app:
  description: ''
  icon: 👨‍💼
  icon_background: '#E0EAFF'
  mode: advanced-chat
  name: 面试准备（条件并行）
  use_icon_as_answer_icon: false
dependencies:
- current_identifier: null
  type: marketplace
  value:
    marketplace_plugin_unique_identifier: langgenius/openai:0.0.13@9caa0421b5519db036aaccdbf1980d1071550767d6c59e9d9388dd386a92e9f6
kind: app
version: 0.1.5
workflow:
  conversation_variables:
  - description: Questions generated for the interview
    id: 7fd2e3cf-50f0-41d4-bdec-ec13f036d510
    name: interview_qns
    selector:
    - conversation
    - interview_qns
    value: ''
    value_type: string
  - description: 'Information about the company, crawed from homepage. '
    id: 0858475c-4ec3-4909-879e-5d29147f8c3b
    name: company_info
    selector:
    - conversation
    - company_info
    value: ''
    value_type: string
  environment_variables: []
  features:
    file_upload:
      allowed_file_extensions:
      - .JPG
      - .JPEG
      - .PNG
      - .GIF
      - .WEBP
      - .SVG
      allowed_file_types:
      - image
      allowed_file_upload_methods:
      - local_file
      - remote_url
      enabled: false
      fileUploadConfig:
        audio_file_size_limit: 50
        batch_count_limit: 5
        file_size_limit: 15
        image_file_size_limit: 10
        video_file_size_limit: 100
        workflow_file_upload_limit: 10
      image:
        enabled: false
        number_limits: 3
        transfer_methods:
        - local_file
        - remote_url
      number_limits: 3
    opening_statement: ''
    retriever_resource:
      enabled: false
    sensitive_word_avoidance:
      enabled: false
    speech_to_text:
      enabled: false
    suggested_questions: []
    suggested_questions_after_answer:
      enabled: false
    text_to_speech:
      enabled: false
      language: ''
      voice: ''
  graph:
    edges:
    - data:
        isInIteration: false
        sourceType: llm
        targetType: tool
      id: 1724963240375-source-1724963179361-target
      selected: false
      source: '1724963240375'
      sourceHandle: source
      target: '1724963179361'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: tool
        targetType: code
      id: 1724963179361-source-1724963278601-target
      selected: false
      source: '1724963179361'
      sourceHandle: source
      target: '1724963278601'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: code
        targetType: llm
      id: 1724963278601-source-1724963072676-target
      selected: false
      source: '1724963278601'
      sourceHandle: source
      target: '1724963072676'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: tool
      id: 1724963072676-source-1724963334744-target
      selected: false
      source: '1724963072676'
      sourceHandle: source
      target: '1724963334744'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: tool
        targetType: code
      id: 1724963334744-source-1724963406271-target
      selected: false
      source: '1724963334744'
      sourceHandle: source
      target: '1724963406271'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: code
        targetType: llm
      id: 1724963406271-source-1724963438612-target
      selected: false
      source: '1724963406271'
      sourceHandle: source
      target: '1724963438612'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: assigner
      id: 1724963438612-source-1724963505855-target
      selected: false
      source: '1724963438612'
      sourceHandle: source
      target: '1724963505855'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: answer
      id: 1724963057858-true-1724963628776-target
      selected: false
      source: '1724963057858'
      sourceHandle: 'true'
      target: '1724963628776'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: start
        targetType: if-else
      id: 1724912779215-source-1724963057858-target
      selected: false
      source: '1724912779215'
      sourceHandle: source
      target: '1724963057858'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: assigner
        targetType: answer
      id: 1724963505855-source-1724963776867-target
      selected: false
      source: '1724963505855'
      sourceHandle: source
      target: '1724963776867'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: llm
      id: 1724964287707-true-1724963240375-target
      selected: false
      source: '1724964287707'
      sourceHandle: 'true'
      target: '1724963240375'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: answer
      id: 1724964287707-true-1724963567827-target
      selected: false
      source: '1724964287707'
      sourceHandle: 'true'
      target: '1724963567827'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: answer
        targetType: answer
      id: 1724963567827-source-1724963776867-target
      selected: false
      source: '1724963567827'
      sourceHandle: source
      target: '1724963776867'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: if-else
