Table of contents
Official Content
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The following samples show how to use The Lab via PyGEAI for Agents, Tools, Tasks, and Agentic Processes. They are organized into three usage levels:

  • Command Line: The geai ai-lab command allows you to execute actions from the command line.
  • Low-Level Service Layer: The AgentClient, ToolClient, ReasoningStrategyClient, and AgenticProcessClient classes provide a Low-Level Interface for interacting with The Lab’s APIs.
  • High-Level Service Layer: The AILabManager class provides a High-Level Interface for creating and managing Agents, Agentic Processes, and Tools.

Agents

Create Agent

Creates a new AI Agent in a specified project, defining its name, access scope, prompt instructions, LLM settings, and other configurations.

Command Line

geai ai-lab create-agent \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --name "Public Translator V2" \
  --access-scope "public" \
  --public-name "com.genexus.geai.public_translator" \
  --job-description "Translates" \
  --avatar-image "https://www.shareicon.net/data/128x128/2016/11/09/851442_logo_512x512.png" \
  --description "Agent that translates from any language to english." \
  --agent-data-prompt-instructions "the user will provide a text, you must return the same text translated to english" \
  --agent-data-prompt-input "text" \
  --agent-data-prompt-input "avoid slang indicator" \
  --agent-data-prompt-output '{"key": "translated_text", "description": "translated text, with slang or not depending on the indication. in plain text."}' \
  --agent-data-prompt-output '{"key": "summary", "description": "a summary in the original language of the text to be translated, also in plain text."}' \
  --agent-data-prompt-example '{"inputData": "opitiiiis mundo no-slang", "output": "{\"translated_text\":\"hello world\",\"Summary\":\"saludo\"}"}' \
  --agent-data-llm-max-tokens 5000 \
  --agent-data-llm-timeout 0 \
  --agent-data-llm-temperature 0.5 \
  --agent-data-model-name "gpt-4-turbo-preview" \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.agents.clients import AgentClient
client = AgentClient()
response = client.create_agent(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    name="Public Translator V2",
    access_scope="public",
    public_name="com.genexus.geai.public_translator",
    job_description="Translates",
    avatar_image="https://www.shareicon.net/data/128x128/2016/11/09/851442_logo_512x512.png",
    description="Agent that translates from any language to english.",
    agent_data_prompt={
        "instructions": "the user will provide a text, you must return the same text translated to english",
        "inputs": ["text", "avoid slang indicator"],
        "outputs": 
            {"key": "translated_text", "description": "translated text, with slang or not depending on the indication. in plain text."},
            {"key": "summary", "description": "a summary in the original language of the text to be translated, also in plain text."}
        ,
        "examples": 
            {"inputData": "opitiiiis mundo [no-slang", "output": "{\"translated_text\":\"hello world\",\"Summary\":\"saludo\"}"}
        ]
    },
    agent_data_llm_config={
        "maxTokens": 5000,
        "timeout": 0,
        "temperature": 0.5
    },
    agent_data_models={"name": "gpt-4-turbo-preview"},
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import Agent, AgentData, Prompt, PromptOutput, PromptExample, LlmConfig, ModelList, Model
manager = AILabManager()

prompt = Prompt(
    instructions="the user will provide a text, you must return the same text translated to english",
    inputs="text", "avoid slang indicator",
    outputs=
        PromptOutput(key="translated_text", description="translated text, with slang or not depending on the indication. in plain text."),
        PromptOutput(key="summary", description="a summary in the original language of the text to be translated, also in plain text.")
    ,
    examples=
        PromptExample(input_data="opitiiiis mundo [no-slang", output="{\"translated_text\":\"hello world\",\"Summary\":\"saludo\"}")
    ]
)
llm_config = LlmConfig(max_tokens=5000, timeout=0, temperature=0.5)
models = ModelList(models=Model(name="gpt-4-turbo-preview"))
agent_data = AgentData(prompt=prompt, llm_config=llm_config, models=models)

agent = Agent(
    name="Public Translator V2",
    access_scope="public",
    public_name="com.genexus.geai.public_translator",
    job_description="Translates",
    avatar_image="https://www.shareicon.net/data/128x128/2016/11/09/851442_logo_512x512.png",
    description="Agent that translates from any language to english.",
    agent_data=agent_data
)

created_agent = manager.create_agent(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent=agent,
    automatic_publish=False
)
print(created_agent)

Update Agent

Updates the configuration of an existing Agent, including its name, prompt instructions, or LLM settings.

