Task Agents (SDK)

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TLDR;

Task Agents are Workflow components in which a custom operation on all tasks in the Agent stage can be triggered. This allows you to set up pre-labeling, such as using foundation models such as GPT-4o, automated quality assurance, or any other custom action you need for your workflow.

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Adding Task Agents to your Workflow

To add Task Agents to your Workflow you must add an Agent stage component to your Workflow.

1. Connect the Agent stage in the required place in your Workflow.

2. Click + next to Add pathway and give the pathway a meaningful name. Repeat this step for each additional pathway you want to add. Pathways allow you to connect the Agent stage to other workflow components.

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Configuring Task Agents

Use the Encord SDK to configure your Task Agent. The Task Agent executes the configured SDK script for all tasks that are routed through the Task Agent stage in your Workflow.

# Import dependencies
from encord.user_client import EncordUserClient
from encord.workflow import AgentStage

# Authenticate using the path to your private key
user_client = EncordUserClient.create_with_ssh_private_key(
ssh_private_key_path="<private_key_path>"
)

# Specify the Project that contains the Task agent. Replace <project_hash> with the hash of your Project
project = user_client.get_project(<project_hash>)

# Specify the Task Agent
agent_stage = project.workflow.get_stage(name="Agent 1", type_=AgentStage)
for task in agent_stage.get_tasks():

    # Now you have the agent task containing the data hash
    # Insert you custom logic here

# When the custom logic is completed, the task can be moved forward to the selected pathway
task.proceed(pathway_name="continue to Review")

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Triggering the Task Agent

Task Agents aggregate all tasks that reach the Agent stage in the workflow. Your custom script must be triggered at this stage before the tasks proceed further in the workflow.

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End-to-End Agent Example

We provide an end-to-end example using a Jupyter Notebook here.