update

Dockerfile

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+# 使用官方的Python运行时作为父镜像
+FROM python:3.10-slim
+
+# 设置工作目录
+WORKDIR /app
+
+# 安装 Conda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \
+    && bash miniconda.sh -b -p /opt/conda \
+    && rm miniconda.sh \
+    && /opt/conda/bin/conda update conda -y \
+    && /opt/conda/bin/conda clean -tipsy
+
+# 将 Conda 添加到 PATH
+ENV PATH="/opt/conda/bin:${PATH}"
+
+# 创建 Conda 环境
+RUN conda create -n lagent python=3.10 -y
+
+# 激活 Conda 环境
+SHELL ["conda", "run", "-n", "lagent", "/bin/bash", "-c"]
+
+# 安装 PyTorch 和其他依赖项
+RUN conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 -c pytorch -c nvidia -y
+RUN pip install termcolor==2.4.0 streamlit==1.39.0 class_registry==2.1.2 datasets==3.1.0
+
+# 克隆代码仓库
+RUN git clone https://github.com/InternLM/lagent.git
+WORKDIR /app/lagent
+RUN git checkout e304e5d
+RUN pip install -e .
+WORKDIR /app
+
+# 安装 griffe
+RUN pip install griffe==0.48.0
+
+# 拷贝应用代码到工作目录
+COPY . /app
+
+# 暴露端口
+EXPOSE 8501
+
+# 运行命令
+CMD ["streamlit", "run", "app.py"]

app.py

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+import copy
+import os
+from typing import List
+import streamlit as st
+from lagent.actions import ArxivSearch
+from lagent.prompts.parsers import PluginParser
+from lagent.agents.stream import INTERPRETER_CN, META_CN, PLUGIN_CN, AgentForInternLM, get_plugin_prompt
+from lagent.llms import GPTAPI
+
+class SessionState:
+    """管理会话状态的类。"""
+
+    def init_state(self):
+        """初始化会话状态变量。"""
+        st.session_state['assistant'] = []  # 助手消息历史
+        st.session_state['user'] = []  # 用户消息历史
+        # 初始化插件列表
+        action_list = [
+            ArxivSearch(),
+        ]
+        st.session_state['plugin_map'] = {action.name: action for action in action_list}
+        st.session_state['model_map'] = {}  # 存储模型实例
+        st.session_state['model_selected'] = None  # 当前选定模型
+        st.session_state['plugin_actions'] = set()  # 当前激活插件
+        st.session_state['history'] = []  # 聊天历史
+        st.session_state['api_base'] = None  # 初始化API base地址
+
+    def clear_state(self):
+        """清除当前会话状态。"""
+        st.session_state['assistant'] = []
+        st.session_state['user'] = []
+        st.session_state['model_selected'] = None
+
+
+class StreamlitUI:
+    """管理 Streamlit 界面的类。"""
+
+    def __init__(self, session_state: SessionState):
+        self.session_state = session_state
+        self.plugin_action = []  # 当前选定的插件
+        # 初始化提示词
+        self.meta_prompt = META_CN
+        self.plugin_prompt = PLUGIN_CN
+        self.init_streamlit()
+
+    def init_streamlit(self):
+        """初始化 Streamlit 的 UI 设置。"""
+        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')
+
+    def setup_sidebar(self):
+        """设置侧边栏，选择模型和插件。"""
+        # 模型名称和 API Base 输入框
+        model_name = st.sidebar.text_input('模型名称：', value='internlm2.5-latest')
+        
+        # ================================== 硅基流动的API ==================================
+        # 注意，如果采用硅基流动API，模型名称需要更改为：internlm/internlm2_5-7b-chat 或者 internlm/internlm2_5-20b-chat
+        # api_base = st.sidebar.text_input(
+        #     'API Base 地址：', value='https://api.siliconflow.cn/v1/chat/completions'
+        # )
+        # ================================== 浦语官方的API ==================================
+        api_base = st.sidebar.text_input(
+            'API Base 地址：', value='https://internlm-chat.intern-ai.org.cn/puyu/api/v1/chat/completions'
+        )
+        # ==================================================================================
+        # 插件选择
+        plugin_name = st.sidebar.multiselect(
+            '插件选择',
+            options=list(st.session_state['plugin_map'].keys()),
+            default=[],
+        )
+
+        # 根据选择的插件生成插件操作列表
+        self.plugin_action = [st.session_state['plugin_map'][name] for name in plugin_name]
+
+        # 动态生成插件提示
+        if self.plugin_action:
+            self.plugin_prompt = get_plugin_prompt(self.plugin_action)
+
+        # 清空对话按钮
+        if st.sidebar.button('清空对话', key='clear'):
+            self.session_state.clear_state()
+
+        return model_name, api_base, self.plugin_action
+
+    def initialize_chatbot(self, model_name, api_base, plugin_action):
+        """初始化 GPTAPI 实例作为 chatbot。"""
+        token = os.getenv("token")
+        if not token:
+            st.error("未检测到环境变量 `token`，请设置环境变量，例如 `export token='your_token_here'` 后重新运行 X﹏X")
+            st.stop()  # 停止运行应用
+            
+        # 创建完整的 meta_prompt，保留原始结构并动态插入侧边栏配置
+        meta_prompt = [
+            {"role": "system", "content": self.meta_prompt, "api_role": "system"},
+            {"role": "user", "content": "", "api_role": "user"},
+            {"role": "assistant", "content": self.plugin_prompt, "api_role": "assistant"},
+            {"role": "environment", "content": "", "api_role": "environment"}
+        ]
+
+        api_model = GPTAPI(
+            model_type=model_name,
+            api_base=api_base,
+            key=token,  # 从环境变量中获取授权令牌
+            meta_template=meta_prompt,
+            max_new_tokens=512,
+            temperature=0.8,
+            top_p=0.9
+        )
+        return api_model
+
+    def render_user(self, prompt: str):
+        """渲染用户输入内容。"""
+        with st.chat_message('user'):
+            st.markdown(prompt)
+
+    def render_assistant(self, agent_return):
+        """渲染助手响应内容。"""
+        with st.chat_message('assistant'):
+            content = getattr(agent_return, "content", str(agent_return))
+            st.markdown(content if isinstance(content, str) else str(content))
+
+
+def main():
+    """主函数，运行 Streamlit 应用。"""
+    if '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')
+
+    # 设置侧边栏并获取模型和插件信息
+    model_name, api_base, plugin_action = st.session_state['ui'].setup_sidebar()
+    plugins = [dict(type=f"lagent.actions.{plugin.__class__.__name__}") for plugin in plugin_action]
+
+    if (
+        'chatbot' not in st.session_state or
+        model_name != st.session_state['chatbot'].model_type or
+        'last_plugin_action' not in st.session_state or
+        plugin_action != st.session_state['last_plugin_action'] or
+        api_base != st.session_state['api_base']    
+    ):
+        # 更新 Chatbot
+        st.session_state['chatbot'] = st.session_state['ui'].initialize_chatbot(model_name, api_base, plugin_action)
+        st.session_state['last_plugin_action'] = plugin_action  # 更新插件状态
+        st.session_state['api_base'] = api_base  # 更新 API Base 地址
+
+        # 初始化 AgentForInternLM
+        st.session_state['agent'] = AgentForInternLM(
+            llm=st.session_state['chatbot'],
+            plugins=plugins,
+            output_format=dict(
+                type=PluginParser,
+                template=PLUGIN_CN,
+                prompt=get_plugin_prompt(plugin_action)
+            )
+        )
+        # 清空对话历史
+        st.session_state['session_history'] = []
+
+    if 'agent' not in st.session_state:
+        st.session_state['agent'] = None
+
+    agent = st.session_state['agent']
+    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)
+
+    # 处理用户输入
+    if user_input := st.chat_input(''):
+        st.session_state['ui'].render_user(user_input)
+
+        # 调用模型时确保侧边栏的系统提示词和插件提示词生效
+        res = agent(user_input, session_id=0)
+        st.session_state['ui'].render_assistant(res)
+
+        # 更新会话状态
+        st.session_state['user'].append(user_input)
+        st.session_state['assistant'].append(copy.deepcopy(res))
+
+    st.session_state['last_status'] = None
+
+
+if __name__ == '__main__':
+    main()