Command Line

geai ai-lab update-agent \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --agent-id "agent-123" \
  --name "Public Translator V3" \
  --description "Updated agent for translations." \
  --agent-data-prompt-instructions "the user provides text, translate it to English accurately" \
  --agent-data-llm-temperature 0.7 \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.agents.clients import AgentClient
client = AgentClient()
response = client.update_agent(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent_id="agent-123",
    name="Public Translator V3",
    description="Updated agent for translations.",
    agent_data_prompt={
        "instructions": "the user provides text, translate it to English accurately"
    },
    agent_data_llm_config={
        "temperature": 0.7
    },
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import Agent, AgentData, Prompt, LlmConfig

manager = AILabManager()

agent = Agent(
    name="Public Translator V3",
    description="Updated agent for translations.",
    agent_data=AgentData(
        prompt=Prompt(instructions="the user provides text, translate it to English accurately"),
        llm_config=LlmConfig(temperature=0.7)
    )
)

updated_agent = manager.update_agent(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent_id="agent-123",
    agent=agent,
    automatic_publish=False
)
print(updated_agent)

List Agents

Retrieves a list of Agents in a specified project, with optional filters for status, pagination, scope, and draft inclusion.

Command Line

geai ai-lab list-agents \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --status "active" \
  --allow-drafts 0 \
  --allow-external 1

Low-Level Service Layer

from pygeai.lab.agents.clients import AgentClient

client = AgentClient()
response = client.list_agents(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    status="active",
    allow_drafts=False,
    allow_external=True
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import FilterSettings
manager = AILabManager()

filters = FilterSettings(
    status="active",
    allow_drafts=False,
    allow_external=True
)
agent_list = manager.get_agent_list(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    filter_settings=filters
)
print(agent_list)

Delete Agent

Deletes an Agent from a specified project using its ID.

Command Line

geai ai-lab delete-agent \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --agent-id "agent-123"

Low-Level Service Layer

from pygeai.lab.agents.clients import AgentClient
client = AgentClient()
response = client.delete_agent(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent_id="agent-123"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
manager = AILabManager()
response = manager.delete_agent(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent_id="agent-123"
)
print(response)

Publish Agent Revision

Publishes a revision of an Agent, making it available for use.

Command Line

geai ai-lab publish-agent-revision \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --agent-id "agent-123"

Low-Level Service Layer

from pygeai.lab.agents.clients import AgentClient

client = AgentClient()
response = client.publish_agent_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent_id="agent-123"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager

manager = AILabManager()
response = manager.publish_agent_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    agent_id="agent-123"
)
print(response)

Tools

Create Tool

Creates a new Tool in a specified project, defining its name, description, scope, and parameters for use by Agents.

Command Line

geai ai-lab create-tool \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --name "sample tool V3" \
  --description "a builtin tool that does something but really does nothing cos it does not exist." \
  --scope "builtin" \
  --parameter '{"key": "input", "dataType": "String", "description": "some input that the tool needs.", "isRequired": true}' \
  --parameter '{"key": "some_nonsensitive_id", "dataType": "String", "description": "Configuration that is static, in the sense that whenever the tool is used, the value for this parameter is configured here. The llm will not know about it.", "isRequired": true, "type": "config", "fromSecret": false, "value": "b001e30b4016001f5f76b9ae9215ac40"}' \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.tools.clients import ToolClient

