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      - whether it's your meeting notes, business documents, or any ideas you want
      to clarify. I'll assist you in breaking down the key points and making complex
      information clear and actionable. Let's begin! 🚀
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          Dev team for all the debugging support about files upload! This Chatflow
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          今天，对于处理大量业务文档的中大型企业，","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"2️⃣
          当他们每天收到包含客户反馈、內部报告和各种信息的大量邮件时，","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"3️⃣
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          因此，客户需要一种方法来实现AI辅助的文档处理，能够自动识别重要信息、智能归类、生成灵活的摘要、学习业务术语，并最终能够基于这些文档回答问题。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
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          今日、新機能開発中で大量の業務文書を扱う企業にとって・","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"2️⃣
          毎日様々な種類の文書（メール・顧客フィードバック・社内報告書","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"など）を処理する際に、","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"3️⃣
          効率的に文書を整理・分類し、重要度を判断し、内容を迅速に把握することが困難であるため、","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"4️⃣
          顧客は、AIを活用して文書を自動的に整理・分類し、重要度を判断し、柔軟な長さで要約を生成し、業務固有の知識を理解した上で質問に答えられるシステムを必要としている。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":null,"format":"","indent":0,"type":"root","version":1}}'
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          Today, for business professionals handling diverse document types,","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"2️⃣
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          therefore, the customer needs a way to implement an Al-powered document
          processing system that can automatically categorize, prioritize, summarize,
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          解决方案是什么？与其他替代方案相比，为什么它是满足客户需求的正确方法？","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"具体为客户提供了什么产品/服务？客户能在功能/情感/价值层的共鸣？还有没有更好的方法？","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"4️⃣
          我们如何描述端到端的客户体验？给客户带来的最大的价值是什么？","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"真的是客户想要的吗？客户会有什么样的感受？客户会说什么？","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"5️⃣
          我们如何定义和衡量成功与否？","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"衡量产品/服务成功的指标是什么？如何进行追踪和验证？","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"而本
          Chatflow 要解决的问题，就是帮助你思考清楚「第 2️⃣ 点」。很多时候只要将不清晰的表达稍加修饰整理，就能呈现一份清晰的描述文本。这正是大语言模型擅长的！","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
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          Who are the customers? What insights do we have about them?  ","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"Customer
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          What are the customer’s pain points and opportunities? What data supports
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          What is the solution? Compared to alternative options, why is it the right
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          How do we describe the end-to-end customer experience? What is the greatest
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          顧客の課題や機会は何か？それを裏付けるデータはあるか？  ","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"顧客のニーズは何か？我々は彼らのどのような問題を解決しようとしているのか？そのニーズがあることをどう証明するか？","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"3️⃣
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            First, carefully read and analyze the text. Pay close attention to the
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            Output your detailed analysis within <detailed_analysis> tags. In your
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            3. The precise problem or opportunity being addressed, including any underlying
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            Be as specific and focused as possible, avoiding broad or general statements.
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            Do not expand beyond what is explicitly stated or strongly implied in
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            After completing your detailed analysis, summarize your findings using
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            1️⃣ Today, for ____[customer type],

            2️⃣ when ____[situation],

            3️⃣ they are forced to ____[describe problem/opportunity],

            4️⃣ therefore, the customer needs a way to ____[insert need].

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            Ensure that your summary is highly specific, focused, and directly related
            to the core message of the given text. It’s important to pay attention
            to and include the specific terminology mentioned in the previous analysis,
            as these terms may be directly related to the technical aspects of the
            solution or approach being discussed.(write details and try to be as accurate
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            Output your final response in the following structure:

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            [Your detailed analysis here]

            </detailed_analysis>


            <five_customer_questions>

            [Your summary in the specified format here]

            </five_customer_questions>


            Remember to be as specific and focused as possible in both your detailed
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            aspects of the customer''s situation and requirements. Output Language:
            {{#1728593630194.output_language#}}.

