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大模型实战营课程笔记 ②

作者：2023面试高手 | 2024-02-28 21:24:16

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大模型实战营课程笔记 ②

Demo 练习

一、环境搭建

1、创建开发机

2、添加镜像

3、选择资源

4、创建完成后进入开发机

5、用bash命令，进入conda环境

6、用以下命令，克隆一个已有的pytorch 2.0.1的环境

conda create --name internlm-demo --clone=/root/share/conda_envs/internlm-base

7、激活环境

conda activate internlm-demo

8、在环境中安装运行demo所需的依赖

  1. # 升级pip
  2. python -m pip install --upgrade pip
  3.  
  4. pip install modelscope==1.9.5
  5. pip install transformers==4.35.2
  6. pip install streamlit==1.24.0
  7. pip install sentencepiece=0.1.99
  8. pip install accelerate==0.24.1

二、模型下载

InternStudio平台的share目录已经准备了全系列的InternLM模型，可以直接复制

  1. mkdir -p /root/model/Shanghai_AI_Laboratory
  2. cp -r /root/share/temp/model_repos/internlm-chat-7b /root/model/Shanghai_AI_Laboratory

三、代码准备

在 /root 路径下新建 code 目录，然后切换路径，clone代码

  1. cd /root/code
  2. git clone http://gitee.com/internlm/InternLM.git

切换commit版本，与教程commit版本保持一致

  1. cd InternLM
  2. git checkout 3028f07cb79e5b1d7342f4ad8d11efad3fd13d17

将 /root/code/InternLM/web_demo.py中29行和33行模型更换为本地的 /root/model/Shanghai_AI_Laboratory/internlm-chat-7b

用ctrl+s进行保存

四、终端运行

打开vscode, 在 /root/code/InternLM 目录下新建一个 cli_demo.py文件

填入以下代码

  1. import torch
  2. from transformers import AutoTokenizer, AutoModelForCausalLM
  3.  
  4.  
  5. model_name_or_path = "/root/model/Shanghai_AI_Laboratory/internlm-chat-7b"
  6.  
  7. tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
  8. model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype=torch.bfloat16, device_map='auto')
  9. model = model.eval()
  10.  
  11. system_prompt = """You are an AI assistant whose name is InternLM (书生·浦语).
  12. - InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.
  13. - InternLM (书生·浦语) can understand and communicate fluently in the language chosen by the user such as English and 中文.
  14. """
  15.  
  16. messages = [(system_prompt, '')]
  17.  
  18. print("=============Welcome to InternLM chatbot, type 'exit' to exit.=============")
  19.  
  20. while True:
  21.     input_text = input("User  >>> ")
  22.     input_text = input_text.replace(' ', '')
  23.     if input_text == "exit":
  24.         break
  25.     response, history = model.chat(tokenizer, input_text, history=messages)
  26.     messages.append((input_text, response))
  27.     print(f"robot >>> {response}")

 运行终端，切换internlm-demo环境。

  1. bash
  2. conda info -e
  3. conda activate internlm-demo

复制以下命令，运行

python /root/code/InternLM/cli_demo.py

 发现报错，ModuleNotFoundError: No module named ‘sentencepiece‘

说明在当前的 Python 环境中缺少名为 sentencepiece 的模块，导致 Python 找不到该模块。

sentencepiece 是一个 Python 第三方模块，用于自然语言处理（NLP）任务中的分词和词嵌入。要解决这个错误，需要安装 sentencepiece 模块。你可以通过以下命令使用 pip 安装 sentencepiece：

pip install sentencepiece

 安装好后，重新运行“python /root/code/InternLM/cli_demo.py”即可。输入exit可退出终端。

 五、web demo运行

1、配置本地端口

打开本地power shell 终端，运行以下命令来生成 SSH 密钥对

ssh-keygen -t rsa

被提示选择密钥文件的保存位置，默认情况下是在 ~/.ssh/ 目录中。按 Enter 键接受默认值或输入自定义路径 。

公钥默认存储在 ~/.ssh/id_rsa.pub，可以通过系统自带的 cat 工具查看文件内容：（如下图所示）

cat ~\.ssh\id_rsa.pub

将公钥复制到剪贴板中，然后回到 InternStudio 控制台，点击配置 SSH Key。 (注意不能有中文)

 2、点击“开发机”下的“SSH链接”查看端口号 *****（五位数字）在本地终端输入以下命令，并更改新的端口号。注意3390换成自己端口号，最小化。

ssh -CNg -L 6006:127.0.0.1:6006 root@ssh.intern-ai.org.cn -p 33090

3、运行web demo

切换到vscode界面，运行/root/code/InternLM目录下的web_demo.py文件，然后，按住ctrl+网址链接，就可以打开网页。

  1. bash
  2. conda activate internlm-demo  # 首次进入 vscode 会默认是 base 环境，所以首先切换环境
  3. cd /root/code/InternLM
  4. streamlit run web_demo.py --server.address 127.0.0.1 --server.port 6006