      id: 1724963057858-false-1724964287707-target
      selected: false
      source: '1724963057858'
      sourceHandle: 'false'
      target: '1724964287707'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: llm
      id: 1724964287707-0dad4dbf-9e2c-46be-a133-c915c34772dc-1724965395766-target
      selected: false
      source: '1724964287707'
      sourceHandle: 0dad4dbf-9e2c-46be-a133-c915c34772dc
      target: '1724965395766'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: llm
      id: 1724964287707-0dad4dbf-9e2c-46be-a133-c915c34772dc-1724965405707-target
      source: '1724964287707'
      sourceHandle: 0dad4dbf-9e2c-46be-a133-c915c34772dc
      target: '1724965405707'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: llm
      id: 1724964287707-0dad4dbf-9e2c-46be-a133-c915c34772dc-1724965407816-target
      source: '1724964287707'
      sourceHandle: 0dad4dbf-9e2c-46be-a133-c915c34772dc
      target: '1724965407816'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: llm
      id: 1724964287707-0dad4dbf-9e2c-46be-a133-c915c34772dc-1724965409826-target
      source: '1724964287707'
      sourceHandle: 0dad4dbf-9e2c-46be-a133-c915c34772dc
      target: '1724965409826'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: answer
      id: 1724965395766-source-1725955402316-target
      source: '1724965395766'
      sourceHandle: source
      target: '1725955402316'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: answer
      id: 1724965405707-source-1725955402316-target
      source: '1724965405707'
      sourceHandle: source
      target: '1725955402316'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: answer
      id: 1724965407816-source-1725955402316-target
      source: '1724965407816'
      sourceHandle: source
      target: '1725955402316'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: answer
      id: 1724965409826-source-1725955402316-target
      source: '1724965409826'
      sourceHandle: source
      target: '1725955402316'
      targetHandle: target
      type: custom
      zIndex: 0
    nodes:
    - data:
        desc: ''
        selected: false
        title: 开始
        type: start
        variables:
        - label: 面试的职位
          max_length: null
          options: []
          required: true
          type: text-input
          variable: role
        - label: 你将要面试的公司
          max_length: null
          options: []
          required: true
          type: text-input
          variable: company
      height: 116
      id: '1724912779215'
      position:
        x: 30
        y: 281.5
      positionAbsolute:
        x: 30
        y: 281.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        cases:
        - case_id: 'true'
          conditions:
          - comparison_operator: '='
            id: 0026768d-dcad-44c6-a957-b514096b2fdf
            value: '1'
            varType: number
            variable_selector:
            - sys
            - dialogue_count
          id: 'true'
          logical_operator: and
        desc: ''
        selected: false
        title: 条件分支
        type: if-else
      height: 126
      id: '1724963057858'
      position:
        x: 334
        y: 281.5
      positionAbsolute:
        x: 334
        y: 281.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: 1a8a0822-5f72-4513-871f-dc2819e50225
          role: system
          text: "<prompt>\nAnalyze JSON data containing URL of official website. You\
            \ are given a JSON data that is returned from a Google search query. Your\
            \ task is to analyze the JSON data and identify the most probable URL\
            \ of the company's official website. \n\nReturn the URL of the company's\
            \ official website. Make sure the output does not contain anything else\
            \ other than the url. \n\n**Example:**\n## Example Input\n\n```json\n\
            {\n  \"query\": \"Google\",\n  \"results\": [\n    {\n      \"title\"\
            : \"Google\",\n      \"url\": \"https://www.google.com/\"\n    },\n  \
            \  {\n      \"title\": \"Google - About Google\",\n      \"url\": \"https://about.google/\"\
            \n    }\n  ]\n}\n```\n## Example Output\nhttps://www.google.com/\n\n</prompt>"
        - id: 7e785114-f076-4273-8133-5cada69bf0cd
          role: user
          text: 'Goole search result: {{#1724963278601.result#}}'
        selected: false
        title: 过滤搜索
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724963072676'
      position:
        x: 1854
        y: 478.5
      positionAbsolute:
        x: 1854
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        author: Dify
        desc: ''
        height: 88
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"1.
          确认候选人面试的职位和公司。","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: 240
      height: 88
      id: '1724963084766'
      position:
        x: 638
        y: 149.28956022607213
      positionAbsolute:
        x: 638
        y: 149.28956022607213