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            {{#sys.query#}}'
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        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"📌 中文版输入样本","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"今天我们要分享的
          Dify Chatflow 和企业提效密切相关。坦白说，很多企业效率低下归结下来只有一个问题 —— 沟通效率太低。什么是沟通效率太低呢？就是一句话能说清楚的事情你说了大半天都没有解释清楚。比如说，这种效率低其实可能体现在用户访谈里。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"很多企业花费了大量时间和精力做用户访谈，但由于访谈的提问设计得不够好，导致用户访谈变成了一种毫无意义的闲聊。仿佛在问：你吃了吗？然后用户说：吃了。又或者用户支支吾吾说了一大堆零散的信息，而调研人员没办法用一段话整合清楚用户真正想表达的诉求。更不要说之后怎么传递给自己的团队来处理和优化自己的产品了。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"基于此，我们今天设计一套
          Chatflow，来解决这个问题。你既可以直接粘贴文本，又可以借助 Dify 的文件上传系统来上传一段聊天记录，比如和用户访谈结束后的录音文字
          pdf，或者单纯截图。随后让 LLM 帮你按照 Amazon 的 Five Key Customer Questions 方法论其中第二步的思路，借助
          LLM 强大的语言能力以输出精良的沟通文本。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
        theme: yellow
        title: ''
        type: ''
        width: 592
      height: 337
      id: '1730054779846'
      position:
        x: 758.853771448933
        y: 1294.0126224651422
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        x: 758.853771448933
        y: 1294.0126224651422
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom-note
      width: 592
    - data:
        author: lysonober
        desc: ''
        height: 347
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"🤩 输出结果","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"1️⃣
          今天，对于进行用户访谈的企业，","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"2️⃣
          当他们在用户访谈中遇到沟通效率低下的问题时，","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"3️⃣
          他们被迫花费大量时间和精力却无法获取有价值的用户反馈，也难以将零散的访谈文本信息整合成有意义的洞察，","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"4️⃣
          因此，客户需要一种方法来利用Dify Chatflow和LLM技术，自动分析各种形式的用户访谈数据（如文本、录音转文字、截图），并基于Amazon的Five
          Key Customer Questions方法论生成精炼的沟通文本，以提高访谈效率，更准确地捕捉用户需求，并有效地向团队传达以优化产品。","type":"text","version":1}],"direction":"ltr","format":"start","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
        theme: violet
        title: ''
        type: ''
        width: 289
      height: 347
      id: '1730055116151'
      position:
        x: 1391.0270276673382
        y: 1294.0126224651422
      positionAbsolute:
        x: 1391.0270276673382
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      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom-note
      width: 289
    - data:
        author: lysonober
        desc: ''
        height: 364
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"📌 日本語版入力サンプル 👈","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"今日は、企業の効率向上に密接に関連する
          Dify Chatflow をご紹介します。率直に言うと、多くの企業の非効率性の根本原因はただ一つ、つまり「コミュニケーションの効率が低すぎること」です。では、コミュニケーション効率が低いとはどういう意味でしょうか？一言で伝えられることが、延々と時間をかけても説明できない状態です。例えば、このような効率の悪さはユーザーインタビューにも表れることがあります。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"多くの企業はユーザーインタビューに大量の時間と労力を費やしていますが、質問設計が不十分なため、インタビューが無意味なおしゃべりに終わってしまうことがあります。例えば「食事はしましたか？」と尋ねて「しました」と答えられるような場面です。または、ユーザーが長々と断片的な情報を話し、調査員がユーザーの本当のニーズを一言でまとめられない状態です。これでは、チームに伝えて製品を最適化するのも一苦労です。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"これに基づき、今日はこの問題を解決するために
          Chatflow を設計しました。テキストを直接貼り付けるだけでなく、Dify のファイルアップロードシステムを使用して、ユーザーインタビュー後の録音文字起こし
          PDF やスクリーンショットなどのチャットログをアップロードできます。次に、LLM の強力な言語処理能力を活用し、Amazon の「Five Key
          Customer Questions」フレームワークの第 2 ステップに沿って、精緻なコミュニケーション文章を出力します。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
        theme: yellow
        title: ''
        type: ''
        width: 598
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      position:
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    - data:
        author: lysonober
        desc: ''
        height: 193
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"📌 Usage suggestions","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"This
          Chatflow does not have a \"topic segmentation\" function, which means if
          a conversation covers many different requirement points, I suggest you first
          segment these texts yourself, or create another chatflow/workflow to address
          this issue. Then, for each focal point discussed, use this Chatflow set
          to generate results one by one.","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
        theme: blue
        title: ''
        type: ''
        width: 552
      height: 193
      id: '1730055191782'
      position:
        x: 168.06818855311468
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      type: custom-note
      width: 552
    - data:
        author: lysonober
        desc: ''
        height: 363
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"🤩 出力結果","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":" ","type":"text","version":1}],"direction":null,"format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"1️⃣
          今日、ユーザーインタビューを実施する企業にとって、","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"2️⃣
          ユーザーインタビューが非効率的で有意義な情報を得られない状況において、","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"3️⃣
          彼らは適切な質問設計ができず、ユーザーの真のニーズを把握し、チームに伝達することが困難であり、","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"4️⃣
          したがって、顧客はテキスト、音声データ、画像からユーザーのニーズを抽出し、LLMを活用してAmazonのFive Key Customer Questions方法論に基づいた高品質なコミュニケーションテキストを生成する方法が必要です。","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":null,"format":"","indent":0,"type":"root","version":1}}'
        theme: violet
        title: ' (1)'
        type: ''
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    - data:
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        height: 388
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        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"📌 English Version Sample","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"Today,
          we’re sharing a Dify Chatflow that’s closely tied to enhancing enterprise
          efficiency. Frankly speaking, the root cause of inefficiency in many companies
          boils down to one issue: low communication efficiency. But what exactly
          does that mean? It’s when something that could be explained in a single