client = ToolClient()
response = client.create_tool(
project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
name="sample tool V3",
description="a builtin tool that does something but really does nothing cos it does not exist.",
scope="builtin",
parameters=
{"key": "input", "dataType": "String", "description": "some input that the tool needs.", "isRequired": True},
{"key": "some_nonsensitive_id", "dataType": "String", "description": "Configuration that is static, in the sense that whenever the tool is used, the value for this parameter is configured here. The llm will not know about it.", "isRequired": True, "type": "config", "fromSecret": False, "value": "b001e30b4016001f5f76b9ae9215ac40"}
,
automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import Tool, ToolParameter
manager = AILabManager()

tool = Tool(
    name="sample tool V3",
    description="a builtin tool that does something but really does nothing cos it does not exist.",
    scope="builtin",
    parameters=
        ToolParameter(
            key="input",
            data_type="String",
            description="some input that the tool needs.",
            is_required=True
        ),
        ToolParameter(
            key="some_nonsensitive_id",
            data_type="String",
            description="Configuration that is static, in the sense that whenever the tool is used, the value for this parameter is configured here. The llm will not know about it.",
            is_required=True,
            type="config",
            from_secret=False,
            value="b001e30b4016001f5f76b9ae9215ac40"
        )
    
)

created_tool = manager.create_tool(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool=tool,
    automatic_publish=False
)
print(created_tool)

Update Tool

Updates the configuration of an existing Tool, including its name, description, or parameters.

Command Line

geai ai-lab update-tool \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --tool-id "tool-456" \
  --name "sample tool V4" \
  --description "Updated builtin tool." \
  --scope "builtin" \
  --parameter '{"key": "input", "dataType": "String", "description": "updated input.", "isRequired": true}' \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.tools.clients import ToolClient

client = ToolClient()
response = client.update_tool(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool_id="tool-456",
    name="sample tool V4",
    description="Updated builtin tool.",
    scope="builtin",
    parameters=
        {"key": "input", "dataType": "String", "description": "updated input.", "isRequired": True}
    ,
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import Tool, ToolParameter

manager = AILabManager()

tool = Tool(
    name="sample tool V4",
    description="Updated builtin tool.",
    scope="builtin",
    parameters=
        ToolParameter(
            key="input",
            data_type="String",
            description="updated input.",
            is_required=True
        )
    
)

updated_tool = manager.update_tool(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool_id="tool-456",
    tool=tool,
    automatic_publish=False
)
print(updated_tool)

Delete Tool

Deletes a Tool from a specified project using its ID.

Command Line

geai ai-lab delete-tool \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --tool-id "tool-456"

Low-Level Service Layer

from pygeai.lab.tools.clients import ToolClient

client = ToolClient()
response = client.delete_tool(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool_id="tool-456"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager

manager = AILabManager()
response = manager.delete_tool(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool_id="tool-456"
)
print(response)

Publish Tool Revision

Publishes a revision of a Tool, making it available for use.

Command Line

geai ai-lab publish-tool-revision \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --tool-id "tool-456"

Low-Level Service Layer

from pygeai.lab.tools.clients import ToolClient

client = ToolClient()
response = client.publish_tool_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool_id="tool-456"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager

manager = AILabManager()
response = manager.publish_tool_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    tool_id="tool-456"
)
print(response)

Tasks

Create Task

Creates a new Task in a specified project, defining its name, description, prompt configuration, and artifact types.

Command Line

geai ai-lab create-task \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --name "Sample v2" \
  --description "A simple task that requires no tools and define no prompt" \
  --title-template "Sample Task" \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient

client = AgenticProcessClient()
response = client.create_task(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    name="Sample v2",
    description="A simple task that requires no tools and define no prompt",
    title_template="Sample Task",
    prompt_data={},
    artifact_types=[],
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import Task, Prompt, ArtifactTypeList

manager = AILabManager()

task = Task(
    name="Sample v2",
    description="A simple task that requires no tools and define no prompt",
    title_template="Sample Task",
    prompt_data=Prompt(),
    artifact_types=ArtifactTypeList(artifact_types=[])
)

created_task = manager.create_task(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task=task,
    automatic_publish=False
)
print(created_task)

Update Task

Updates the configuration of an existing Task, including its name, description, or prompt settings.