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom-note
      width: 240
    - data:
        desc: ''
        provider_id: google
        provider_name: google
        provider_type: builtin
        selected: false
        title: 谷歌搜索
        tool_configurations: {}
        tool_label: GoogleSearch
        tool_name: google_search
        tool_parameters:
          query:
            type: mixed
            value: '{{#1724963240375.text#}}'
        type: tool
      height: 54
      id: '1724963179361'
      position:
        x: 1246
        y: 478.5
      positionAbsolute:
        x: 1246
        y: 478.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: ee4d175e-1ca2-4d98-b3d5-14845a24dbb4
          role: system
          text: "<instructions>\n1. Read the user's query carefully to understand\
            \ the main topic or subject they are interested in.\n2. Identify the key\
            \ terms or phrases within the user's query that best represent the main\
            \ topic.\n3. Simplify the user's query by removing any unnecessary words\
            \ or phrases that do not contribute to the main topic.\n4. Generate a\
            \ concise search query that captures the essence of the user's interest,\
            \ using the identified key terms or phrases.\n5. Ensure that the output\
            \ is a clear and direct search query suitable for a Google search.\n6.\
            \ The output should not contain any XML tags or additional formatting.\n\
            </instructions>\n\n<examples>\n<example>\n  <input>\n    I want to know\
            \ about nvidia\n  </input>\n  <output>\n    nvidia\n  </output>\n</example>\n\
            \n<example>\n  <input>\n    Can you tell me more about the history of\
            \ the internet?\n  </input>\n  <output>\n    history of the internet\n\
            \  </output>\n</example>\n\n<example>\n  <input>\n    What are the health\
            \ benefits of green tea?\n  </input>\n  <output>\n    health benefits\
            \ of green tea\n  </output>\n</example>\n</examples>"
        - id: 34a949ff-f31a-4a3b-b999-a6ce16a06f0d
          role: user
          text: '{{#1724912779215.company#}}'
        selected: false
        title: 生成搜索词
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724963240375'
      position:
        x: 942
        y: 478.5
      positionAbsolute:
        x: 942
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        code: "def main(arg1):\n    import json\n    data = json.dumps(arg1)\n   \
          \ return {\n        'result': data \n    }"
        code_language: python3
        desc: ''
        outputs:
          result:
            children: null
            type: string
        selected: false
        title: 代码执行
        type: code
        variables:
        - value_selector:
          - '1724963179361'
          - json
          variable: arg1
      height: 54
      id: '1724963278601'
      position:
        x: 1550
        y: 478.5
      positionAbsolute:
        x: 1550
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        desc: ''
        provider_id: firecrawl
        provider_name: firecrawl
        provider_type: builtin
        selected: false
        title: Crawl
        tool_configurations:
          allowBackwardCrawling: 0
          allowExternalContentLinks: 0
          excludes: null
          headers: null
          ignoreSitemap: 0
          includeHtml: 0
          includeRawHtml: 0
          includes: null
          limit: 1
          maxDepth: 2
          mode: default
          onlyIncludeTags: null
          onlyMainContent: 1
          removeTags: null
          replaceAllPathsWithAbsolutePaths: 0
          returnOnlyUrls: 0
          screenshot: 0
          waitFor: null
          wait_for_results: 1
        tool_label: Crawl
        tool_name: crawl
        tool_parameters:
          url:
            type: mixed
            value: '{{#1724963072676.text#}}'
        type: tool
      height: 558
      id: '1724963334744'
      position:
        x: 2158
        y: 478.5
      positionAbsolute:
        x: 2158
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        code: "def main(arg1: str) -> dict:\n    import json\n    data = json.dumps(arg1)\n\
          \    result = data[:8000] if len(data) > 8000 else data\n    return {\n\
          \        \"result\": result,\n    }"
        code_language: python3
        desc: 如果长于8000字符则裁剪
        outputs:
          result:
            children: null
            type: string
        selected: false
        title: json2str
        type: code
        variables:
        - value_selector:
          - '1724963334744'
          - json
          variable: arg1
      height: 82
      id: '1724963406271'
      position:
        x: 2462
        y: 478.5
      positionAbsolute:
        x: 2462
        y: 478.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: 81eedfc4-5963-466b-8b58-9633bd0351d4
          role: system
          text: '<instructions>