打开链接后，模型才会加载，速度稍微有些慢。

六、Lagent智能体工具调用Demo

1、环境准备、模型下载（同上一、二，若已完成，不需要重新安装）

2、Lagent安装

切换路径到/root/code 克隆lagent仓库，切换commit ID,安装。

  1. cd /root/code
  2. git clone https://gitee.com/internlm/lagent.git
  3. cd /root/code/lagent
  4. git checkout 511b03889010c4811b1701abb153e02b8e94fb5e # 尽量保证和教程commit版本一致
  5. pip install -e . # 源码安装

这个警告不用管，直接成功完成安装。注意：源码安装，那里最后有一个“.”。

3、修改目录

直接将以下内容替换进/root/code/lagent/examples/react_web_demo.py

  1. import copy
  2. import os
  3.  
  4. import streamlit as st
  5. from streamlit.logger import get_logger
  6.  
  7. from lagent.actions import ActionExecutor, GoogleSearch, PythonInterpreter
  8. from lagent.agents.react import ReAct
  9. from lagent.llms import GPTAPI
  10. from lagent.llms.huggingface import HFTransformerCasualLM
  11.  
  12.  
  13. class SessionState:
  14.  
  15.     def init_state(self):
  16.         """Initialize session state variables."""
  17.         st.session_state['assistant'] = []
  18.         st.session_state['user'] = []
  19.  
  20.         #action_list = [PythonInterpreter(), GoogleSearch()]
  21.         action_list = [PythonInterpreter()]
  22.         st.session_state['plugin_map'] = {
  23.             action.name: action
  24.             for action in action_list
  25.         }
  26.         st.session_state['model_map'] = {}
  27.         st.session_state['model_selected'] = None
  28.         st.session_state['plugin_actions'] = set()
  29.  
  30.     def clear_state(self):
  31.         """Clear the existing session state."""
  32.         st.session_state['assistant'] = []
  33.         st.session_state['user'] = []
  34.         st.session_state['model_selected'] = None
  35.         if 'chatbot' in st.session_state:
  36.             st.session_state['chatbot']._session_history = []
  37.  
  38.  
  39. class StreamlitUI:
  40.  
  41.     def __init__(self, session_state: SessionState):
  42.         self.init_streamlit()
  43.         self.session_state = session_state
  44.  
  45.     def init_streamlit(self):
  46.         """Initialize Streamlit's UI settings."""
  47.         st.set_page_config(
  48.             layout='wide',
  49.             page_title='lagent-web',
  50.             page_icon='./docs/imgs/lagent_icon.png')
  51.         # st.header(':robot_face: :blue[Lagent] Web Demo ', divider='rainbow')
  52.         st.sidebar.title('模型控制')
  53.  
  54.     def setup_sidebar(self):
  55.         """Setup the sidebar for model and plugin selection."""
  56.         model_name = st.sidebar.selectbox(
  57.             '模型选择：', options=['gpt-3.5-turbo','internlm'])
  58.         if model_name != st.session_state['model_selected']:
  59.             model = self.init_model(model_name)
  60.             self.session_state.clear_state()
  61.             st.session_state['model_selected'] = model_name
  62.             if 'chatbot' in st.session_state:
  63.                 del st.session_state['chatbot']
  64.         else:
  65.             model = st.session_state['model_map'][model_name]
  66.  
  67.         plugin_name = st.sidebar.multiselect(
  68.             '插件选择',
  69.             options=list(st.session_state['plugin_map'].keys()),
  70.             default=[list(st.session_state['plugin_map'].keys())[0]],
  71.         )
  72.  
  73.         plugin_action = [
  74.             st.session_state['plugin_map'][name] for name in plugin_name
  75.         ]
  76.         if 'chatbot' in st.session_state:
  77.             st.session_state['chatbot']._action_executor = ActionExecutor(
  78.                 actions=plugin_action)
  79.         if st.sidebar.button('清空对话', key='clear'):
  80.             self.session_state.clear_state()
  81.         uploaded_file = st.sidebar.file_uploader(
  82.             '上传文件', type=['png', 'jpg', 'jpeg', 'mp4', 'mp3', 'wav'])
  83.         return model_name, model, plugin_action, uploaded_file
  84.  
  85.     def init_model(self, option):
  86.         """Initialize the model based on the selected option."""
  87.         if option not in st.session_state['model_map']:
  88.             if option.startswith('gpt'):
  89.                 st.session_state['model_map'][option] = GPTAPI(
  90.                     model_type=option)
  91.             else:
  92.                 st.session_state['model_map'][option] = HFTransformerCasualLM(
  93.                     '/root/model/Shanghai_AI_Laboratory/internlm-chat-7b')
  94.         return st.session_state['model_map'][option]
  95.  
  96.     def initialize_chatbot(self, model, plugin_action):
  97.         """Initialize the chatbot with the given model and plugin actions."""
  98.         return ReAct(
  99.             llm=model, action_executor=ActionExecutor(actions=plugin_action))
  100.  
  101.     def render_user(self, prompt: str):
  102.         with st.chat_message('user'):
  103.             st.markdown(prompt)
  104.  
  105.     def render_assistant(self, agent_return):
  106.         with st.chat_message('assistant'):
  107.             for action in agent_return.actions:
  108.                 if (action):
  109.                     self.render_action(action)
  110.             st.markdown(agent_return.response)
  111.  
  112.     def render_action(self, action):
  113.         with st.expander(action.type, expanded=True):
  114.             st.markdown(
  115.                 "<p style='text-align: left;display:flex;'> <span style='font-size:14px;font-weight:600;width:70px;text-align-last: justify;'>插    件</span><span style='width:14px;text-align:left;display:block;'>:</span><span style='flex:1;'>"  # noqa E501
  116.                 + action.type + '</span></p>',
