Plugin AiTool

KestraFlow ​Kestra​Flow

yaml
type: "io.kestra.plugin.ai.tool.kestraflow"
yaml
id: agent_calling_flows_explicitly
namespace: company.ai

inputs:
  - id: use_case
    type: SELECT
    description: Your Orchestration Use Case
    defaults: Hello World
    values:
      - Business Automation
      - Business Processes
      - Data Engineering Pipeline
      - Data Warehouse and Analytics
      - Infrastructure Automation
      - Microservices and APIs
      - Hello World

tasks:
  - id: agent
    type: io.kestra.plugin.ai.agent.AIAgent
    prompt: Execute a flow that best matches the {{ inputs.use_case }} use case selected by the user
    provider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-2.5-flash
      apiKey: "{{ kv('GEMINI_API_KEY') }}"
    tools:
      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: business-automation
        description: Business Automation

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: business-processes
        description: Business Processes

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: data-engineering-pipeline
        description: Data Engineering Pipeline

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: dwh-and-analytics
        description: Data Warehouse and Analytics

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: file-processing
        description: File Processing

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: hello-world
        description: Hello World

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: infrastructure-automation
        description: Infrastructure Automation

      - type: io.kestra.plugin.ai.tool.KestraFlow
        namespace: tutorial
        flowId: microservices-and-apis
        description: Microservices and APIs
yaml
id: agent_calling_flows_implicitly
namespace: company.ai

inputs:
  - id: use_case
    type: SELECT
    description: Your Orchestration Use Case
    defaults: Hello World
    values:
      - Business Automation
      - Business Processes
      - Data Engineering Pipeline
      - Data Warehouse and Analytics
      - Infrastructure Automation
      - Microservices and APIs
      - Hello World

tasks:
  - id: agent
    type: io.kestra.plugin.ai.agent.AIAgent
    prompt: |
      Execute a flow that best matches the {{ inputs.use_case }} use case selected by the user. Use the following mapping of use cases to flow IDs:
      - Business Automation: business-automation
      - Business Processes: business-processes
      - Data Engineering Pipeline: data-engineering-pipeline
      - Data Warehouse and Analytics: dwh-and-analytics
      - Infrastructure Automation: infrastructure-automation
      - Microservices and APIs: microservices-and-apis
      - Hello World: hello-world
      Remember that all those flows are in the tutorial namespace.
    provider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-2.5-flash
      apiKey: "{{ kv('GEMINI_API_KEY') }}"
    tools:
      - type: io.kestra.plugin.ai.tool.KestraFlow
Properties
Default false
Format date-time