            1. 访问需要汇总信息的公司主页。

            2. 提取不超过 150 个字的公司关键信息，包括但不限于：

            - 公司名称

            - 行业或部门

            - 主要产品或服务

            - 使命或愿景声明

            - 主要高管或领导团队

            - 总部所在地

            - 成立年份

            - 任何显著的成就或里程碑

            3. 以简洁连贯的方式总结提取的信息。

            4. 确保摘要清晰、信息丰富且没有任何不必要的细节。

            5. 输出应为纯文本，不应包含任何 XML 标记。

            </instructions>


            <examples>

            <example>

            <instructions>

            输入：

            公司 A 的主页


            输出：

            公司 A 是技术领域的领先公司，专门提供创新软件解决方案。该公司成立于 2005 年，总部位于加利福尼亚州旧金山。他们的使命是用尖端产品彻底改变科技行业。主要高管包括首席执行官
            John Doe 和首席技术官 Jane Smith。显著的成就包括跻身财富 500 强并在 2020 年获得技术创新奖。

            </instructions>

            </example>


            <example>

            <instructions>

            输入：

            B 公司主页


            输出：

            B 公司从事医疗保健行业，提供一流的医疗设备和服务。该公司成立于 1998 年，总部位于纽约市。他们的愿景是通过先进技术增进全球健康。领导团队由首席执行官
            Alice Johnson 和首席运营官 Robert Brown 领导。重要里程碑包括开发突破性的 MRI 机器和在 2018 年获得 HealthTech
            卓越奖。

            </instructions>

            </example>


            <example>

            <instructions>

            输入：

            公司 C 主页


            输出：

            公司 C 是汽车行业的知名企业，以制造高性能电动汽车而闻名。该公司成立于 2010 年，位于密歇根州底特律。他们的使命是通过可持续能源解决方案推动交通运输的未来。执行团队包括首席执行官
            Michael Green 和首席财务官 Laura White。主要成就包括推出首款全自动电动汽车，并在 2021 年被评为年度汽车制造商。

