arxiv.org/abs/2206.12839) 72 | * Generate proposals candidates based with prios, e.g imports, files from same dirs. 73 | * Use a proposal candidate classifier to select based proposals for LLM. 74 | - [ML-Enhanced Code Completion Improves Developer Productivity](https://ai.googleblog.com/2022/07/ml-enhanced-code-completion-improves.html) 75 | * 500M Encoder-Decoder based model, fine tuned on Google's monorepo. 76 | * 34% acceptance rate for multi-line code completion suggestions. 77 | - [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://arxiv.org/abs/2303.12712): Chapter 3 on coding scenario. Chat UX. 78 | - [Efficient Training of Language Models to Fill in the Middle](https://arxiv.org/abs/2207.14255): Train decoder-only model with suffix context using a special token. 79 | - [Toolformer: Language Models Can Teach Themselves to Use Tools](https://arxiv.org/abs/2302.04761): LLM as API glue layer. 80 | - [CodeCompose: A Large-Scale Industrial Deployment of 81 | AI-assisted Code Authoring](https://arxiv.org/abs/2305.12050) 82 | * deployed as single line code completion to reduce latency to 300ms - 500ms. 83 | * 1.3B parameter size. 84 | * fine-tuning improves accuracy / bleu by 50% - 100%. 85 | 86 | 87 | ## Products & Startups 88 | 89 | - [Copilot](https://github.com/features/copilot) + [Copilot X](https://github.com/features/preview/copilot-x) 90 | - [Codeium](https://www.codeium.com/) 91 | - [CodeComplete.AI](https://codecomplete.ai/) 92 | - [Codify](https://codify.smallcloud.ai/) [refact.ai](https://refact.ai/) 93 | - [Cody](https://docs.sourcegraph.com/cody) 94 | - [Amazon Codewhisperer](https://aws.amazon.com/cn/codewhisperer/) 95 | - [Replit Ghostwrite](https://replit.com/site/ghostwriter) 96 | - [Tabnine](https://www.tabnine.com/) 97 | - [AiXCoder](https://www.aixcoder.com/en/) 98 | - [Turin Tech](https://www.turintech.ai/) 99 | - [Cursor](https://www.cursor.so/) 100 | - [Buildt](https://www.buildt.ai/) [Cosine](https://cosine.sh/) 101 | - [Safurai](https://www.safurai.com/) 102 | - [phind](https://www.phind.com/) 103 | - [AskCodi](https://www.askcodi.com/) 104 | - [MutableAI](https://mutable.ai/) 105 | - [Machinet](https://machinet.net/) 106 | - [BlackBox](https://www.useblackbox.io/) 107 | - [MetaBob](https://www.metabob.com) 108 | - [aider](https://aider.chat) 109 | - [sweep](http://sweep.dev) 110 | - [continuedev](http://continue.dev) 111 | - [ZZZ Code AI](https://zzzcode.ai/) 112 | - [Augment Code](https://www.augmentcode.com/) 113 | - [CodeGen](https://www.codegen.com/) 114 | - [Pixee](https://pixee.ai) 115 | - [MutahunterAI](https://mutahunter.ai) 116 | - [Trae](https://www.trae.ai/home) 117 | 118 | ## Peer Awesome Lists 119 | - [Awesome AI-Powered Developer Tools](https://github.com/jamesmurdza/awesome-ai-devtools) 120 | - [Are copilots local yet?](https://github.com/ErikBjare/are-copilots-local-yet) 121 | 122 | ## Star History 123 | 124 | [![Star History Chart](https://api.star-history.com/svg?repos=wsxiaoys/awesome-ai-coding&type=Date)](https://star-history.com/#wsxiaoys/awesome-ai-coding&Date) 125 | --------------------------------------------------------------------------------