1. System字段添加了药品信息查询的功能

2. 模型路径更新 3. DR0代表健康改为非糖尿病视网膜病变 4. 将cuda版本信息检测放到app.py,避免多次执行
AIzealotwu · Mar 3, 2024 · 6cce9e8 · 6cce9e8
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diff --git a/README.md b/README.md
@@ -49,7 +49,7 @@ Demo访问地址: [OculiChatDA](https://openxlab.org.cn/apps/detail/helloworld/O
 ## 模型
 | 模型                  | 基座                | 数据量               | OpenXLab                                                                             
 |---------------------|-------------------|-------------------|----------------------------------------------------------------------------------------|
-| OculiChatDA-chat-7b | InternLM2-chat-7b | 500K个对话，对话轮次为1～64 | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/helloworld/OculiChatDA) |
+| OculiChatDA-chat-7b | InternLM2-chat-7b | 500K个对话，对话轮次为1～64 | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/flyer/OculiChatDA) |
 
 ## 环境安装
 ```bash
@@ -135,7 +135,7 @@ xtuner chat ./merged --prompt-template internlm2_chat
 
 继续输入:
 
-    我上传了一张图片，图片路径为/a/b/c.jpg 情判断我是否患有青光眼
+    我上传了一张图片，图片路径为/a/b/c.jpg q请判断我是否患有青光眼
 
 模型输出:
 
@@ -154,6 +154,14 @@ lmdeploy convert internlm2-chat-7b  ./merged
 lmdeploy serve api_server ./workspace --server-name 0.0.0.0 --server-port 23333 --tp 1
 ```
 