Command Line

geai ai-lab update-task \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --task-id "task-789" \
  --name "Sample v3" \
  --description "Updated simple task." \
  --title-template "Updated Sample Task" \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient

client = AgenticProcessClient()
response = client.update_task(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task_id="task-789",
    name="Sample v3",
    description="Updated simple task.",
    title_template="Updated Sample Task",
    prompt_data={},
    artifact_types=[],
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import Task, Prompt, ArtifactTypeList

manager = AILabManager()

task = Task(
    name="Sample v3",
    description="Updated simple task.",
    title_template="Updated Sample Task",
    prompt_data=Prompt(),
    artifact_types=ArtifactTypeList(artifact_types=[])
)

updated_task = manager.update_task(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task_id="task-789",
    task=task,
    automatic_publish=False
)
print(updated_task)

Delete Task

Deletes a Task from a specified project using its ID.

Command Line

geai ai-lab delete-task \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --task-id "task-789"

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient

client = AgenticProcessClient()
response = client.delete_task(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task_id="task-789"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager

manager = AILabManager()
response = manager.delete_task(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task_id="task-789"
)
print(response)

Publish Task Revision

Publishes a revision of a Task, making it available for use.

Command Line

geai ai-lab publish-task-revision \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --task-id "task-789"

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient


client = AgenticProcessClient()
response = client.publish_task_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task_id="task-789"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager


manager = AILabManager()
response = manager.publish_task_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    task_id="task-789"
)
print(response)

Agentic Processes

Create Agentic Process

Creates a new Agentic Process in a specified project, defining its workflow through activities, signals, events, and sequence flows.

Command Line

geai ai-lab create-process \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --key "product_def" \
  --name "Basic Process V4" \
  --description "This is a sample process" \
  --kb '{"name": "basic-sample", "artifactTypeName": "sample-artifact"}' \
  --agentic-activity '{"key": "activityOne", "name": "First Step", "taskName": "basic-task", "agentName": "sample-translator", "agentRevisionId": 0}' \
  --artifact-signal '{"key": "artifact.upload.1", "name": "artifact.upload", "handlingType": "C", "artifactTypeName": "sample-artifact"}' \
  --user-signal '{"key": "signal_done", "name": "process-completed"}' \
  --start-event '{"key": "artifact.upload.1", "name": "artifact.upload"}' \
  --end-event '{"key": "end", "name": "Done"}' \
  --sequence-flow '{"key": "step1", "sourceKey": "artifact.upload.1", "targetKey": "activityOne"}' \
  --sequence-flow '{"key": "step2", "sourceKey": "activityOne", "targetKey": "signal_done"}' \
  --sequence-flow '{"key": "stepEnd", "sourceKey": "signal_done", "targetKey": "end"}' \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient

client = AgenticProcessClient()
response = client.create_process(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    key="product_def",
    name="Basic Process V4",
    description="This is a sample process",
    kb={"name": "basic-sample", "artifactTypeName": "sample-artifact"},
    agentic_activities=
        {"key": "activityOne", "name": "First Step", "taskName": "basic-task", "agentName": "sample-translator", "agentRevisionId": 0}
    ,
    artifact_signals=
        {"key": "artifact.upload.1", "name": "artifact.upload", "handlingType": "C", "artifactTypeName": ["sample-artifact"}
    ],
    user_signals=
        {"key": "signal_done", "name": "process-completed"}
    ,
    start_event={"key": "artifact.upload.1", "name": "artifact.upload"},
    end_event={"key": "end", "name": "Done"},
    sequence_flows=
        {"key": "step1", "sourceKey": "artifact.upload.1", "targetKey": "activityOne"},
        {"key": "step2", "sourceKey": "activityOne", "targetKey": "signal_done"},
        {"key": "stepEnd", "sourceKey": "signal_done", "targetKey": "end"}
    ,
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import AgenticProcess, KnowledgeBase, AgenticActivity, ArtifactSignal, UserSignal, Event, SequenceFlow