          sentence ends up taking ages to clarify. This inefficiency is often reflected
          in user interviews, for example.","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"Many
          companies invest a great deal of time and effort into conducting user interviews,
          but due to poorly designed questions, these interviews end up as meaningless
          chit-chat. It’s like asking, “Have you eaten?” and getting a response of,
          “Yes, I have.” Or the user provides a long-winded, fragmented response,
          and the researcher struggles to summarize the true needs being expressed.
          Passing this on to their team for further product optimization becomes even
          more challenging.","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"To
          address this, today we’ve designed a Chatflow that can solve this issue.
          You can simply paste text or use Dify’s file upload system to upload a chat
          log, such as a PDF of the transcribed recording after a user interview,
          or even just a screenshot. Then, leveraging the powerful language capabilities
          of LLM, it will provide a refined communication summary following Amazon’s
          Five Key Customer Questions framework, specifically focusing on step two,
          to deliver a clear and concise communication output.","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
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        title: ''
        type: ''
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      position:
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        desc: ''
        height: 390
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"font-size:
          16px;","text":"🤩 Output","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0},{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"1️⃣
          Today, for enterprises conducting user interviews and product research,","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"2️⃣
          when they face low communication efficiency and struggle to extract meaningful
          insights from user responses,","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"3️⃣
          they are forced to deal with ineffective interviews, fragmented user feedback,
          and difficulties in summarizing and conveying user needs to product teams,","type":"text","version":1},{"type":"linebreak","version":1},{"detail":0,"format":0,"mode":"normal","style":"","text":"4️⃣
          therefore, the customer needs a way to leverage Dify Chatflow, a tool that
          uses LLM capabilities to analyze various input formats (text, PDF, screenshots)
          of user interview data and provide refined, clear, and concise communication
          summaries based on Amazon''s Five Key Customer Questions framework, specifically
          focusing on step two.","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
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        desc: ''
        model:
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          mode: chat
          name: claude-3-5-sonnet-20241022
          provider: anthropic
        prompt_template:
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          role: system
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            the most precise and granular aspects of the customer's situation and
            requirements.
        - id: da34f205-e09e-42bf-be7e-ec9f9bf69de1
          role: user
          text: "Here is the text ((please also read the image as part of the input)\
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            </docs>\n</text>\n\n<instructions>\nFirst, carefully read and analyze\
            \ the text. Pay close attention to the specific details that reveal the\
            \ customer type, situation, problem/opportunity, needs and the specific\
            \ terms. Focus on extracting the most granular and precise information\
            \ possible.\n\nOutput your detailed analysis within <detailed_analysis>\
            \ tags. In your analysis, identify and elaborate on:\n1. The specific\
            \ customer type or audience, including any relevant characteristics or\
            \ sub-categories\n2. The particular situation or context, including any\
            \ nuances or specific circumstances\n3. The precise problem or opportunity\
            \ being addressed, including any underlying issues or root causes\n4.\
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            \ or capabilities that would address the problem\n\nBe as specific and\
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            \ beyond what is explicitly stated or strongly implied in the text.\n\n\
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            \ to the core message of the given text. It’s important to pay attention\
            \ to and include the specific terminology mentioned in the previous analysis,\
            \ as these terms may be directly related to the technical aspects of the\
            \ solution or approach being discussed.(write details and try to be as\
            \ accurate as possible)\n\nOutput your final response in the following\
            \ structure:\n<detailed_analysis>\n[Your detailed analysis here]\n</detailed_analysis>\n\
            \n<five_customer_questions>\n[Your summary in the specified format here]\n\
            </five_customer_questions>\n\nRemember to be as specific and focused as\
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        prompt_template:
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          role: system
          text: You are tasked with analyzing a given text (with image) to extract
            its core message and identify specific customer needs. Your analysis should
            be detailed and focused, identifying the most precise and granular aspects
            of the customer's situation and requirements.
        - id: a1704124-84c7-49b4-9dd1-827d1d8bf6aa
          role: user
          text: 'Here is the text (please also view the image)to analyze:

            <text>

            {{#sys.query#}}

            </text>


            <instructions>

            First, carefully read and analyze the text. Pay close attention to the
            specific details that reveal the customer type, situation, problem/opportunity,
            needs and the specific terms. Focus on extracting the most granular and
            precise information possible.


            Output your detailed analysis within <detailed_analysis> tags. In your
            analysis, identify and elaborate on:

            1. The specific customer type or audience, including any relevant characteristics
            or sub-categories

            2. The particular situation or context, including any nuances or specific
            circumstances

            3. The precise problem or opportunity being addressed, including any underlying
            issues or root causes

            4. The exact need or solution required, including any specific features
            or capabilities that would address the problem


            Be as specific and focused as possible, avoiding broad or general statements.
            Concentrate on the core functionality or purpose described in the text.
            Do not expand beyond what is explicitly stated or strongly implied in
            the text.


            After completing your detailed analysis, summarize your findings using
            the following format within <five_customer_questions> tags:


            <five_customer_questions>

            1️⃣ Today, for ____[customer type],

            2️⃣ when ____[situation],

            3️⃣ they are forced to ____[describe problem/opportunity],

            4️⃣ therefore, the customer needs a way to ____[insert need].

            </five_customer_questions>


            Ensure that your summary is highly specific, focused, and directly related
            to the core message of the given text. It’s important to pay attention
            to and include the specific terminology mentioned in the previous analysis,
            as these terms may be directly related to the technical aspects of the
            solution or approach being discussed.(write details and try to be as accurate
            as possible)


            Output your final response in the following structure:

            <detailed_analysis>

            [Your detailed analysis here]

            </detailed_analysis>


            <five_customer_questions>

            [Your summary in the specified format here]

            </five_customer_questions>


            Remember to be as specific and focused as possible in both your detailed
            analysis and summary. Your goal is to identify the most precise and granular
            aspects of the customer''s situation and requirements. Output Language:
            {{#1728593630194.output_language#}}.


