1.It is necessary to develop an AI assistant or multi-agent system that:
Takes tasks in the form of commands or text descriptions.
Executes them autonomously or semi-autonomously.
Does not lose task execution.
Has a task queue and execution statuses.
Supports retry attempts.
Keeps a log of actions.
Generates a report on the results.
Stores task history and artifacts including files and results.
Can work with tools such as shell, scripts, git repositories, and integrations.
Technology selection
The performer must choose one of the options or propose a combination and justify the choice.
AutoGen Microsoft multi-agent orchestration Planner Executor Reviewer
OpenHands autonomous dev ops agent for task execution and working with tools
CrewAI multi-agent roles and coordination
Claude Code as LLM brain inside the system
OpenClaw or Clow Bot optionally if experience is available
The response must indicate:
What stack will be used.
Why it was chosen.
How the architecture will be implemented.
What needs to be implemented
3.1 Deployment
Installation and launch via Docker preferably docker compose.
Simple launch instruction README.
Secure storage of API keys through env file.
Ability to restart without data loss.
3.2 Task management
The system must include:
Task Queue.
Task statuses new, in progress, done, failed, paused.
Retry mechanism.
Idempotency so that a retry does not create conflicts.
Complete logging of actions including commands, changes, and files.
Report for each task with a description of actions taken and results.
Storage of task history for at least 30 days through a database or files.
3.3 Memory and context
Short-term context for the current task.
Long-term memory for projects, rules, and previous tasks through a vector database or structured database.
Ability to set assistant operation rules.
3.4 Tools and automation
Execution of actions through shell and scripts.
Working with git including clone, branch, and commit according to an agreed template.
Ability to add new tools through a plugin architecture.
3.5 Management interface
At least one option needs to be implemented:
Telegram bot
or
Web UI simple task panel
or
CLI
Implementation of two interfaces is allowed.
Project result
A fully operational system deployed on the server.
Docker compose file.
Example env file.
Brief usage instruction.
Five or ten demonstration scenarios task execution report.
Access to logs and task history.
Acceptance criteria
I create ten tasks in a row. All appear in the queue and correctly change statuses.
Two tasks intentionally cause an error. The system records the status failed, shows the reason, and retry works correctly.
After restarting the containers, the task queue and statuses are preserved.
Reports on tasks are available and saved.