MacOS Agent.yml

app:
  description: MacOS Agent, achieve user's goal using applescript.
  icon: "\U0001F916"
  icon_background: '#FFEAD5'
  mode: advanced-chat
  name: MacOS Agent
workflow:
  features:
    file_upload:
      image:
        enabled: false
        number_limits: 3
        transfer_methods:
        - local_file
        - remote_url
    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: code
      id: llm-source-1720603933600-target
      source: llm
      sourceHandle: source
      target: '1720603933600'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: code
        targetType: http-request
      id: 1720603933600-source-1720603954849-target
      source: '1720603933600'
      sourceHandle: source
      target: '1720603954849'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: http-request
        targetType: llm
      id: 1720603968110-source-llm-target
      source: '1720603968110'
      sourceHandle: source
      target: llm
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: llm
        targetType: answer
      id: 1720604011717-source-answer-target
      source: '1720604011717'
      sourceHandle: source
      target: answer
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: start
        targetType: code
      id: 1720603854640-source-1720604039714-target
      source: '1720603854640'
      sourceHandle: source
      target: '1720604039714'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: code
        targetType: http-request
      id: 1720604039714-source-1720603968110-target
      source: '1720604039714'
      sourceHandle: source
      target: '1720603968110'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: http-request
        targetType: if-else
      id: 1720603954849-source-1720701168680-target
      source: '1720603954849'
      sourceHandle: source
      target: '1720701168680'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: llm
      id: 1720701168680-true-1720604011717-target
      source: '1720701168680'
      sourceHandle: 'true'
      target: '1720604011717'
      targetHandle: target
      type: custom
      zIndex: 0
    - data:
        isInIteration: false
        sourceType: if-else
        targetType: answer
      id: 1720701168680-false-1720701198958-target
      source: '1720701168680'
      sourceHandle: 'false'
      target: '1720701198958'
      targetHandle: target
      type: custom
      zIndex: 0
    nodes:
    - data:
        desc: ''
        selected: false
        title: Start
        type: start
        variables: []
      height: 54
      id: '1720603854640'
      position:
        x: 30
        y: 282
      positionAbsolute:
        x: 30
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        context:
          enabled: false
          variable_selector: []
        desc: Retrieve the script from the LLM.
        memory:
          role_prefix:
            assistant: ''
            user: ''
          window:
            enabled: false
            size: 10
        model:
          completion_params:
            temperature: 0.7
          mode: chat
          name: deepseek-chat
          provider: deepseek
        prompt_template:
        - id: 0c599526-2f75-4238-a182-c5824184e45f
          role: system
          text: '{{#1720603968110.body#}}'
        selected: false
        title: LLM:get_script
        type: llm
        variables: []
        vision:
          enabled: false
      height: 128
      id: llm
      position:
        x: 942
        y: 282
      positionAbsolute:
        x: 942
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: '{{#1720604011717.text#}}'
        desc: ''
        selected: false
        title: Answer:with_execution
        type: answer
        variables: []
      height: 107
      id: answer
      position:
        x: 2462
        y: 282
      positionAbsolute:
        x: 2462
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        code: "import json\n\ndef main(llm_output: str, user_input: str) -> dict:\n\
          \    # Ensure the llm_output is properly formatted for JSON\n    llm_output_formatted\
          \ = json.dumps(llm_output)\n    user_input_formatted = json.dumps(user_input)\n\
          \    return {\n        \"llm_output_formatted\": llm_output_formatted,\n\
          \        \"user_input_formatted\": user_input_formatted, \n    }"
        code_language: python3
        desc: Format variables as JSON values.
        outputs:
          llm_output_formatted:
            children: null
            type: string
          user_input_formatted:
            children: null
            type: string
        selected: false
        title: Code:format_params
        type: code
        variables:
        - value_selector:
          - llm
          - text
          variable: llm_output
        - value_selector:
          - sys
          - query
          variable: user_input
      height: 84
      id: '1720603933600'
      position:
        x: 1246
        y: 282
      positionAbsolute:
        x: 1246
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        authorization:
          config: null
          type: no-auth
        body:
          data: "{\n    \"point\": \"execute_script\",\n    \"params\": {\n      \
            \  \"user_id\": \"{{#sys.user_id#}}\",\n        \"inputs\": {\n      \
            \      \"user_input\": {{#1720603933600.user_input_formatted#}},\n\n \
            \           \"llm_output\": {{#1720603933600.llm_output_formatted#}},\n\
            \             \"script_timeout\": {{#1720604039714.script_timeout#}}\n\
            \        }\n    }\n}"
          type: json
        desc: Send the LLM output to the Agent for execution.
