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Task management for AI agents
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pip install taskara
Create a task
from taskara import Task
task = Task(
description="Search for the most common varieties of french ducks",
owner_id="delores@agentsea.ai"
)
Assign the task to an agent
task.assigned_to = "roko@agentsea.ai"
Post a message to the task thread
task.post_message("assistant", "Getting started working on this")
task.status = "in progress"
Create a custom thread for the task
task.create_thread("debug")
task.post_message("assistant", "I'll post debug messages to this thread", thread="debug")
task.post_message("assistant", 'My current screenshot', images=["b64img"], thread="debug")
Store prompts used to accomplish the task
from mllm import RoleThread, RoleMessage
thread = RoleThread()
thread.post(role="system", msg="I am a helpful assistant")
response = RoleMessage(
role="assistant",
text="How can I help?"
)
task.store_prompt(thread, response, namespace="actions")
Store the result
task.output = "The most common type of french duck is the Rouen"
task.status = "success"
Save the task
task.save()
Taskara comes with a task tracker server which can be run on docker or kubernetes.
Install surfkit to create a tracker
pip install surfkit
Create a tracker
surfkit create tracker
List trackers
surfkit list trackers
Get tracker logs
surfkit logs tracker <name>
Create a task
surfkit create task --description "Search for french ducks"
List tasks
surfkit list tasks
Get a task
surfkit get task <id>
Taskara is integrated with:
Come join us on Discord.
Thread and prompt storage can be backed by:
Sqlite will be used by default. To use postgres simply configure the env vars:
DB_TYPE=postgres
DB_NAME=tasks
DB_HOST=localhost
DB_USER=postgres
DB_PASS=abc123
Thread image storage by default will utilize the db, to configure bucket storage using GCS:
export THREAD_STORAGE_SA_JSON='{
"type": "service_account",
...
}'
export THREAD_STORAGE_BUCKET=my-bucket
FAQs
Task management for AI agents
We found that taskara demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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