Files
project_6/upstream_ref/xllm/.github/CONTRIBUTING.md
EX Engine 002f9879b2 ref(upstream): FULL TREE — Deep-Spark xllm (1470) + ds_vllm csrc/models (703)
Replaces cherry-picked upstream_ref with complete source trees.

xllm/ — Iluvatar official C++ inference engine (15MB, 1470 files)
  Complete: kernels → layers → models → runtime → scheduler → api
  Excluded: .git, binary images, third_party submodule checkouts

ds_vllm/ — Iluvatar official vllm fork (8MB, 703 files)
  Included: csrc/ (ALL CUDA kernels), fused_moe/, qwen3_5 model, _custom_ops
  Excluded: tests, benchmarks, docs, examples (not needed for reference)

Critical call chains now fully traceable:
  MoE: moe_topk_softmax_kernels.cuh → ixformer.h → fused_moe.cpp → layer
  GDN: qwen3_gated_delta_net_base.cpp → qwen3_5_gated_delta_net.cpp
  Attention: ixformer.h → xllm_paged_attention → attention.cpp
2026-08-10 02:54:03 +00:00

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[English](./CONTRIBUTING.md) | [中文](./CONTRIBUTING_zh.md)
# Contribute to xLLM
+ Write / translate / fix our documentation
+ Raise questions / Answer questions
+ Provide demos, examples or test cases
+ Give suggestions or other comments
+ Paticipate in [issues](https://github.com/xxx/xLLM/issues) or [discussions](https://github.com/xxx/xLLM/discussions)
+ Pull requests
+ Sharing related research / application
+ Any other ways to improve xLLM
For developers who want to contribute to our code, here is the guidance:
## 1. Choose an issue to contribute
+ Issues with label `PR welcome`, which means:
+ A reproducible bug
+ A function in plan
## 2. Install environment for development
+ We strongly suggest you to read our **[Document](http://xxx/docs/)** before developing
+ For setting environment, please check our **[Readme file](/README.md)**
## 3. Build our project
+ You could run our demo to check whether the requirements are successfully installed:
## 4. Test
After the PR is submitted, we will format and test the code.
Our tests are still far from perfect, so you are welcomed to add tests to our project!