书生开源大模型-第2讲-笔记

1.环境准备

1.1环境

先克隆我们的环境

bash /root/share/install_conda_env_internlm_base.sh internlm-demo

1.2 模型参数

下载或者复制下来，开发机中已经有一份参数了

mkdir -p /root/model/Shanghai_AI_Laboratorycp -r /root/share/temp/model_repos/internlm-chat-7b /root/model/Shanghai_AI_Laboratory

# 下载会慢些import torchfrom modelscope import snapshot_download, AutoModel, AutoTokenizerimport osmodel_dir = snapshot_download('Shanghai_AI_Laboratory/internlm-chat-7b', cache_dir='/root/model', revision='v1.0.3')

注意这里复制好参数后，在下面的代码中要替换成我们自己的模型参数位置。

web_demo中lode_model方法

def load_model():model = (AutoModelForCausalLM.from_pretrained("/root/model/Shanghai_AI_Laboratory/internlm-chat-7b", trust_remote_code=True).to(torch.bfloat16).cuda())tokenizer = AutoTokenizer.from_pretrained("/root/model/Shanghai_AI_Laboratory/internlm-chat-7b", trust_remote_code=True)return model, tokenizer

1.3代码

从github上clone模型代码以及创建一个demo

cd /root/codegit clone https://gitee.com/internlm/InternLM.git# 切换 commit 版本，与教程 commit 版本保持一致，可以让大家更好的复现。cd InternLMgit checkout 3028f07cb79e5b1d7342f4ad8d11efad3fd13d17

demo

import torchfrom transformers import AutoTokenizer, AutoModelForCausalLMmodel_name_or_path = "/root/model/Shanghai_AI_Laboratory/internlm-chat-7b"tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype=torch.bfloat16, device_map='auto')model = model.eval()system_prompt = """You are an AI assistant whose name is InternLM (书生·浦语).- 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.- InternLM (书生·浦语) can understand and communicate fluently in the language chosen by the user such as English and 中文."""messages = [(system_prompt, '')]print("=============Welcome to InternLM chatbot, type 'exit' to exit.=============")while True:input_text = input("User>>> ")input_text = input_text.replace(' ', '')if input_text == "exit":breakresponse, history = model.chat(tokenizer, input_text, history=messages)messages.append((input_text, response))print(f"robot >>> {response}")

2.web_demo

在我们本机上去运行一个demo。

2.1 SSH

首先创建我们的ssh密钥。（一直敲回车让他默认位置即可

ssh-keygen -t rsa

完成后使用cat ~\.ssh\id_rsa.pub即可查看。

我们将其全部复制下来，然后回到 InternStudio 控制台，点击配置 SSH Key。

然后根据控制台上的端口号使用如下命令即可链接

ssh -CNg -L 6006:127.0.0.1:6006 root@ssh.intern-ai.org.cn -p {端口号}

2.2 运行

终端中输入

streamlit run web_demo.py --server.address 127.0.0.1 --server.port 6006

等待模型加载即可

3.Lagent 智能体工具调用 Demo

3.1环境准备

跟1.1中一样

3.2 模型

cd /root/codegit clone https://gitee.com/internlm/lagent.gitcd /root/code/lagentgit checkout 511b03889010c4811b1701abb153e02b8e94fb5e # 尽量保证和教程commit版本一致pip install -e . # 源码安装

