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          text: '你的角色：你是 百晓生- 世上最好的研究和解释代理。


            你的工作：以各种可能的方式以用户提问的语言解释{{#sys.query#}}，使其易于理解。


            您的动机：让学习者对他需要理解的每个{{#sys.query#}}给予“啊哈”时刻。 你可以通过解释事物的艺术来做到这一点。


            学习者简介： 学习者什么都不知道！ 他完全是个初学者。 他只听得懂简单的语言，没有行话和繁重的语法。 他喜欢将概念形象化，这让他更好地理解。'
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            \ 不要从所有摘要中选择相同的信息。 总是在下一个总结中发现新的东西。\n\n{{#sys.query#}}\n<instructions>\
            \  1. 首先识别需要简化的概念，使用高中生能理解的语言。  \n2. 将复杂的概念分解成更小、更易消化的部分，以便能够轻松向高中生解释。\
            \  \n3. 使用简单的语言，避免技术术语，以确保清晰和理解。  4. 提供现实生活中的例子或类比，帮助以相关方式说明该概念。  \n5.\
            \ 确保解释简洁明了，专注于该概念的关键方面。 \n6. 请记住在输出中避免使用任何XML标签，因为最终解释应为纯文本。\n7.用知乎的风格进行科普介绍\n\
            </instructions> \n<examples> <example> 对于光合作用这个概念： 输入：绿色植物和其他一些生物利用阳光通过叶绿素合成食物的过程。\
            \ 输出：植物利用阳光和一种叫做叶绿素的绿色色素制造自己的食物。</example> <example> 对于重力这个概念： 输入：将一个物体吸引到地球中心或任何其他具有质量的物理体上的力量。\
            \ 输出：重力是让我们留在地面上并使东西掉下来的原因。</example> <example> 对于民主这个概念： 输入：由整个居民或所有符合条件成员通过选举代表进行管理的一种政府制度。\
            \ 输出：民主就是一个国家的人们投票选择他们的领导人，并共同做出决定。</example></examples>"
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          text: '用类比或者隐喻介绍概念{{#sys.query#}}

            比如

            Docker 的比喻：

            想象你正在经营一家移动餐车生意。🚐🍔

            你有一个食谱书（Dockerfile），里面详细记录了如何制作你的招牌菜。📘

            根据这个食谱，你准备了一些预制食材和调料（Docker 镜像）。这些都整齐地装在密封容器里，随时可以使用。🥫🧂

            当顾客来点餐时，你不是从头开始做饭，而是拿出这些预制的食材（基础镜像），快速组合并加热（创建容器）。🔥

            每个订单（容器）都在单独的餐盒（隔离环境）中制作和服务，互不影响。🍱

            你的餐车可以轻松地开到任何地方（可移植性），在那里提供完全相同的美食体验。🌆🏙️

            当你想要更新菜单时，你只需要修改你的食谱书（更新 Dockerfile），然后准备新的预制食材（构建新镜像）。🆕

            你还可以把你的食谱分享到美食论坛（Docker Hub），让其他餐车主也能制作你的招牌菜。🌐👨‍🍳👩‍🍳'
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            be used to generate relevant images.


            Guidelines for interpreting the input:

            1. Identify key elements, themes, and imagery in the description

            2. Consider the mood, style, and atmosphere implied by the description

            3. Look for specific objects, colors, textures, or visual elements mentioned


            Process for converting the description to prompt words:

            1. Break down the description into its core components

            2. Translate metaphorical language into concrete visual elements

            3. Add relevant adjectives to enhance the visual description

            4. Include any specific artistic styles or techniques that might be appropriate

            5. Must use English.


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            - Provide a list of English words or short phrases separated by commas

            - Ensure the list is comprehensive yet concise

            - Avoid repetition and redundancy

            - Order the words from most important/relevant to least


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            amber glow, melodic waves, comforting presence


            Now, please convert the given description into prompt words for image
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          role: system
          text: '列举{{#1724750759528.text#}}提及可能造成理解障碍的专业名词，然后逐一用一句话进行扫盲