            </instructions>

            </example>

            </examples>'
        - id: 02f7eb65-0f78-47cf-95ed-4f725a7728c8
          role: user
          text: '公司信息: {{#1724963406271.result#}}'
        selected: false
        title: 总结公司信息
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724963438612'
      position:
        x: 2766
        y: 478.5
      positionAbsolute:
        x: 2766
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        assigned_variable_selector:
        - conversation
        - company_info
        desc: ''
        input_variable_selector:
        - '1724963438612'
        - text
        selected: false
        title: Variable Assigner
        type: assigner
        write_mode: over-write
      height: 88
      id: '1724963505855'
      position:
        x: 3070
        y: 478.5
      positionAbsolute:
        x: 3070
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: 从互联网上收集有关贵公司的信息......
        desc: ''
        selected: false
        title: 直接回复
        type: answer
        variables: []
      height: 102
      id: '1724963567827'
      position:
        x: 3070
        y: 1286
      positionAbsolute:
        x: 3070
        y: 1286
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: '能否确认一下你是否在{{#1724912779215.company#}}面试 {{#1724912779215.role#}}职位？ '
        desc: ''
        selected: false
        title: 直接回复
        type: answer
        variables: []
      height: 140
      id: '1724963628776'
      position:
        x: 638
        y: 281.5
      positionAbsolute:
        x: 638
        y: 281.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: '{{#1724963438612.text#}}'
        desc: ''
        selected: false
        title: 直接回复
        type: answer
        variables: []
      height: 105
      id: '1724963776867'
      position:
        x: 3374
        y: 478.5
      positionAbsolute:
        x: 3374
        y: 478.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        cases:
        - case_id: 'true'
          conditions:
          - comparison_operator: empty
            id: 5f77d9ff-cfe0-4ba4-bd78-310750cc8db0
            value: ''
            varType: string
            variable_selector:
            - conversation
            - company_info
          id: 'true'
          logical_operator: and
        - case_id: 0dad4dbf-9e2c-46be-a133-c915c34772dc
          conditions:
          - comparison_operator: empty
            id: acabfa1b-a2c6-4f52-aa84-aee57d1b858b
            value: ''
            varType: string
            variable_selector:
            - conversation
            - interview_qns
          id: 0dad4dbf-9e2c-46be-a133-c915c34772dc
          logical_operator: and
        desc: ''
        selected: false
        title: 条件分支
        type: if-else
      height: 174
      id: '1724964287707'
      position:
        x: 638
        y: 462.5
      positionAbsolute:
        x: 638
        y: 462.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: c81af202-eae2-43a2-9dd9-a80a27b8877c
          role: system
          text: "<instructions>\nGenerate a potential interview question for {{#1724912779215.role#}}\
            \ and a {{#1724912779215.company#}} that has does the following.\n{{#conversation.company_info#}}\
            \ \n\nFollow these steps:\n\n1. Identify the key responsibilities and\
            \ skills required for the role within the company that specializes in\
            \ xxx.\n2. Consider the unique aspects of the company and its specialization\
            \ in xxx.\n3. Formulate a question that assesses the candidate's knowledge,\
            \ experience, and suitability for the role in the context of the company's\
            \ specialization.\n4. Ensure the question is open-ended to allow the candidate\
            \ to provide a detailed response.\n5. Avoid using any XML tags and output\
            \ only the question and nothing else in the output.\n\nThe goal is to\
            \ create a question that not only evaluates the candidate's technical\
            \ skills but also their understanding of the company's niche and how they\
            \ can contribute to its success.\n\n</instructions>\n\n<examples>\n<example>\n\
            Input: \nRole: Data Scientist\nCompany Specialization: Healthcare Analytics\n\
            \nOutput: \nCan you describe a project where you used data analytics to\
            \ improve healthcare outcomes? What challenges did you face and how did\
            \ you overcome them?\n\n</example>\n\n<>\n<example input> \nRole: Software\
            \ Engineer\nCompany Specialization: Financial Technology (FinTech)\n\n\
            <example output> \nHow have you previously contributed to the development\
            \ of secure and scalable financial applications? Can you provide an example\
            \ of a specific project and the technologies you used?\n\n</>\n\n<>\n\
            <example input> \nRole: Marketing Manager\nCompany Specialization: Eco-friendly\
            \ Consumer Products\n\n<example output>\nWhat strategies have you implemented\
            \ in the past to successfully market eco-friendly products? How did you\
            \ measure the effectiveness of these strategies?\n\n</>\n</examples>"
        selected: false
        title: LLM 1
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724965395766'
      position:
        x: 942
        y: 615.5
      positionAbsolute:
        x: 942
        y: 615.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: ab7d4c1b-4813-4b8b-8a8a-d8db84ce2f61
          role: system
          text: "<instructions>\nGenerate a potential interview question for {{#1724912779215.role#}}\
            \ and a {{#1724912779215.company#}} that has does the following.\n{{#conversation.company_info#}}\
            \ \n\nFollow these steps:\n\n1. Identify the key responsibilities and\
            \ skills required for the role within the company that specializes in\
            \ xxx.\n2. Consider the unique aspects of the company and its specialization\
            \ in xxx.\n3. Formulate a question that assesses the candidate's knowledge,\
            \ experience, and suitability for the role in the context of the company's\
            \ specialization.\n4. Ensure the question is open-ended to allow the candidate\
            \ to provide a detailed response.\n5. Avoid using any XML tags and output\
            \ only the question and nothing else in the output.\n\nThe goal is to\
            \ create a question that not only evaluates the candidate's technical\
            \ skills but also their understanding of the company's niche and how they\
