Basic Task Agent Example

Before getting started, ensure that you have:

• python >= 3.10. If you do not have Python 3.10, we recommend using pyenv to manage your Python versions.
• The ability to authenticate with Encord.
• Installed the Encord Agents library.

The following example shows how to create a simple Task Agent to change the priority of each task before moving it to the next stage of the Workflow.

We also provide more detailed Task Agent examples and Editor Agent examples.

1. Create Encord Project

Create a Project in Encord containing the following Workflow with an agent stage.

The purple node in the Workflow is an agent node named pre-label. It has a single pathway called annotate that moves tasks to the next stage in the Workflow.

Copy the Project ID in the top left of the Project page.

Check if your existing Project has any agent nodes by running the following command.

Command

encord-agents print agent-nodes <your_project_hash>

2. Define the Agent

In the directory you created for your agents, create a Python file. In this example we use agent.py.

Copy paste the following template in to the Python file:

agent.py

from encord.objects import LabelRowV2
from encord_agents.tasks import Runner

runner = Runner(project_hash="<your_project_hash>")

@runner.stage(stage="pre-label")
def my_agent_logic(lr: LabelRowV2) -> str:
    # ...
    return "annotate"

if __name__ == "__main__":
    runner.run()

The my_agent_logic function takes a LabelRowV2 instance belonging to a task currently in the "pre-label" agent stage. The agent then returns the name of the pathway the task should follow once completed.

We must define how this data is handled. In this example, we keep it simple by assigning priority based on the file name. If the file name contains "london", it gets assigned a high priority; otherwise, it gets assigned low priority.

@runner.stage(stage="pre-label")
def my_agent_logic(lr: LabelRowV2) -> str:
    lr.set_priority(priority=float("london" in lr.data_title))
    return "annotate"

3. Run the Agent

The Agent must be run in order for tasks to be moved on to the next Workflow stage.

Run the agent by executing the following command:

python agent.py