Task Agents (https://app.encord.com/agents/task-agents or https://app.us.encord.com/agents/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.
To add Task Agents to your Workflow you must add an Agent stage component to your Workflow.
Connect the Agent stage in the required place in your Workflow.
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.
Coming Soon! We’re currently evaluating webhooks for the Agent stage. Please let us know if this would help your use-case by reaching out to support@encord.com.
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.
General Example
The General Example script shows how to configure a Task Agent with the name Agent 1
and with a pathway called continue to Review
.
Ensure that you:
<private_key_path>
with the path to your private key.<project_hash>
with the hash of your Project.Pre-Classification of Images Using GPT 4o
The Pre-Classification script uses GPT 4o mini to route images to different annotation stages depending on what it is contained in the image. The Pre-Classification script applies to the following Workflow.
In the following script:
<private_key_path>
with the hash of your private key.<project_hash>
with the hash of your Project.Agent 1
with the name of your Agent stage.Pre-Labeling Videos Using a Mock Model
This guide makes the following assumptions:
encord-agents
library using the following command:The Pre-Labeling Script selects a random class from the Ontology, generates random bounding box labels, and applies random confidence scores for video frames before advancing the videos to the annotation stage (Annotate 1
). Below is an example of a Workflow where the Pre-Labeling agent can be effectively utilized.
To authenticate, you must set either of following environment variables in the environment that you plan to run your agents.
In the following script:
<project_hash>
with the hash of your Project.prelabel_video.py
with your new file name.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.
We provide end-to-end examples using Jupyter Notebooks here.
Task Agents (https://app.encord.com/agents/task-agents or https://app.us.encord.com/agents/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.
To add Task Agents to your Workflow you must add an Agent stage component to your Workflow.
Connect the Agent stage in the required place in your Workflow.
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.
Coming Soon! We’re currently evaluating webhooks for the Agent stage. Please let us know if this would help your use-case by reaching out to support@encord.com.
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.
General Example
The General Example script shows how to configure a Task Agent with the name Agent 1
and with a pathway called continue to Review
.
Ensure that you:
<private_key_path>
with the path to your private key.<project_hash>
with the hash of your Project.Pre-Classification of Images Using GPT 4o
The Pre-Classification script uses GPT 4o mini to route images to different annotation stages depending on what it is contained in the image. The Pre-Classification script applies to the following Workflow.
In the following script:
<private_key_path>
with the hash of your private key.<project_hash>
with the hash of your Project.Agent 1
with the name of your Agent stage.Pre-Labeling Videos Using a Mock Model
This guide makes the following assumptions:
encord-agents
library using the following command:The Pre-Labeling Script selects a random class from the Ontology, generates random bounding box labels, and applies random confidence scores for video frames before advancing the videos to the annotation stage (Annotate 1
). Below is an example of a Workflow where the Pre-Labeling agent can be effectively utilized.
To authenticate, you must set either of following environment variables in the environment that you plan to run your agents.
In the following script:
<project_hash>
with the hash of your Project.prelabel_video.py
with your new file name.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.
We provide end-to-end examples using Jupyter Notebooks here.