            </instructions>'
        selected: false
        title: Analysis (Image)
        type: llm
        variables: []
        vision:
          configs:
            detail: high
            variable_selector:
            - sys
            - files
          enabled: true
      height: 96
      id: '1730059949714'
      position:
        x: 1783.6079698930473
        y: 275.9691351813799
      positionAbsolute:
        x: 1783.6079698930473
        y: 275.9691351813799
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        desc: ''
        is_array_file: true
        selected: false
        title: Doc Extractor
        type: document-extractor
        variable_selector:
        - sys
        - files
      height: 92
      id: '1730060680136'
      position:
        x: 1268.3889170093034
        y: 316.0702957621009
      positionAbsolute:
        x: 1268.3889170093034
        y: 316.0702957621009
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        context:
          enabled: false
          variable_selector: []
        desc: ''
        model:
          completion_params:
            temperature: 0.5
          mode: chat
          name: claude-3-5-sonnet-20240620
          provider: anthropic
        prompt_template:
        - id: 562509c4-10ce-4130-ac0e-8c3394de46a5
          role: system
          text: You are tasked with analyzing a given text to extract its core message
            and identify specific customer needs. Your analysis should be detailed
            and focused, identifying the most precise and granular aspects of the
            customer's situation and requirements.
        - id: 66c15dbb-74ba-4212-ae21-0eb8976cb92c
          role: user
          text: "Here is the text to analyze:\n\n<text>\n    <docs>\n    {{#1730060680136.text#}}\n\
            \    </docs>\n{{#sys.query#}}\n</text>\n\n<instructions>\nFirst, carefully\
            \ read and analyze the text. Pay close attention to the specific details\
            \ that reveal the customer type, situation, problem/opportunity, needs\
            \ and the specific terms. Focus on extracting the most granular and precise\
            \ information possible.\n\nOutput your detailed analysis within <detailed_analysis>\
            \ tags. In your analysis, identify and elaborate on:\n1. The specific\
            \ customer type or audience, including any relevant characteristics or\
            \ sub-categories\n2. The particular situation or context, including any\
            \ nuances or specific circumstances\n3. The precise problem or opportunity\
            \ being addressed, including any underlying issues or root causes\n4.\
            \ The exact need or solution required, including any specific features\
            \ or capabilities that would address the problem\n\nBe as specific and\
            \ focused as possible, avoiding broad or general statements. Concentrate\
            \ on the core functionality or purpose described in the text. Do not expand\
            \ beyond what is explicitly stated or strongly implied in the text.\n\n\
            After completing your detailed analysis, summarize your findings using\
            \ the following format within <five_customer_questions> tags:\n\n<five_customer_questions>\n\
            1️⃣ Today, for ____[customer type],\n2️⃣ when ____[situation],\n3️⃣ they\
            \ are forced to ____[describe problem/opportunity],\n4️⃣ therefore, the\
            \ customer needs a way to ____[insert need].\n</five_customer_questions>\n\
            \nEnsure that your summary is highly specific, focused, and directly related\
            \ to the core message of the given text. It’s important to pay attention\
            \ to and include the specific terminology mentioned in the previous analysis,\
            \ as these terms may be directly related to the technical aspects of the\
            \ solution or approach being discussed.(write details and try to be as\
            \ accurate as possible)\n\nOutput your final response in the following\
            \ structure:\n<detailed_analysis>\n[Your detailed analysis here]\n</detailed_analysis>\n\
            \n<five_customer_questions>\n[Your summary in the specified format here]\n\
            </five_customer_questions>\n\nRemember to be as specific and focused as\