            注意不要输出其他内容

            <output format>

            利率：银行支付给存款者的利息百分比。

            换汇：将一种货币转换为另一种货币的过程。

            存款：将钱放入银行，银行会给你利息。

            利息：你存的钱在一段时间后获得的额外收入。

            </output format>'
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        title: 专业名词扫盲
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          role: system
          text: "<instructions>\n1. Begin by understanding the Bloom's taxonomy of\
            \ learning pathways, which include remembering, understanding, applying,\
            \ analyzing, synthesizing, and evaluating.\n2. Utilize the Bloom's taxonomy\
            \ to create a structured learning plan for a student, focusing on each\
            \ of the learning pathways mentioned.\n3. Develop a detailed study plan\
            \ that outlines specific activities, resources, and assessments for each\
            \ stage of the Bloom's taxonomy.\n4. Ensure that the learning plan is\
            \ comprehensive and covers all aspects of the learning process, from basic\
            \ memorization to critical evaluation.\n5. Remember to format the output\
            \ without any XML tags, as the final result should be a clear and concise\
            \ study plan for the student.\n\n<examples>\n<example>\nInput:\n- Bloom's\
            \ taxonomy learning pathways: remembering, understanding, applying, analyzing,\
            \ synthesizing, evaluating\n\nOutput:\n- Study Plan:\n  - Remembering:\
            \ Flashcards for key concepts\n  - Understanding: Reading assignments\
            \ with comprehension questions\n  - Applying: Practical exercises or simulations\n\
            \  - Analyzing: Case studies or problem-solving tasks\n  - Synthesizing:\
            \ Group projects or research papers\n  - Evaluating: Peer reviews or self-assessments\n\
            </example>\n\n<example>\nInput:\n- Bloom's taxonomy learning pathways:\
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            \  - Understanding: Concept mapping activities\n  - Applying: Hands-on\
            \ experiments or real-world applications\n  - Analyzing: Data interpretation\
            \ tasks or critical thinking exercises\n  - Evaluating: Debates or presentations\
            \ with peer feedback\n</example>\n\n<example>\nInput:\n- Bloom's taxonomy\
            \ learning pathways: remembering, applying, synthesizing\n\nOutput:\n\
            - Study Plan:\n- 用于谷歌查询的 query\n\n</example>"
        - id: 95174a7b-1579-44be-8a55-09dee29b93f1
          role: user
          text: '根据{{#1724743284784.text#}}给出学习计划

            '
        selected: false
        title: 学习计划
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724924800278'
      position:
        x: 942
        y: 762
      positionAbsolute:
        x: 942
        y: 762
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        desc: ''
        instruction: '提取{{#1724924800278.text#}}中的 query 作为谷歌搜索的查询词，必须使用英语返回

          提取{{#1724924800278.text#}}中的 plan 作为计划，请用 markdown 语法给出有序分点用{{#sys.query#}}的语言返回'
        model:
          completion_params:
            temperature: 0.7
          mode: chat
          name: gpt-4o-mini-2024-07-18
          provider: langgenius/openai/openai
        parameters:
        - description: 学习计划
          name: plan
          required: true
          type: string
        - description: 查询
          name: query
          required: true
          type: string
        query:
        - '1724924800278'
        - text
        reasoning_mode: prompt
        selected: false
        title: Parameter Extractor
        type: parameter-extractor
        variables: []
      height: 96
      id: '1724925821012'
      position:
        x: 1246
        y: 757.5
      positionAbsolute:
        x: 1246
        y: 757.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        desc: ''
        provider_id: tavily
        provider_name: tavily
        provider_type: builtin
        selected: false
        title: TavilySearch
        tool_configurations:
          exclude_domains: null
          include_answer: null
          include_domains: null
          include_images: null
          include_raw_content: null
          max_results: 5
          search_depth: basic
        tool_label: TavilySearch
        tool_name: tavily_search
        tool_parameters:
          query:
            type: mixed
            value: '{{#1724925821012.query#}}'
        type: tool
      height: 246
      id: '1724925966029'
      position:
        x: 1550
        y: 683.5
      positionAbsolute:
        x: 1550
        y: 683.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        context:
          enabled: false
          variable_selector: []
        desc: ''
        model:
          completion_params:
            temperature: 0.7
          mode: chat
          name: gpt-4o-mini
          provider: langgenius/openai/openai
        prompt_template:
        - id: 63cad421-2fca-4c36-b04f-1066992cf29e
          role: system
          text: '将{{#1724925966029.text#}}中的 url 和简介提取出来以：

            学习资料（给出几个词的描述）：url

            的格式进行输出'
        selected: false
        title: 给出学习资料
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724926011843'
      position:
        x: 1852.287813017275
        y: 762
      positionAbsolute:
        x: 1852.287813017275
        y: 762
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        classes:
        - id: '1'
          name: '识别用户是否是在询问关于概念，定义，名词介绍的问题

            如果是就选择这一个类别：

            例如：什么是量化宽松，什么是 docker，CRM 是什么意思，为我科普一下数字游民。'
        - id: '2'
          name: 其他问题，比如用户的闲聊
        desc: ''
        instructions: ''
        model:
          completion_params:
            temperature: 0.7
          mode: chat
          name: gpt-4o-mini-2024-07-18
          provider: langgenius/openai/openai
        query_variable_selector:
        - '1724727524982'
        - sys.query
        selected: false
        title: Question Classifier
        topics: []
        type: question-classifier
      height: 242
      id: '1724927400256'
      position:
        x: 332.57142857142856
        y: 324
      positionAbsolute:
        x: 332.57142857142856
        y: 324
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        context:
          enabled: false
          variable_selector: []
        desc: ''
        model:
          completion_params:
            temperature: 0.7
          mode: chat
          name: gpt-4o-mini-2024-07-18
          provider: langgenius/openai/openai
        prompt_template:
        - id: cc4f5e3a-02b0-4ae1-9f18-d4157e464042
          role: system
          text: 拒绝用户的闲聊
        selected: false
        title: LLM 8
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724927639466'
      position:
        x: 631.4138803076465
        y: 917.5000000000001
      positionAbsolute:
        x: 631.4138803076465
        y: 917.5000000000001
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: '{{#1724927639466.text#}}'
        desc: ''
        selected: false
        title: Answer 2
        type: answer
        variables: []
      height: 105
      id: '1724927780214'
      position:
        x: 942
        y: 917.5000000000001
      positionAbsolute:
        x: 942
        y: 917.5000000000001
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    viewport:
      x: 65.3722791208645
      y: 53.33561028311577
      zoom: 0.6571581021562093
