First add

Contributors.md

+# Contributors
+None
\ No newline at end of file

LICENSE

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README.md

+# RoboBrain
+## 论文
+[RoboBrain: A Unified Brain Model for Robotic Manipulation from Abstract to Concrete](https://arxiv.org/abs/2502.21257)
+
+## 模型结构
+模型基于qwen2.5进行构建。
+<div align=center>
+    <img src="./doc/model.png"/>
+</div>
+
+## 算法原理
+在实际应用中，该模型首先生成详细的计划，然后将其拆分为子任务描述以执行具体的机器人任务。
+<div align=center>
+    <img src="./doc/methods.png"/>
+</div>
+
+## 环境配置
+### 硬件需求
+
+DCU型号：K100_AI,节点数量：1台,卡数：2 张。
+
+`-v 路径`、`docker_name`和`imageID`根据实际情况修改
+
+### Docker（方法一）
+```bash
+docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:vllm0.8.5-ubuntu22.04-dtk25.04-rc7-das1.5-py3.10-20250612-fixpy-rocblas0611-rc2
+docker run -it --shm-size 200g --network=host --name {docker_name} --privileged --device=/dev/kfd --device=/dev/dri --device=/dev/mkfd --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -u root -v /path/your_code_data/:/path/your_code_data/ -v /opt/hyhal/:/opt/hyhal/:ro {imageID} bash
+
+cd /your_code_path/robobrain_pytorch
+```
+
+### Dockerfile（方法二）
+```bash
+cd docker
+docker build --no-cache -t robobrain:latest .
+docker run -it --shm-size 200g --network=host --name {docker_name} --privileged --device=/dev/kfd --device=/dev/dri --device=/dev/mkfd --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -u root -v /path/your_code_data/:/path/your_code_data/ -v /opt/hyhal/:/opt/hyhal/:ro {imageID} bash
+
+cd /your_code_path/robobrain_pytorch
+```
+
+### Anaconda（方法三）
+关于本项目DCU显卡所需的特殊深度学习库可从[光合](https://developer.sourcefind.cn/tool/)开发者社区下载安装。
+```bash
+DTK: 25.04
+python: 3.10
+vllm: 0.8.5
+torch: 2.4.1+das.opt2.dtk2504
+deepspeed: 0.14.2+das.opt2.dtk2504
+```
+`Tips：以上dtk驱动、python、torch等DCU相关工具版本需要严格一一对应`
+
+## 数据集
+无
+
+## 训练
+暂无
+
+## 推理
+### vllm推理方法
+#### server
+
+server启动
+```bash
+vllm serve BAAI/RoboBrain --served-model-name robobrain --max_model_len 16384 -tp 2 --limit_mm_per_prompt image=2
+```
+
+client访问
+```bash
+python client.py
+```
+
+## result
+<div align=center>
+    <img src="./doc/results-dcu.png"/>
+</div>
+
+### 精度
+DCU与GPU精度一致，推理框架：vllm。
+
+## 应用场景
+### 算法类别
+文本理解
+
+### 热点应用行业
+制造,广媒,家居,教育
+
+## 预训练权重
+- [BAAI/RoboBrain](https://huggingface.co/BAAI/RoboBrain)
+
+## 源码仓库及问题反馈
+- https://developer.sourcefind.cn/codes/modelzoo/robobrain_pytorch
+
+## 参考资料
+- https://github.com/FlagOpen/RoboBrain.git

client.py

+import argparse
+import base64
+
+from openai import OpenAI
+from vllm import LLM
+
+parse = argparse.ArgumentParser()
+parse.add_argument("--image_path", type=str, default="./doc/planning.png")
+parse.add_argument("--port", type=int, default=8000)
+args = parse.parse_args()
+
+
+if __name__ == "__main__":
+
+    openai_api_key = "robobrain-123123"
+    openai_api_base = f"http://127.0.0.1:{args.port}/v1"
+
+    client = OpenAI(
+        api_key=openai_api_key,
+        base_url=openai_api_base,
+    )
+
+    prompt = "Given the obiects in the image, if you are required to complete the task \"Put the apple in the basket\", what is your detailed plan? Write your plan and explain it in detail, using the following format: Step_1: xxx\nStep_2: xxx\n ...\nStep_n: xxx\n"
+
+
+    with open(args.image_path, "rb") as f:
+        encoded_image = base64.b64encode(f.read())
+        encoded_image = encoded_image.decode("utf-8")
+        base64_img = f"data:image;base64,{encoded_image}"
+    models = client.models.list()
+    model = models.data[0].id
+    response = client.chat.completions.create(
+        model=model,
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {"type": "image_url", "image_url": {"url": base64_img}},
+                    {"type": "text", "text": prompt},
+                ],
+            },
+        ],
+        temperature=0.1
+    )
+
+    content = response.choices[0].message.content
+    print(content)
+
+    '''
+    Prediction: (as an example)
+        Step_1: Move to the apple. Move towards the apple on the table.
+        Step_2: Pick up the apple. Grab the apple and lift it off the table.
+        Step_3: Move towards the basket. Move the apple towards the basket without dropping it.
+        Step_4: Put the apple in the basket. Place the apple inside the basket, ensuring it is in a stable position.
+    '''
\ No newline at end of file

docker/Dockerfile

+FROM image.sourcefind.cn:5000/dcu/admin/base/custom:vllm0.8.5-ubuntu22.04-dtk25.04-rc7-das1.5-py3.10-20250612-fixpy-rocblas0611-rc2
\ No newline at end of file

model.properties

+# 模型唯一标识
+modelCode=1628
+# 模型名称
+modelName=robobrain_pytorch
+# 模型描述
+modelDescription=迄今为止最强大的开源实体化大脑模型。
+# 应用场景
+appScenario=推理,对话问答,制造,广媒,家居,教育
+# 框架类型
+frameType=pytorch