dify-workflow-generator/ai_data_analysis.yml at master · SevenDataAI/dify-workflow-generator · GitHub

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version: 0.5.0
kind: app
app:
  name: AI 智能问数
  mode: workflow
  icon: 📊
  icon_background: '#FFEAD5'
  description: 将自然语言转换为 SQL 查询并分析数据结果
  use_icon_as_answer_icon: false
workflow:
  graph:
    nodes:
    - id: start
      position:
        x: 100
        y: 300
      width: 244
      height: 54
      data:
        type: start
        title: Start
        desc: ''
        variables:
        - variable: query
          type: string
          label: 数据问题
          required: true
          max_length: 256
          default: ''
          options: []
        - variable: table_schema
          type: string
          label: 表结构
          required: false
          max_length: 256
          default: CREATE TABLE sales (date DATE, amount DECIMAL, region VARCHAR)
          options: []
    - id: d7579be0
      position:
        x: 400
        y: 100
      width: 244
      height: 54
      data:
        type: llm
        title: 生成SQL
        desc: ''
        model:
          provider: openai
          name: gpt-4
          mode: chat
          completion_params:
            temperature: 0.7
            max_tokens: 4096
        prompt_template:
        - role: user
          text: '你是一个数据分析师。根据以下表结构，将用户问题转换为 SQL 查询语句。


            表结构：

            {{#start.table_schema#}}


            用户问题：

            {{#start.query#}}


            请只输出 SQL 语句，不要包含其他解释。'
    - id: f3dc8e41
      position:
        x: 700
        y: 100
      width: 244
      height: 54
      data:
        type: code
        title: 执行查询
        desc: ''
        code_language: python3
        code: "def main(args):\n    sql = args.get(\"sql\")\n    # 这里模拟数据库返回结果\n \
          \   # 实际项目中，这里会连接数据库执行 SQL\n    print(f\"Executing: {sql}\")\n    \n   \
          \ mock_data = [\n        {\"date\": \"2024-01-01\", \"amount\": 1000, \"\
          region\": \"North\"},\n        {\"date\": \"2024-01-02\", \"amount\": 1500,\
          \ \"region\": \"South\"}\n    ]\n    \n    return {\n        \"result\"\
          : mock_data,\n        \"status\": \"success\"\n    }\n"
        variables:
        - variable: sql
          value_selector:
          - 生成SQL
          - text
        outputs:
        - variable: result
          type: array-object
    - id: 70e52fd5
      position:
        x: 100
        y: 300
      width: 244
      height: 54
      data:
        type: llm
        title: 分析结果
        desc: ''
        model:
          provider: openai
          name: gpt-4
          mode: chat
          completion_params:
            temperature: 0.7
            max_tokens: 4096
        prompt_template:
        - role: user
          text: '根据执行的 SQL 和数据结果，回答用户的问题。


            问题：{{#start.query#}}

            SQL：{{#生成SQL.text#}}

            数据结果：

            {{#执行查询.result#}}


            请用通俗易懂的语言总结数据洞察。'
    - id: 743de7ae
      position:
        x: 400
        y: 300
      width: 244
      height: 54
      data:
        type: end
        title: End
        desc: ''
        outputs:
        - variable: answer
          value_selector:
          - 分析结果
          - text
        - variable: sql
          value_selector:
          - 生成SQL
          - text
    edges:
    - id: edge_0
      source: start
      target: d7579be0
      sourceHandle: source
      targetHandle: target
    - id: edge_1
      source: d7579be0
      target: f3dc8e41
      sourceHandle: source
      targetHandle: target
    - id: edge_2
      source: f3dc8e41
      target: 70e52fd5
      sourceHandle: source
      targetHandle: target
    - id: edge_3
      source: 70e52fd5
      target: 743de7ae
      sourceHandle: source
      targetHandle: target
  features: {}
  environment_variables: []
  conversation_variables: []