3.3修改代码

应该做的也是修改模型参数文件

import copyimport osimport streamlit as stfrom streamlit.logger import get_loggerfrom lagent.actions import ActionExecutor, GoogleSearch, PythonInterpreterfrom lagent.agents.react import ReActfrom lagent.llms import GPTAPIfrom lagent.llms.huggingface import HFTransformerCasualLMclass SessionState:def init_state(self):"""Initialize session state variables."""st.session_state['assistant'] = []st.session_state['user'] = []#action_list = [PythonInterpreter(), GoogleSearch()]action_list = [PythonInterpreter()]st.session_state['plugin_map'] = {action.name: actionfor action in action_list}st.session_state['model_map'] = {}st.session_state['model_selected'] = Nonest.session_state['plugin_actions'] = set()def clear_state(self):"""Clear the existing session state."""st.session_state['assistant'] = []st.session_state['user'] = []st.session_state['model_selected'] = Noneif 'chatbot' in st.session_state:st.session_state['chatbot']._session_history = []class StreamlitUI:def __init__(self, session_state: SessionState):self.init_streamlit()self.session_state = session_statedef init_streamlit(self):"""Initialize Streamlit's UI settings."""st.set_page_config(layout='wide',page_title='lagent-web',page_icon='./docs/imgs/lagent_icon.png')# st.header(':robot_face: :blue[Lagent] Web Demo ', divider='rainbow')st.sidebar.title('模型控制')def setup_sidebar(self):"""Setup the sidebar for model and plugin selection."""model_name = st.sidebar.selectbox('模型选择：', options=['gpt-3.5-turbo','internlm'])if model_name != st.session_state['model_selected']:model = self.init_model(model_name)self.session_state.clear_state()st.session_state['model_selected'] = model_nameif 'chatbot' in st.session_state:del st.session_state['chatbot']else:model = st.session_state['model_map'][model_name]plugin_name = st.sidebar.multiselect('插件选择',options=list(st.session_state['plugin_map'].keys()),default=[list(st.session_state['plugin_map'].keys())[0]],)plugin_action = [st.session_state['plugin_map'][name] for name in plugin_name]if 'chatbot' in st.session_state:st.session_state['chatbot']._action_executor = ActionExecutor(actions=plugin_action)if st.sidebar.button('清空对话', key='clear'):self.session_state.clear_state()uploaded_file = st.sidebar.file_uploader('上传文件', type=['png', 'jpg', 'jpeg', 'mp4', 'mp3', 'wav'])return model_name, model, plugin_action, uploaded_filedef init_model(self, option):"""Initialize the model based on the selected option."""if option not in st.session_state['model_map']:if option.startswith('gpt'):st.session_state['model_map'][option] = GPTAPI(model_type=option)else:st.session_state['model_map'][option] = HFTransformerCasualLM('/root/model/Shanghai_AI_Laboratory/internlm-chat-7b')return st.session_state['model_map'][option]def initialize_chatbot(self, model, plugin_action):"""Initialize the chatbot with the given model and plugin actions."""return ReAct(llm=model, action_executor=ActionExecutor(actions=plugin_action))def render_user(self, prompt: str):with st.chat_message('user'):st.markdown(prompt)def render_assistant(self, agent_return):with st.chat_message('assistant'):for action in agent_return.actions:if (action):self.render_action(action)st.markdown(agent_return.response)def render_action(self, action):with st.expander(action.type, expanded=True):st.markdown(" 插件:"# noqa E501+ action.type + '
',unsafe_allow_html=True)st.markdown(" 思考步骤:"# noqa E501+ action.thought + '
',unsafe_allow_html=True)if (isinstance(action.args, dict) and 'text' in action.args):st.markdown(" 执行内容:
",# noqa E501unsafe_allow_html=True)st.markdown(action.args['text'])self.render_action_results(action)def render_action_results(self, action):"""Render the results of action, including text, images, videos, andaudios."""if (isinstance(action.result, dict)):st.markdown(" 执行结果:
",# noqa E501unsafe_allow_html=True)if 'text' in action.result:st.markdown("" + action.result['text'] +'
',unsafe_allow_html=True)if 'image' in action.result:image_path = action.result['image']image_data = open(image_path, 'rb').read()st.image(image_data, caption='Generated Image')if 'video' in action.result:video_data = action.result['video']video_data = open(video_data, 'rb').read()st.video(video_data)if 'audio' in action.result:audio_data = action.result['audio']audio_data = open(audio_data, 'rb').read()st.audio(audio_data)def main():logger = get_logger(__name__)# Initialize Streamlit UI and setup sidebarif 'ui' not in st.session_state:session_state = SessionState()session_state.init_state()st.session_state['ui'] = StreamlitUI(session_state)else:st.set_page_config(layout='wide',page_title='lagent-web',page_icon='./docs/imgs/lagent_icon.png')# st.header(':robot_face: :blue[Lagent] Web Demo ', divider='rainbow')model_name, model, plugin_action, uploaded_file = st.session_state['ui'].setup_sidebar()# Initialize chatbot if it is not already initialized# or if the model has changedif 'chatbot' not in st.session_state or model != st.session_state['chatbot']._llm:st.session_state['chatbot'] = st.session_state['ui'].initialize_chatbot(model, plugin_action)for prompt, agent_return in zip(st.session_state['user'],st.session_state['assistant']):st.session_state['ui'].render_user(prompt)st.session_state['ui'].render_assistant(agent_return)# User input form at the bottom (this part will be at the bottom)# with st.form(key='my_form', clear_on_submit=True):if user_input := st.chat_input(''):st.session_state['ui'].render_user(user_input)st.session_state['user'].append(user_input)# Add file uploader to sidebarif uploaded_file:file_bytes = uploaded_file.read()file_type = uploaded_file.typeif 'image' in file_type:st.image(file_bytes, caption='Uploaded Image')elif 'video' in file_type:st.video(file_bytes, caption='Uploaded Video')elif 'audio' in file_type:st.audio(file_bytes, caption='Uploaded Audio')# Save the file to a temporary location and get the pathfile_path = os.path.join(root_dir, uploaded_file.name)with open(file_path, 'wb') as tmpfile:tmpfile.write(file_bytes)st.write(f'File saved at: {file_path}')user_input = '我上传了一个图像，路径为: {file_path}. {user_input}'.format(file_path=file_path, user_input=user_input)agent_return = st.session_state['chatbot'].chat(user_input)st.session_state['assistant'].append(copy.deepcopy(agent_return))logger.info(agent_return.inner_steps)st.session_state['ui'].render_assistant(agent_return)if __name__ == '__main__':root_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))root_dir = os.path.join(root_dir, 'tmp_dir')os.makedirs(root_dir, exist_ok=True)main()