            \ possible in both your detailed analysis and summary. Your goal is to\
            \ identify the most precise and granular aspects of the customer's situation\
            \ and requirements. Output Language: {{#1728593630194.output_language#}}.\n\
            </instructions>"
        selected: false
        title: Analysis (Doc)
        type: llm
        variables: []
        vision:
          configs:
            detail: high
            variable_selector:
            - '1729727194602'
            - result
          enabled: false
      height: 96
      id: '17300607437060'
      position:
        x: 1783.6079698930473
        y: 408.9682132963155
      positionAbsolute:
        x: 1783.6079698930473
        y: 408.9682132963155
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        code: "def main(arg1: str) -> dict:\n    \"\"\"\n    从文本中提取SVG代码内容\n    \n\
          \    Args:\n        arg1: 包含SVG代码的文本字符串\n        \n    Returns:\n      \
          \  dict: 包含提取结果的字典，格式为 {\"result\": str}\n    \"\"\"\n    try:\n       \
          \ # 定位SVG内容\n        start_tag = \"<svg_card>\"\n        end_tag = \"</svg_card>\"\
          \n        \n        content = arg1[arg1.index(start_tag) + len(start_tag):arg1.index(end_tag)]\n\
          \            \n        return {\"result\": content.strip()}\n        \n\
          \    except ValueError:\n        return {\"result\": \"SVG wrong\"}  # 如果找不到标签，返回自定义的提醒内容"
        code_language: python3
        desc: ''
        outputs:
          result:
            children: null
            type: string
        selected: false
        title: SVG extractor
        type: code
        variables:
        - value_selector:
          - '1729719431700'
          - text
          variable: arg1
      height: 52
      id: '1730065438460'
      position:
        x: 3138.185487287336
        y: 458.5744696223079
      positionAbsolute:
        x: 3138.185487287336
        y: 458.5744696223079
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        answer: '{{#1730059949714.text#}}'
        desc: ''
        selected: false
        title: Answer Preview
        type: answer
        variables: []
      height: 101
      id: '1730069983351'
      position:
        x: 2180.273316627065
        y: 275.9691351813799
      positionAbsolute:
        x: 2180.273316627065
        y: 275.9691351813799
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        answer: "<details>\n    <summary><h2 style=\"display: inline;\">Customer Requirements</h2></summary>\n\
          \    <p>"
        desc: ''
        selected: false
        title: Answer Init
        type: answer
        variables: []
      height: 130
      id: '1730070193226'
      position:
        x: 469.9736303733853
        y: 231.47857669330966
      positionAbsolute:
        x: 469.9736303733853
        y: 231.47857669330966
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        answer: '{{#17300573261730.text#}}'
        desc: ''
        selected: false
        title: Answer Preview
        type: answer
        variables: []
      height: 101
      id: '1730070339677'
      position:
        x: 2180.273316627065
        y: 535.5479623195462
      positionAbsolute:
        x: 2180.273316627065
        y: 535.5479623195462
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        answer: '{{#17300607437060.text#}}'
        desc: ''
        selected: false
        title: Answer Preview
        type: answer
        variables: []
      height: 101
      id: '1730070383606'
      position:
        x: 2180.273316627065
        y: 408.9682132963155
      positionAbsolute:
        x: 2180.273316627065
        y: 408.9682132963155
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    - data:
        answer: '{{#17300532699170.text#}}'
        desc: ''
        selected: false
        title: Answer Preview
        type: answer
        variables: []
      height: 101
      id: '1730070398320'
      position:
        x: 2180.273316627065
        y: 143.53653282317302
      positionAbsolute:
        x: 2180.273316627065
        y: 143.53653282317302
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 243
    viewport:
      x: 53.15974707870987
      y: 217.11576642500887
      zoom: 0.48800570369799656