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+
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+ root = true
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+
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+ [*]
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+ charset = utf-8
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+ end_of_line = lf
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+ indent_style = space
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+ indent_size = 4
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+ trim_trailing_whitespace = true
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+ insert_final_newline = true
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+
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+ [*.{json,yaml,yml}]
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+ indent_size = 2
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+
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+ [*.md]
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+ indent_size = 2
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+ x-soft-wrap-text = true
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+
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+ [*.rst]
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+ indent_size = 4
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+ x-soft-wrap-text = true
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+
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+ [Makefile]
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+ indent_style = tab
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+ [settings]
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+ default_stages: [pre-commit, pre-push, manual]
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+
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+ repos:
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+ - repo: https://github.com/pre-commit/pre-commit-hooks
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+ rev: v5.0.0
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+ hooks:
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+ - id: check-symlinks
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+ - id: destroyed-symlinks
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+ - id: trailing-whitespace
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+ - id: end-of-file-fixer
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+ - id: check-yaml
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+ args: [--allow-multiple-documents]
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+ - id: check-toml
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+ - id: check-ast
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+ - id: check-added-large-files
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+ - id: check-merge-conflict
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+ - id: check-shebang-scripts-are-executable
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+ - id: detect-private-key
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+ - id: no-commit-to-branch
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+ - repo: https://github.com/PyCQA/isort
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+ rev: 5.13.2
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+ hooks:
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+ - id: isort
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+ - repo: https://github.com/psf/black
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+ rev: 24.10.0
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sglang_repo/Makefile ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ .PHONY: check-deps install-deps format update help
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+
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+ # Show help for each target
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+ help:
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+ @echo "Available targets:"
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+ @grep -E '^[a-zA-Z0-9_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-20s\033[0m %s\n", $$1, $$2}'
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+
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+ check-deps: ## Check and install required Python formatting dependencies
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+ @command -v isort >/dev/null 2>&1 || (echo "Installing isort..." && pip install isort)
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+ @command -v black >/dev/null 2>&1 || (echo "Installing black..." && pip install black)
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+
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+ install-deps: ## Install Python formatting tools (isort and black)
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+ pip install isort black
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+
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+ format: check-deps ## Format modified Python files using isort and black
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+ @echo "Formatting modified Python files..."
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+ git diff --name-only --diff-filter=M | grep '\.py$$' | xargs -I {} sh -c 'isort {} && black {}'
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+
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+ FILES_TO_UPDATE = docker/Dockerfile.rocm \
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+ python/pyproject.toml \
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+ python/sglang/version.py \
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+ docs/developer/setup_github_runner.md \
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+ docs/start/install.md
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+
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+ update: ## Update version numbers across project files. Usage: make update <new_version>
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+ @if [ -z "$(filter-out $@,$(MAKECMDGOALS))" ]; then \
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+ echo "Version required. Usage: make update <new_version>"; \
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+ exit 1; \
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+ fi
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+ @OLD_VERSION=$$(grep "version" python/sglang/version.py | cut -d '"' -f2); \
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+ NEW_VERSION=$(filter-out $@,$(MAKECMDGOALS)); \
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+ echo "Updating version from $$OLD_VERSION to $$NEW_VERSION"; \
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+ for file in $(FILES_TO_UPDATE); do \
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+ if [ "$(shell uname)" = "Darwin" ]; then \
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+ sed -i '' -e "s/$$OLD_VERSION/$$NEW_VERSION/g" $$file; \
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+ else \
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+ sed -i -e "s/$$OLD_VERSION/$$NEW_VERSION/g" $$file; \
38
+ fi \
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+ done; \
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+ echo "Version update complete"
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+
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+ %:
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+ @:
sglang_repo/README.md ADDED
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1
+ # SGLang for PowerRAG
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+ <div align="center" id="sglangtop">
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+ <img src="https://raw.githubusercontent.com/sgl-project/sglang/main/assets/logo.png" alt="logo" width="400" margin="10px"></img>
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+ [![](https://img.shields.io/badge/Gurubase-(experimental)-006BFF)](https://gurubase.io/g/sglang)
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+
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+ </div>
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+
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+ --------------------------------------------------------------------------------
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+
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+ | [**Blog**](https://lmsys.org/blog/2024-07-25-sglang-llama3/)
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+ | [**Documentation**](https://docs.sglang.ai/)
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+ | [**Join Slack**](https://slack.sglang.ai/)
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+ | [**Join Bi-Weekly Development Meeting**](https://meeting.sglang.ai/)
20
+ | [**Slides**](https://github.com/sgl-project/sgl-learning-materials?tab=readme-ov-file#slides) |
21
+
22
+ ## News
23
+ - [2025/01] 🔥 SGLang provides day one support for DeepSeek V3/R1 models on NVIDIA and AMD GPUs with DeepSeek-specific optimizations. ([instructions](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3), [AMD blog](https://www.amd.com/en/developer/resources/technical-articles/amd-instinct-gpus-power-deepseek-v3-revolutionizing-ai-development-with-sglang.html))
24
+ - [2024/12] 🔥 v0.4 Release: Zero-Overhead Batch Scheduler, Cache-Aware Load Balancer, Faster Structured Outputs ([blog](https://lmsys.org/blog/2024-12-04-sglang-v0-4/)).