3.4运行

与2.1中一样，先本机链接

ssh -CNg -L 6006:127.0.0.1:6006 root@ssh.intern-ai.org.cn -p {端口号}

然后远程终端运行即可

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

我尝试了上传一张简单方程的图片，但是似乎失败了，模型并不能理解图中内容。(图中是3+x=6)

4.浦语·灵笔图文理解创作 Demo

4.1环境

从本地克隆一个已有的pytorch 2.0.1 的环境

/root/share/install_conda_env_internlm_base.sh xcomposer-demo

接下来运行以下命令，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

4.2模型准备

复制比较快

mkdir -p /root/model/Shanghai_AI_Laboratorycp -r /root/share/temp/model_repos/internlm-xcomposer-7b /root/model/Shanghai_AI_Laboratory

4.3代码

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

4.4运行

cd /root/code/InternLM-XComposerpython examples/web_demo.py\--folder /root/model/Shanghai_AI_Laboratory/internlm-xcomposer-7b \--num_gpus 1 \--port 6006

可以自动生成内容，并自动寻找合适图片！

其中还有多模态对话demo

书生开源大模型-第2讲-笔记

1.环境准备

1.1环境

1.2 模型参数

1.3代码

2.web_demo

2.1 SSH

2.2 运行

3.Lagent 智能体工具调用 Demo

3.1环境准备

3.2 模型

3.3修改代码

3.4运行

4.浦语·灵笔图文理解创作 Demo

4.1环境

4.2模型准备

4.3代码

4.4运行

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书生开源大模型-第2讲-笔记

1.环境准备

1.1环境

1.2 模型参数

1.3代码

2.web_demo

2.1 SSH

2.2 运行

3.Lagent 智能体工具调用 Demo

3.1环境准备

3.2 模型

3.3修改代码

3.4运行

4.浦语·灵笔图文理解创作 Demo

4.1环境

4.2模型准备

4.3代码

4.4运行

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