Fix doc links and add tests

.github/copilot-instructions.md

@@ -40,10 +40,11 @@ These instructions help AI agents work productively in this repo. Focus on concr
   - Initialize infra: `twinkle.initialize(mode='local', seed=42)`
   - Inspect device placement: call `twinkle.infra.get_device_placement()`.
 - **Ray Serve demo (HTTP services):**
-  - Config and launcher: [cookbook/client/server.py](cookbook/client/server.py), [cookbook/client/server_config.yaml](cookbook/client/server_config.yaml)
+  - Config and launcher: [cookbook/client/tinker/megatron/server.py](https://github.com/modelscope/twinkle/blob/main/cookbook/client/tinker/megatron/server.py), [cookbook/client/tinker/megatron/server_config.yaml](https://github.com/modelscope/twinkle/blob/main/cookbook/client/tinker/megatron/server_config.yaml)
   - Start:
-    - `python cookbook/client/server.py`
-    - Endpoints print on startup (default `localhost:8000`).
+    - `cd cookbook/client/tinker/megatron`
+    - `python server.py`
+    - Endpoints print on startup (default `localhost:8000` or `https://www.modelscope.cn/twinkle`).
   - Model app binds `MultiLoraTransformersModel` and exposes routes like `/add_adapter_to_model`, `/forward`, `/calculate_loss`, etc. See [src/twinkle/server/twinkle/model.py](src/twinkle/server/twinkle/model.py).
 - **vLLM inference:** Use `VLLMEngine` with engine args; LoRA weight sync via `patch.vllm_lora_weights`. See [src/twinkle/sampler/vllm_engine.py](src/twinkle/sampler/vllm_engine.py).
 

README_ZH.md

@@ -113,7 +113,7 @@ pip install -e .
 |                   | [deepseek-ai/DeepSeek-R1](https://modelscope.cn/models/deepseek-ai/DeepSeek-R1)                                          | transformers>=4.39.3 | ✅               | [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1)                                     |
 | deepSeek-r1-distill | [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://modelscope.cn/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) ~32B | transformers>=4.37   | ✅               | [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) |
 
-更详细的模型支持列表 👉  [快速开始.md](https://github.com/modelscope/twinkle/blob/dev/docs/source/%E4%BD%BF%E7%94%A8%E6%8C%87%E5%BC%95/%E5%BF%AB%E9%80%9F%E5%BC%80%E5%A7%8B.md)
+更详细的模型支持列表 👉  [快速开始.md](docs/source_zh/使用指引/快速开始.md)
 
 ## 示例代码
 

docs/README.md

@@ -10,7 +10,7 @@
     We adopt the google style docstring format as the standard, please refer to the following documents.
     1. Google Python style guide docstring [link](http://google.github.io/styleguide/pyguide.html#381-docstrings)
     2. Google docstring example [link](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html)
-    3. sample：torch.nn.modules.conv [link](https://pytorch.org/docs/stable/_modules/torch/nn/modules/conv.html#Conv1d)
+    3. sample：torch.nn.modules.conv [link](https://docs.pytorch.org/docs/stable/generated/torch.nn.Conv1d.html)
     4. load function as an example：
 
     ```python

docs/source_en/Usage Guide/NPU-Support.md

@@ -6,13 +6,13 @@ This document describes how to install and use the Twinkle framework in Huawei A
 
 Before getting started, please ensure your system meets the following requirements:
 
-| Component | Version Requirement | Description |
-|------|---------|------|
-| Python | >= 3.11, < 3.13 | Twinkle framework requirement |
-| Ascend Firmware Driver (HDK) | Latest version recommended | Hardware driver and firmware |
-| CANN Toolkit | 8.3.RC1 or higher | Heterogeneous Computing Architecture |
-| PyTorch | 2.7.1 | Deep learning framework |
-| torch_npu | 2.7.1 | Ascend PyTorch adapter plugin |
+| Component                    | Version Requirement        | Description                          |
+|------------------------------|----------------------------|--------------------------------------|
+| Python                       | >= 3.11, < 3.13            | Twinkle framework requirement        |
+| Ascend Firmware Driver (HDK) | Latest version recommended | Hardware driver and firmware         |
+| CANN Toolkit                 | 8.3.RC1 or higher          | Heterogeneous Computing Architecture |
+| PyTorch                      | 2.7.1                      | Deep learning framework              |
+| torch_npu                    | 2.7.1                      | Ascend PyTorch adapter plugin        |
 
 **Important Notes**:
 - torch and torch_npu versions **must be exactly the same** (e.g., both 2.7.1)

tests/docs/__init__.py

@@ -0,0 +1 @@
+# Copyright (c) ModelScope Contributors. All rights reserved.