25
+ - [2024/09] v0.3 Release: 7x Faster DeepSeek MLA, 1.5x Faster torch.compile, Multi-Image/Video LLaVA-OneVision ([blog](https://lmsys.org/blog/2024-09-04-sglang-v0-3/)).
26
+ - [2024/07] v0.2 Release: Faster Llama3 Serving with SGLang Runtime (vs. TensorRT-LLM, vLLM) ([blog](https://lmsys.org/blog/2024-07-25-sglang-llama3/)).
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+
28
+ <details>
29
+ <summary>More</summary>
30
+
31
+ - [2024/10] The First SGLang Online Meetup ([slides](https://github.com/sgl-project/sgl-learning-materials?tab=readme-ov-file#the-first-sglang-online-meetup)).
32
+ - [2024/02] SGLang enables **3x faster JSON decoding** with compressed finite state machine ([blog](https://lmsys.org/blog/2024-02-05-compressed-fsm/)).
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+ - [2024/01] SGLang provides up to **5x faster inference** with RadixAttention ([blog](https://lmsys.org/blog/2024-01-17-sglang/)).
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+ - [2024/01] SGLang powers the serving of the official **LLaVA v1.6** release demo ([usage](https://github.com/haotian-liu/LLaVA?tab=readme-ov-file#demo)).
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+
36
+ </details>
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+
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+ ## About
39
+ SGLang is a fast serving framework for large language models and vision language models.
40
+ It makes your interaction with models faster and more controllable by co-designing the backend runtime and frontend language.
41
+ The core features include:
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+
43
+ - **Fast Backend Runtime**: Provides efficient serving with RadixAttention for prefix caching, jump-forward constrained decoding, overhead-free CPU scheduler, continuous batching, token attention (paged attention), tensor parallelism, FlashInfer kernels, chunked prefill, and quantization (FP8/INT4/AWQ/GPTQ).
44
+ - **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.
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+ - **Extensive Model Support**: Supports a wide range of generative models (Llama, Gemma, Mistral, QWen, DeepSeek, LLaVA, etc.), embedding models (e5-mistral, gte, mcdse) and reward models (Skywork), with easy extensibility for integrating new models.
46
+ - **Active Community**: SGLang is open-source and backed by an active community with industry adoption.
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+
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+ ## Getting Started
49
+ - [Install SGLang](https://docs.sglang.ai/start/install.html)
50
+ - [Quick Start](https://docs.sglang.ai/start/send_request.html)
51
+ - [Backend Tutorial](https://docs.sglang.ai/backend/openai_api_completions.html)
52
+ - [Frontend Tutorial](https://docs.sglang.ai/frontend/frontend.html)
53
+ - [Contribution Guide](https://docs.sglang.ai/references/contribution_guide.html)
54
+
55
+ ## Benchmark and Performance
56
+ Learn more in the release blogs: [v0.2 blog](https://lmsys.org/blog/2024-07-25-sglang-llama3/), [v0.3 blog](https://lmsys.org/blog/2024-09-04-sglang-v0-3/), [v0.4 blog](https://lmsys.org/blog/2024-12-04-sglang-v0-4/)
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+
58
+ ## Roadmap
59
+ [Development Roadmap (2024 Q4)](https://github.com/sgl-project/sglang/issues/1487)
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+
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+ ## Adoption and Sponsorship
62
+ The project is supported by (alphabetically): AMD, Baseten, Cursor, DataCrunch, Etched, Hyperbolic, Jam & Tea Studios, LinkedIn, LMSYS.org, Meituan, NVIDIA, RunPod, Stanford, UC Berkeley, UCLA, xAI, 01.AI.
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+
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+ ## Acknowledgment and Citation
65
+ We learned the design and reused code from the following projects: [Guidance](https://github.com/guidance-ai/guidance), [vLLM](https://github.com/vllm-project/vllm), [LightLLM](https://github.com/ModelTC/lightllm), [FlashInfer](https://github.com/flashinfer-ai/flashinfer), [Outlines](https://github.com/outlines-dev/outlines), and [LMQL](https://github.com/eth-sri/lmql). Please cite the paper, [SGLang: Efficient Execution of Structured Language Model Programs](https://arxiv.org/abs/2312.07104), if you find the project useful.
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