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Task management for AI agents

Project description


Taskara

Task management for AI agents
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Installation

pip install taskara

Usage

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

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()

Backends

Thread and prompt storage can be backed by:

  • Sqlite
  • Postgresql

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

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