        headers: Authorization:Bearer {{#1720604039714.agent_api_key#}}
        method: post
        params: ''
        selected: false
        timeout:
          max_connect_timeout: 0
          max_read_timeout: 0
          max_write_timeout: 0
        title: Agent:execute_script
        type: http-request
        url: '{{#1720604039714.agent_api_endpoint#}}'
        variables: []
      height: 141
      id: '1720603954849'
      position:
        x: 1550
        y: 282
      positionAbsolute:
        x: 1550
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        authorization:
          config: null
          type: no-auth
        body:
          data: "{\n    \"point\": \"get_llm_system_prompt\",\n    \"params\": {\n\
            \        \"user_id\": \"{{#sys.user_id#}}\"\n    }\n}"
          type: json
        desc: Retrieve the LLM system prompt from the macOS Agent server.
        headers: Authorization:Bearer {{#1720604039714.agent_api_key#}}
        method: post
        params: ''
        selected: false
        timeout:
          max_connect_timeout: 0
          max_read_timeout: 0
          max_write_timeout: 0
        title: Agent:get_llm_system_prompt
        type: http-request
        url: '{{#1720604039714.agent_api_endpoint#}}'
        variables: []
      height: 141
      id: '1720603968110'
      position:
        x: 638
        y: 282
      positionAbsolute:
        x: 638
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        context:
          enabled: false
          variable_selector: []
        desc: Use reply_prompt that includes "execution" as the system prompt for
          the LLM to respond to user input.
        memory:
          query_prompt_template: '{{#sys.query#}}'
          role_prefix:
            assistant: ''
            user: ''
          window:
            enabled: true
            size: 50
        model:
          completion_params:
            temperature: 0.7
          mode: chat
          name: deepseek-chat
          provider: deepseek
        prompt_template:
        - id: 60cbca91-199d-4764-90d9-2851ab63c9ae
          role: system
          text: '{{#1720603954849.body#}}'
        selected: false
        title: LLM:reply
        type: llm
        variables: []
        vision:
          enabled: false
      height: 164
      id: '1720604011717'
      position:
        x: 2158
        y: 282
      positionAbsolute:
        x: 2158
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        code: "\ndef main() -> dict:\n    config = {\n        \"agent_api_endpoint\"\
          : \"http://host.docker.internal:8088\",\n        \"agent_api_key\": \"a-secret-key\"\
          ,\n        \"script_timeout\": 60\n    }\n    return {\n        \"agent_api_endpoint\"\
          : config[\"agent_api_endpoint\"],\n        \"agent_api_key\": config[\"\
          agent_api_key\"],\n        \"script_timeout\": config[\"script_timeout\"\
          ],\n    }\n"
        code_language: python3
        desc: Configuration for macOS Agent Server.
        outputs:
          agent_api_endpoint:
            children: null
            type: string
          agent_api_key:
            children: null
            type: string
          script_timeout:
            children: null
            type: number
        selected: true
        title: Code:config
        type: code
        variables: []
      height: 102
      id: '1720604039714'
      position:
        x: 334
        y: 282
      positionAbsolute:
        x: 334
        y: 282
      selected: true
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        conditions:
        - comparison_operator: not empty
          id: '1720701184521'
          value: ''
          variable_selector:
          - '1720603954849'
          - body
        desc: if any script execution result
        logical_operator: and
        selected: false
        title: IF:script_execution
        type: if-else
      height: 156
      id: '1720701168680'
      position:
        x: 1854
        y: 282
      positionAbsolute:
        x: 1854
        y: 282
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    - data:
        answer: '{{#llm.text#}}'
        desc: no script execution
        selected: false
        title: Answer:without_execution
        type: answer
        variables: []
      height: 137
      id: '1720701198958'
      position:
        x: 2158
        y: 486
      positionAbsolute:
        x: 2158
        y: 486
      selected: false
      sourcePosition: right
      targetPosition: left
      type: custom
      width: 244
    viewport:
      x: 58.32490827558104
      y: 176.2416089142547
      zoom: 0.5618969968745753