  117.                 unsafe_allow_html=True)
  118.             st.markdown(
  119.                 "<p style='text-align: left;display:flex;'> <span style='font-size:14px;font-weight:600;width:70px;text-align-last: justify;'>思考步骤</span><span style='width:14px;text-align:left;display:block;'>:</span><span style='flex:1;'>"  # noqa E501
  120.                 + action.thought + '</span></p>',
  121.                 unsafe_allow_html=True)
  122.             if (isinstance(action.args, dict) and 'text' in action.args):
  123.                 st.markdown(
  124.                     "<p style='text-align: left;display:flex;'><span style='font-size:14px;font-weight:600;width:70px;text-align-last: justify;'> 执行内容</span><span style='width:14px;text-align:left;display:block;'>:</span></p>",  # noqa E501
  125.                     unsafe_allow_html=True)
  126.                 st.markdown(action.args['text'])
  127.             self.render_action_results(action)
  128.  
  129.     def render_action_results(self, action):
  130.         """Render the results of action, including text, images, videos, and
  131.         audios."""
  132.         if (isinstance(action.result, dict)):
  133.             st.markdown(
  134.                 "<p style='text-align: left;display:flex;'><span style='font-size:14px;font-weight:600;width:70px;text-align-last: justify;'> 执行结果</span><span style='width:14px;text-align:left;display:block;'>:</span></p>",  # noqa E501
  135.                 unsafe_allow_html=True)
  136.             if 'text' in action.result:
  137.                 st.markdown(
  138.                     "<p style='text-align: left;'>" + action.result['text'] +
  139.                     '</p>',
  140.                     unsafe_allow_html=True)
  141.             if 'image' in action.result:
  142.                 image_path = action.result['image']
  143.                 image_data = open(image_path, 'rb').read()
  144.                 st.image(image_data, caption='Generated Image')
  145.             if 'video' in action.result:
  146.                 video_data = action.result['video']
  147.                 video_data = open(video_data, 'rb').read()
  148.                 st.video(video_data)
  149.             if 'audio' in action.result:
  150.                 audio_data = action.result['audio']
  151.                 audio_data = open(audio_data, 'rb').read()
  152.                 st.audio(audio_data)
  153.  
  154.  
  155. def main():
  156.     logger = get_logger(__name__)
  157.     # Initialize Streamlit UI and setup sidebar
  158.     if 'ui' not in st.session_state:
  159.         session_state = SessionState()
  160.         session_state.init_state()
  161.         st.session_state['ui'] = StreamlitUI(session_state)
  162.  
  163.     else:
  164.         st.set_page_config(
  165.             layout='wide',
  166.             page_title='lagent-web',
  167.             page_icon='./docs/imgs/lagent_icon.png')
  168.         # st.header(':robot_face: :blue[Lagent] Web Demo ', divider='rainbow')
  169.     model_name, model, plugin_action, uploaded_file = st.session_state[
  170.         'ui'].setup_sidebar()
  171.  
  172.     # Initialize chatbot if it is not already initialized
  173.     # or if the model has changed
  174.     if 'chatbot' not in st.session_state or model != st.session_state[
  175.             'chatbot']._llm:
  176.         st.session_state['chatbot'] = st.session_state[
  177.             'ui'].initialize_chatbot(model, plugin_action)
  178.  
  179.     for prompt, agent_return in zip(st.session_state['user'],
  180.                                     st.session_state['assistant']):
  181.         st.session_state['ui'].render_user(prompt)
  182.         st.session_state['ui'].render_assistant(agent_return)
  183.     # User input form at the bottom (this part will be at the bottom)
  184.     # with st.form(key='my_form', clear_on_submit=True):
  185.  
  186.     if user_input := st.chat_input(''):
  187.         st.session_state['ui'].render_user(user_input)
  188.         st.session_state['user'].append(user_input)
  189.         # Add file uploader to sidebar
  190.         if uploaded_file:
  191.             file_bytes = uploaded_file.read()
  192.             file_type = uploaded_file.type
  193.             if 'image' in file_type:
  194.                 st.image(file_bytes, caption='Uploaded Image')
  195.             elif 'video' in file_type:
  196.                 st.video(file_bytes, caption='Uploaded Video')
  197.             elif 'audio' in file_type:
  198.                 st.audio(file_bytes, caption='Uploaded Audio')
  199.             # Save the file to a temporary location and get the path
  200.             file_path = os.path.join(root_dir, uploaded_file.name)
  201.             with open(file_path, 'wb') as tmpfile:
  202.                 tmpfile.write(file_bytes)
  203.             st.write(f'File saved at: {file_path}')
  204.             user_input = '我上传了一个图像，路径为: {file_path}. {user_input}'.format(
  205.                 file_path=file_path, user_input=user_input)
  206.         agent_return = st.session_state['chatbot'].chat(user_input)
  207.         st.session_state['assistant'].append(copy.deepcopy(agent_return))
  208.         logger.info(agent_return.inner_steps)
  209.         st.session_state['ui'].render_assistant(agent_return)
  210.  
  211.  
  212. if __name__ == '__main__':
  213.     root_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
  214.     root_dir = os.path.join(root_dir, 'tmp_dir')
  215.     os.makedirs(root_dir, exist_ok=True)
  216.     main()