            \ can contribute to its success.\n\n</instructions>\n\n<examples>\n<example>\n\
            Input: \nRole: Data Scientist\nCompany Specialization: Healthcare Analytics\n\
            \nOutput: \nCan you describe a project where you used data analytics to\
            \ improve healthcare outcomes? What challenges did you face and how did\
            \ you overcome them?\n\n</example>\n\n<>\n<example input> \nRole: Software\
            \ Engineer\nCompany Specialization: Financial Technology (FinTech)\n\n\
            <example output> \nHow have you previously contributed to the development\
            \ of secure and scalable financial applications? Can you provide an example\
            \ of a specific project and the technologies you used?\n\n</>\n\n<>\n\
            <example input> \nRole: Marketing Manager\nCompany Specialization: Eco-friendly\
            \ Consumer Products\n\n<example output>\nWhat strategies have you implemented\
            \ in the past to successfully market eco-friendly products? How did you\
            \ measure the effectiveness of these strategies?\n\n</>\n</examples>"
        selected: false
        title: LLM 2
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724965405707'
      position:
        x: 942
        y: 752.5
      positionAbsolute:
        x: 942
        y: 752.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: 89b9a36d-fbe0-4359-8dbc-cbeac27fc8dc
          role: system
          text: "<instructions>\nGenerate a potential interview question for {{#1724912779215.role#}}\
            \ and a {{#1724912779215.company#}} that has does the following.\n{{#conversation.company_info#}}\
            \ \n\nFollow these steps:\n\n1. Identify the key responsibilities and\
            \ skills required for the role within the company that specializes in\
            \ xxx.\n2. Consider the unique aspects of the company and its specialization\
            \ in xxx.\n3. Formulate a question that assesses the candidate's knowledge,\
            \ experience, and suitability for the role in the context of the company's\
            \ specialization.\n4. Ensure the question is open-ended to allow the candidate\
            \ to provide a detailed response.\n5. Avoid using any XML tags and output\
            \ only the question and nothing else in the output.\n\nThe goal is to\
            \ create a question that not only evaluates the candidate's technical\
            \ skills but also their understanding of the company's niche and how they\
            \ can contribute to its success.\n\n</instructions>\n\n<examples>\n<example>\n\
            Input: \nRole: Data Scientist\nCompany Specialization: Healthcare Analytics\n\
            \nOutput: \nCan you describe a project where you used data analytics to\
            \ improve healthcare outcomes? What challenges did you face and how did\
            \ you overcome them?\n\n</example>\n\n<>\n<example input> \nRole: Software\
            \ Engineer\nCompany Specialization: Financial Technology (FinTech)\n\n\
            <example output> \nHow have you previously contributed to the development\
            \ of secure and scalable financial applications? Can you provide an example\
            \ of a specific project and the technologies you used?\n\n</>\n\n<>\n\
            <example input> \nRole: Marketing Manager\nCompany Specialization: Eco-friendly\
            \ Consumer Products\n\n<example output>\nWhat strategies have you implemented\
            \ in the past to successfully market eco-friendly products? How did you\
            \ measure the effectiveness of these strategies?\n\n</>\n</examples>"
        selected: false
        title: LLM 3
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724965407816'
      position:
        x: 942
        y: 889.5
      positionAbsolute:
        x: 942
        y: 889.5
      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
          provider: langgenius/openai/openai
        prompt_template:
        - id: d5cb507a-df91-4414-84d5-d3608c5a9e49
          role: system
          text: "<instructions>\nGenerate a potential interview question for {{#1724912779215.role#}}\
            \ and a {{#1724912779215.company#}} that has does the following.\n{{#conversation.company_info#}}\
            \ \n\nFollow these steps:\n\n1. Identify the key responsibilities and\
            \ skills required for the role within the company that specializes in\
            \ xxx.\n2. Consider the unique aspects of the company and its specialization\
            \ in xxx.\n3. Formulate a question that assesses the candidate's knowledge,\
            \ experience, and suitability for the role in the context of the company's\
            \ specialization.\n4. Ensure the question is open-ended to allow the candidate\
            \ to provide a detailed response.\n5. Avoid using any XML tags and output\
            \ only the question and nothing else in the output.\n\nThe goal is to\
            \ create a question that not only evaluates the candidate's technical\
            \ skills but also their understanding of the company's niche and how they\
            \ can contribute to its success.\n\n</instructions>\n\n<examples>\n<example>\n\
            Input: \nRole: Data Scientist\nCompany Specialization: Healthcare Analytics\n\
            \nOutput: \nCan you describe a project where you used data analytics to\
            \ improve healthcare outcomes? What challenges did you face and how did\
            \ you overcome them?\n\n</example>\n\n<>\n<example input> \nRole: Software\
            \ Engineer\nCompany Specialization: Financial Technology (FinTech)\n\n\
            <example output> \nHow have you previously contributed to the development\
            \ of secure and scalable financial applications? Can you provide an example\
            \ of a specific project and the technologies you used?\n\n</>\n\n<>\n\
            <example input> \nRole: Marketing Manager\nCompany Specialization: Eco-friendly\
            \ Consumer Products\n\n<example output>\nWhat strategies have you implemented\
            \ in the past to successfully market eco-friendly products? How did you\
            \ measure the effectiveness of these strategies?\n\n</>\n</examples>"
        selected: false
        title: LLM 4
        type: llm
        variables: []
        vision:
          configs:
            detail: high
          enabled: true
      height: 96
      id: '1724965409826'
      position:
        x: 942
        y: 1026.5
      positionAbsolute:
        x: 942
        y: 1026.5
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: '|No. |问题|

