base on Fast, Flexible and Portable Structured Generation <div align="center" id="top"> <img src="https://raw.githubusercontent.com/mlc-ai/xgrammar/main/assets/logo.svg" alt="logo" width="400" margin="10px"></img> [](https://xgrammar.mlc.ai/docs/) [](https://github.com/mlc-ai/xgrammar/blob/main/LICENSE) [](https://pypi.org/project/xgrammar) [](https://pepy.tech/projects/xgrammar) [](https://deepwiki.com/mlc-ai/xgrammar) **Efficient, Flexible and Portable Structured Generation** [Get Started](#get-started) | [Documentation](https://xgrammar.mlc.ai/docs/) | [Blogpost](https://blog.mlc.ai/2024/11/22/achieving-efficient-flexible-portable-structured-generation-with-xgrammar) | [Technical Report](https://arxiv.org/abs/2411.15100) </div> ## News - [2025/02] XGrammar has been officially integrated into [Modular's MAX](https://docs.modular.com/max/serve/structured-output) - [2025/01] XGrammar has been officially integrated into [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM). - [2024/12] XGrammar has been officially integrated into [vLLM](https://github.com/vllm-project/vllm). - [2024/12] We presented research talks on XGrammar at CMU, UC Berkeley, MIT, THU, SJTU, Ant Group, LMSys, Qingke AI, Camel AI. The slides can be found [here](https://docs.google.com/presentation/d/1iS7tu2EV4IKRWDaR0F3YD7ubrNqtGYUStSskceneelc/edit?usp=sharing). - [2024/11] XGrammar has been officially integrated into [SGLang](https://github.com/sgl-project/sglang). - [2024/11] XGrammar has been officially integrated into [MLC-LLM](https://github.com/mlc-ai/mlc-llm). - [2024/11] We officially released XGrammar v0.1.0! ## Overview XGrammar is an open-source library for efficient, flexible, and portable structured generation. It leverages constrained decoding to ensure **100% structural correctness** of the output. It supports general context-free grammar to enable a broad range of structures, including **JSON**, **regex**, **custom context-free grammar**, etc. XGrammar uses careful optimizations to achieve extremely low overhead in structured generation. It has achieved **near-zero overhead** in JSON generation, making it one of the fastest structured generation engines available. XGrammar features **universal deployment**. It supports: * **Platforms**: Linux, macOS, Windows * **Hardware**: CPU, NVIDIA GPU, AMD GPU, Apple Silicon, TPU, etc. * **Languages**: Python, C++, and JavaScript APIs * **Models**: Qwen, Llama, DeepSeek, Phi, Gemma, etc. XGrammar is very easy to integrate with LLM inference engines. It is the default structured generation backend for most LLM inference engines, including [**vLLM**](https://github.com/vllm-project/vllm), [**SGLang**](https://github.com/sgl-project/sglang), [**TensorRT-LLM**](https://github.com/NVIDIA/TensorRT-LLM), and [**MLC-LLM**](https://github.com/mlc-ai/mlc-llm), as well as many other companies. You can also try out their structured generation modes! ## Get Started Install XGrammar: ```bash pip install xgrammar ``` Import XGrammar: ```python import xgrammar as xgr ``` Please visit our [documentation](https://xgrammar.mlc.ai/docs/) to get started with XGrammar. - [Installation](https://xgrammar.mlc.ai/docs/start/installation) - [Quick start](https://xgrammar.mlc.ai/docs/start/quick_start) ## Adoption XGrammar has been adopted by many projects and companies, including but not limited to: <div align="center"> [<img src="https://raw.githubusercontent.com/mlc-ai/XGrammar-web-assets/refs/heads/main/repo/databricks.svg" height=50/>](https://www.databricks.com/) &emsp; [<img src="https://raw.githubusercontent.com/mlc-ai/XGrammar-web-assets/refs/heads/main/repo/nvidia.svg" height=50/>](https://github.com/NVIDIA/TensorRT-LLM) &emsp; [<img src="https://raw.githubusercontent.com/mlc-ai/XGrammar-web-assets/refs/heads/main/repo/modular.svg" height=50/>](https://www.modular.com/) &emsp; [<img src="https://raw.githubusercontent.com/mlc-ai/XGrammar-web-assets/refs/heads/main/repo/sglang.png" height=50/>](https://github.com/sgl-project/sglang) &emsp; [<img src="https://raw.githubusercontent.com/mlc-ai/XGrammar-web-assets/refs/heads/main/repo/vllm.png" height=50/>](https://github.com/vllm-project/vllm) &emsp; [<img src="https://raw.githubusercontent.com/mlc-ai/XGrammar-web-assets/refs/heads/main/repo/mlc.jpeg" height=50/>](https://github.com/mlc-ai/mlc-llm) &emsp; [<span style="font-size:50px">WebLLM</span>](https://github.com/mlc-ai/web-llm) </div> ## Citation If you find XGrammar useful in your research, please consider citing our paper: ```bibtex @article{dong2024xgrammar, title={Xgrammar: Flexible and efficient structured generation engine for large language models}, author={Dong, Yixin and Ruan, Charlie F and Cai, Yaxing and Lai, Ruihang and Xu, Ziyi and Zhao, Yilong and Chen, Tianqi}, journal={Proceedings of Machine Learning and Systems 7}, year={2024} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"12913","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"