+## 模型上传
+```bash
+python model_upload/convert.py
+openxlab login
+cd merged
+openxlab model create --model-repo='flyer/OculiChatDA' -s ./metafile.yml
+
+```
 ## Web Demo
 ```bash
 streamlit run web_demo.py --server.address=0.0.0.0 --server.port 7860 --server.enableStaticServing True

diff --git a/app.py b/app.py
@@ -1,12 +1,13 @@
 import os
 import time
-
+import torch
 # os.system("pip install torch==2.0.0 torchvision==0.15.1 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu118")
 
 MODEL_DIR = "models/"
-MODEL_REPOSITORY_OPENXLAB = "OpenLMLab/internlm2-chat-7b"
+MODEL_REPOSITORY_OPENXLAB = "flyer/OculiChatDA"
 
 if __name__ == '__main__':
+    print("服务器cuda版本检测：")
     os.system("ls /usr/local")
     if not os.path.exists(MODEL_DIR):
         from openxlab.model import download
@@ -16,6 +17,13 @@
         print("解压后目录结果如下：")
         print(os.listdir(MODEL_DIR))
         os.system(f"lmdeploy convert internlm2-chat-7b {MODEL_DIR}")
+
+    print("torch.cuda.is_available():", torch.cuda.is_available())
+    print("torch.__version__:", torch.__version__)
+    print("torch.version.cuda:", torch.version.cuda)
+    print("torch.cuda.get_device_name(0):", torch.cuda.get_device_name(0))
+    print("nvidia-smi:", os.popen('nvidia-smi').read())
+
     os.system("lmdeploy serve api_server ./workspace --server-name 0.0.0.0 --server-port 23333 --tp 1 --cache-max-entry-count 0.5 &")
     time.sleep(5)
     os.system('streamlit run web_demo.py --server.address=0.0.0.0 --server.port 7860 --server.enableStaticServing True --server.enableStaticServing true')
diff --git a/model_upload/convert.py b/model_upload/convert.py
@@ -0,0 +1,28 @@
+import sys
+import os
+import ruamel.yaml
+
+mstr = ruamel.yaml.scalarstring.DoubleQuotedScalarString
+
+MODEL_DIR = "../merged/"
+yaml = ruamel.yaml.YAML()
+yaml.preserve_quotes = True
+yaml.default_flow_style = False
+file_name = 'metafile.yml'
+# 读取YAML文件内容
+with open(file_name, 'r') as file:
+    data = yaml.load(file)
+data['Models'] = []
+for file in os.listdir(MODEL_DIR):
+    if file == "metafile.yml": continue
+    data['Models'].append({
+        "Name": mstr(file),
+        "Results": [dict(Task=mstr("Text Generation"), Dataset=mstr("none"))],
+        "Weights": mstr(file),
+    })
+
+# 将修改后的数据写回文件
+with open(os.path.join(MODEL_DIR, file_name), 'w') as file:
+    yaml.dump(data, file)
+
+print("Modifications saved to the file.")
diff --git a/model_upload/metafile.yml b/model_upload/metafile.yml
@@ -0,0 +1,76 @@
+Collections:
+- Name: "OculiChatDA"
+  License: "Apache-2.0"
+  Framework: "[]"
+  Paper: {}
+  Code:
+    URL: "https://github.com/JieGenius/OculiChatDA"
+Models:
+- Name: "config.json"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "configuration_internlm.py"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "generation_config.json"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "modeling_internlm2.py"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00001-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00002-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00003-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00004-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00005-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00006-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00007-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model-00008-of-00008.bin"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "special_tokens_map.json"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "tokenization_internlm.py"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "tokenizer_config.json"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "tokenizer.model"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
+- Name: "pytorch_model.bin.index.json"
+  Results:
+  - Task: "Text Generation"
+    Dataset: "none"
diff --git a/requirements.txt b/requirements.txt
@@ -1,7 +1,5 @@
 pandas
 python-docx
-# torch
-# torchvision
 modelscope
 transformers
 xtuner[all]
@@ -10,3 +8,7 @@ streamlit
 lagent==0.2.2
 onnxruntime-gpu
 openxlab
+# torch==2.0.0+cu118
+# torchvision==0.15.1+cu118
+# torchaudio
+# --index-url https://download.pytorch.org/whl/cu118
diff --git a/utils/actions/fundus_diagnosis.py b/utils/actions/fundus_diagnosis.py
@@ -36,7 +36,7 @@ def fundus_diagnosis(self, fundus_path: str) -> dict:
               * msg (str): 工具调用是否成功的说明
               * glaucoma (int): 1代表可疑青光眼，0代表非青光眼
               * dr_level (int): 糖尿病视网膜病变的等级，0代表健康，4代表患病程度最严重
-                                0 为健康
+                                0 为非糖尿病视网膜病变
                                 1 代表轻度非增生性的糖尿病视网膜病变
                                 2 中度
                                 3 重度

diff --git a/web_demo.py b/web_demo.py
@@ -13,13 +13,18 @@
 from lagent.llms.meta_template import INTERNLM2_META as META
 from lagent.schema import AgentStatusCode
 from utils.actions.fundus_diagnosis import FundusDiagnosis
-
+import base64
 # from streamlit.logger import get_logger
 LMDEPLOY_IP = "0.0.0.0:23333"
 MODEL_NAME = "internlm2-chat-7b"
 
 OculiChatDA_META_CN = ("你是一名眼科专家，可以通过文字和图片来帮助用户诊断眼睛的状态。\n"
                        "你的工作单位为**某三家医院**\n"
+                       "你有以下三种能力:\n"
+                       "1. 诊断眼底疾病，包括青光眼和糖尿病视网膜病变\n"
+                       "2. 眼科常见疾病诊断，疾病解答，疾病预防等\n"
+                       "3. 眼科药品信息查询\n" 
+                       "你可以主动询问用户基本信息，比如年龄，用眼频率，用眼环境等等，请时刻保持耐心且细致的回答"
                        "你可以调用外部工具来帮助帮助用户解决问题")
 OculiChatDA_META_CN = OculiChatDA_META_CN  # + "\n".join(ReActCALL_PROTOCOL_CN.split("\n")[1:])
 PLUGIN_CN = """你可以使用如下工具：
@@ -165,7 +170,7 @@ def render_user(self, prompt: str):
         with st.chat_message('user'):
             img_paths = re.findall(r'\!\[.*?\]\((.*?)\)', prompt, re.DOTALL)  # 允许皮配\n等空字符
             if len(img_paths):
-                st.markdown(re.sub(r'!\[.*\]\(.*\)', '', prompt))  # 先渲染非图片部分
+                st.markdown(re.sub(r'!\[.*\]\(.*\)', '', prompt.replace("\\n", " \\n ")))  # 先渲染非图片部分
                 # 再渲染图片
                 img_path = img_paths[0]
                 st.write(
@@ -175,7 +180,7 @@ def render_user(self, prompt: str):
                 # if os.path.exists(img_path):
                 #     st.image(open(img_path, 'rb').read(), caption='Uploaded Image', width=400)
             else:
-                st.markdown(prompt)
+                st.markdown(prompt.replace("\\n", " \\n "))
 
     def render_assistant(self, agent_return):
         with st.chat_message('assistant'):
@@ -284,7 +289,7 @@ def main():
             file_bytes = uploaded_file.read()
             file_type = uploaded_file.type
             if 'image' in file_type:
-                st.image(file_bytes, caption='Uploaded Image')
+                st.image(file_bytes, caption='Uploaded Image', width=600)
             elif 'video' in file_type:
                 st.video(file_bytes, caption='Uploaded Video')
             elif 'audio' in file_type:
@@ -356,11 +361,6 @@ def main():
 
 
 if __name__ == '__main__':
-    print("torch.cuda.is_available():", torch.cuda.is_available())
-    print("torch.__version__:", torch.__version__)
-    print("torch.version.cuda:", torch.version.cuda)
-    print("torch.cuda.get_device_name(0):", torch.cuda.get_device_name(0))
-    print("nvidia-smi:", os.popen('nvidia-smi').read())
     root_dir = 'static'
     os.makedirs(root_dir, exist_ok=True)
-    main()
+    main()