          |---|---|

          |1|{{#1724965395766.text#}}|

          |2|{{#1724965405707.text#}}|

          |3|{{#1724965407816.text#}}|

          |4|{{#1724965409826.text#}}|'
        desc: ''
        selected: false
        title: 回答
        type: answer
        variables: []
      height: 178
      id: '1725955402316'
      position:
        x: 1399.7142857142858
        y: 747.2142857142857
      positionAbsolute:
        x: 1399.7142857142858
        y: 747.2142857142857
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        author: Dify
        desc: ''
        height: 88
        selected: false
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"2.
          网上搜集候选人面试的公司。","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: ' (1)'
        type: ''
        width: 240
      height: 88
      id: '17259897809500'
      position:
        x: 1246
        y: 355.71428571428606
      positionAbsolute:
        x: 1246
        y: 355.71428571428606
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom-note
      width: 240
    - data:
        author: 'Dify '
        desc: ''
        height: 88
        selected: true
        showAuthor: true
        text: '{"root":{"children":[{"children":[{"detail":0,"format":0,"mode":"normal","style":"","text":"3.
          生成面试问题","type":"text","version":1}],"direction":"ltr","format":"","indent":0,"type":"paragraph","version":1,"textFormat":0}],"direction":"ltr","format":"","indent":0,"type":"root","version":1}}'
        theme: blue
        title: ''
        type: ''
        width: 240
      height: 88
      id: '1726021788543'
      position:
        x: 603.4937750827605
        y: 752.5
      positionAbsolute:
        x: 603.4937750827605
        y: 752.5
      selected: true
      sourcePosition: right
      targetPosition: left
      type: custom-note
      width: 240
    viewport:
      x: 54.78672013633752
      y: 127.4523676790916
      zoom: 0.40818354803479734