manager = AILabManager()

process = AgenticProcess(
    key="product_def",
    name="Basic Process V4",
    description="This is a sample process",
    kb=KnowledgeBase(name="basic-sample", artifact_type_name="sample-artifact"),
    agentic_activities=
        AgenticActivity(
            key="activityOne",
            name="First Step",
            task_name="basic-task",
            agent_name="sample-translator",
            agent_revision_id=0
        )
    ,
    artifact_signals=
        ArtifactSignal(
            key="artifact.upload.1",
            name="artifact.upload",
            handling_type="C",
            artifact_type_name=["sample-artifact"
        )
    ],
    user_signals=
        UserSignal(key="signal_done", name="process-completed")
    ,
    start_event=Event(key="artifact.upload.1", name="artifact.upload"),
    end_event=Event(key="end", name="Done"),
    sequence_flows=
        SequenceFlow(key="step1", source_key="artifact.upload.1", target_key="activityOne"),
        SequenceFlow(key="step2", source_key="activityOne", target_key="signal_done"),
        SequenceFlow(key="stepEnd", source_key="signal_done", target_key="end")
    
)

created_process = manager.create_process(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process=process,
    automatic_publish=False
)
print(created_process)

Update Agentic Process

Updates the configuration of an existing Agentic Process, including its name, description, or workflow components.

Command Line

geai ai-lab update-process \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --process-id "process-101" \
  --key "product_def" \
  --name "Basic Process V5" \
  --description "Updated sample process" \
  --kb '{"name": "basic-sample", "artifactTypeName": "sample-artifact"}' \
  --automatic-publish 0

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient

client = AgenticProcessClient()
response = client.update_process(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process_id="process-101",
    key="product_def",
    name="Basic Process V5",
    description="Updated sample process",
    kb={"name": "basic-sample", "artifactTypeName": "sample-artifact"},
    agentic_activities=[],
    artifact_signals=[],
    user_signals=[],
    start_event={},
    end_event={},
    sequence_flows=[],
    automatic_publish=False
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager
from pygeai.lab.models import AgenticProcess, KnowledgeBase

manager = AILabManager()

process = AgenticProcess(
    key="product_def",
    name="Basic Process V5",
    description="Updated sample process",
    kb=KnowledgeBase(name="basic-sample", artifact_type_name="sample-artifact")
)

updated_process = manager.update_process(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process_id="process-101",
    process=process,
    automatic_publish=False
)
print(updated_process)

Delete Agentic Process

Deletes an Agentic Process from a specified project using its ID.

Command Line

geai ai-lab delete-process \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --process-id "process-101"

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient


client = AgenticProcessClient()
response = client.delete_process(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process_id="process-101"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager


manager = AILabManager()
response = manager.delete_process(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process_id="process-101"
)
print(response)

Publish Process Revision

Publishes a revision of an Agentic Process, making it available for use.

Command Line

geai ai-lab publish-process-revision \
  --project-id "2ca6883f-6778-40bb-bcc1-85451fb11107" \
  --process-id "process-101"

Low-Level Service Layer

from pygeai.lab.processes.clients import AgenticProcessClient

client = AgenticProcessClient()
response = client.publish_process_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process_id="process-101"
)
print(response)

High-Level Service Layer

from pygeai.lab.managers import AILabManager

manager = AILabManager()
response = manager.publish_process_revision(
    project_id="2ca6883f-6778-40bb-bcc1-85451fb11107",
    process_id="process-101"
)
print(response)

Availability

Since version 2025-07.

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