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docs/index.rst

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+SGLang Documentation
+====================================
+
+SGLang is a fast serving framework for large language models and vision language models.
+It makes your interaction with models faster and more controllable by co-designing the backend runtime and frontend language.
+The core features include:
+
+- **Fast Backend Runtime**: Provides efficient serving with RadixAttention for prefix caching, jump-forward constrained decoding, continuous batching, token attention (paged attention), tensor parallelism, FlashInfer kernels, chunked prefill, and quantization (INT4/FP8/AWQ/GPTQ).
+- **Flexible Frontend Language**: Offers an intuitive interface for programming LLM applications, including chained generation calls, advanced prompting, control flow, multi-modal inputs, parallelism, and external interactions.
+- **Extensive Model Support**: Supports a wide range of generative models (Llama 3, Gemma 2, Mistral, QWen, DeepSeek, LLaVA, etc.) and embedding models (e5-mistral), with easy extensibility for integrating new models.
+- **Active Community**: SGLang is open-source and backed by an active community with industry adoption.
+
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Getting Started
+
+   install.md
+
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Backend Tutorial
+
+   backend.md
+
+
+.. toctree::
+   :maxdepth: 1
+   :caption: Frontend Tutorial
+
+   frontend.md
+
+
+.. toctree::
+   :maxdepth: 1
+   :caption: References
+
+   sampling_params.md
+   hyperparameter_tuning.md
+   model_support.md
+   contributor_guide.md
+   choices_methods.md
+   benchmark_and_profiling.md
+   troubleshooting.md