weather_query.py

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+import os
+import requests
+from lagent.actions.base_action import BaseAction, tool_api
+from lagent.schema import ActionReturn, ActionStatusCode
+
+class WeatherQuery(BaseAction):
+    def __init__(self):
+        super().__init__()
+        self.api_key = os.getenv("weather_token")
+        print(self.api_key)
+        if not self.api_key:
+            raise EnvironmentError("未找到环境变量 'token'。请设置你的和风天气 API Key 到 'weather_token' 环境变量中，比如export weather_token='xxx' ")
+
+    @tool_api
+    def run(self, location: str) -> dict:
+        """
+        查询实时天气信息。
+
+        Args:
+            location (str): 要查询的地点名称、LocationID 或经纬度坐标（如 "101010100" 或 "116.41,39.92"）。
+
+        Returns:
+            dict: 包含天气信息的字典
+                * location: 地点名称
+                * weather: 天气状况
+                * temperature: 当前温度
+                * wind_direction: 风向
+                * wind_speed: 风速（公里/小时）
+                * humidity: 相对湿度（%）
+                * report_time: 数据报告时间
+        """
+        try:
+            # 如果 location 不是坐标格式（例如 "116.41,39.92"），则调用 GeoAPI 获取 LocationID
+            if not ("," in location and location.replace(",", "").replace(".", "").isdigit()):
+                # 使用 GeoAPI 获取 LocationID
+                geo_url = f"https://geoapi.qweather.com/v2/city/lookup?location={location}&key={self.api_key}"
+                geo_response = requests.get(geo_url)
+                geo_data = geo_response.json()
+
+                if geo_data.get("code") != "200" or not geo_data.get("location"):
+                    raise Exception(f"GeoAPI 返回错误码：{geo_data.get('code')} 或未找到位置")
+
+                location = geo_data["location"][0]["id"]
+
+            # 构建天气查询的 API 请求 URL
+            weather_url = f"https://devapi.qweather.com/v7/weather/now?location={location}&key={self.api_key}"
+            response = requests.get(weather_url)
+            data = response.json()
+
+            # 检查 API 响应码
+            if data.get("code") != "200":
+                raise Exception(f"Weather API 返回错误码：{data.get('code')}")
+
+            # 解析和组织天气信息
+            weather_info = {
+                "location": location,
+                "weather": data["now"]["text"],
+                "temperature": data["now"]["temp"] + "°C", 
+                "wind_direction": data["now"]["windDir"],
+                "wind_speed": data["now"]["windSpeed"] + " km/h",  
+                "humidity": data["now"]["humidity"] + "%",
+                "report_time": data["updateTime"]
+            }
+
+            return {"result": weather_info}
+
+        except Exception as exc:
+            return ActionReturn(
+                errmsg=f"WeatherQuery 异常：{exc}",
+                state=ActionStatusCode.HTTP_ERROR
+            )