4、连接SSH

打开本地power shell 终端。在本地终端输入以下命令，并更改新的端口号。注意3390换成自己端口号，最小化。

ssh -CNg -L 6006:127.0.0.1:6006 root@ssh.intern-ai.org.cn -p 33090

5、Demo运行

streamlit run /root/code/lagent/examples/react_web_demo.py --server.address 127.0.0.1 --server.port 6006

按住ctrl打开浏览器连接。注意模型选择 InrernLM

关闭网页，然后回到vs code，按住ctrl+c 可以关掉Lagent智能体工具调用Demo。

6、查看GPU占用

vgpu-smi

七、浦语·灵笔图文理解创作Demo

1、新建一个新的开发机，配置为A100（1/4）*2。选择镜像和资源配置，如下图所示：

2、进入开发机，进入vs code。打开Terminal终端，“bash”进入conda环境，查看当前虚拟环境。

3、使用以下命令，从本地克隆一个已有的pytorch 2.0.1的环境

conda create --name xcomposer-demo --clone=/root/share/conda_envs/internlm-base

4、用一下命令切换环境

conda activate xcomposer-demo

5、用以下命令，安装transformers、gradio等依赖包

pip install transformers==4.33.1 timm==0.4.12 sentencepiece==0.1.99 gradio==3.44.4 markdown2==2.4.10 xlsxwriter==3.1.2 einops accelerate

(上面error和warning不用管)

6、模型下载

  1. mkdir -p /root/model/Shanghai_AI_Laboratory
  2. cp -r /root/share/temp/model_repos/internlm-xcomposer-7b /root/model/Shanghai_AI_Laboratory

7、代码准备

在/root/code git clone InternLM-XComposer仓库代码

  1. cd /root/code
  2. git clone https://gitee.com/internlm/InternLM-XComposer.git
  3. cd /root/code/InternLM-XComposer
  4. git checkout 3e8c79051a1356b9c388a6447867355c0634932d  # 最好保证和教程的 commit 版本一致

8、demo 运行

在终端运行以下代码

  1. cd /root/code/InternLM-XComposer
  2. python examples/web_demo.py  \
  3.     --folder /root/model/Shanghai_AI_Laboratory/internlm-xcomposer-7b \
  4.     --num_gpus 1 \
  5.     --port 6006

9、配置本地端口（同上）

然后点住ctrl打开网址可以看见浦语的网页，但我这里好像有些问题……

这里是渲染问题，解决方法是在web_demo.py里修改代码

demo.launch(share=True, server_name="0.0.0.0", server_port=6006, root_path=f'/proxy/6006/')

右边可以直接换图片或者换文字。

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