AI assistant on the server
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.
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✋ Hello! We are the IT company dZENcode.
We are implementing a multi-agent AI assistant in Python (FastAPI) with CrewAI/AutoGen, Celery+Redis, queue, statuses, retry, Qdrant/pgvector, shell/git tools, deployment via Docker Compose and Web UI or Telegram, relying on the team's experience, best practices, and our own developments.
Which interface is a priority: Web UI, Telegram, or CLI?
Can we use external LLM APIs or is a fully on-prem solution required?
You can find detailed information about our services and rates on our website:Freelancehunt.
Take a look – we will discuss the details of the work further, write when you are ready.
…
The final cost is determined only after clarifying the scope and requirements.
___________________
Sincerely,
Manager of dZENcode
Our strengths:
💎 10+ years providing IT services: Outsourcing, Outstaffing
🔥 90+ in-house specialists
🚀 Projects "from scratch" and for support
⚙️ SLA and post-production support
✅ Contract with the company, guaranteed results!
🔥 250+ public reviews since 2015.
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Hello. An interesting task, in my opinion, this could become a useful project. I would suggest using stacks, particularly Docker for deployment and maintaining the confidentiality of keys through env files. For task management, I think Redis or PostgreSQL would be suitable - this will allow storing the history of tasks and correctly processing statuses. A command interface or a Telegram bot can be implemented for interaction, depending on your preferences. I am ready to consider different technologies and will propose details if needed. Is there already a clear understanding of the scope of work and expected deadlines? Based on the description, I would estimate the project at 600-800 dollars, with a completion time of approximately 14 days with a buffer, considering possible adjustments.
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265 Hello!
I can develop an AI assistant / multi-agent system for you that accepts tasks in the form of text or commands, queues them, does not lose them upon restart, keeps logs, generates reports, and can perform retries.
What I offer regarding the stack (briefly):
Main backend in Python.
For multi-agent logic - Microsoft AutoGen / Microsoft Agent Framework or CrewAI (both are well-suited for orchestrating multiple agents and complex scenarios).
For actions with code, shell, and git - integration with OpenHands (a specialized devops/code agent with a secure environment).
Task and history storage: PostgreSQL.
Memory/context: vector DB (for example, Qdrant).
… Management interface: a simple web task panel (or by agreement, a Telegram bot / CLI).
How it will work:
You create a task through the web panel (or bot/CLI) - it goes into the task queue with the required status.
The system, with the help of AI agents, plans the steps and executes them (shell, scripts, git, etc.), everything is logged.
In case of an error, the task receives a failed status, there is a retry considering idempotency (repeating does not break the state).
All tasks, statuses, reports, and artifacts are stored in the database and do not disappear even after container restarts.
Deployment:
I will package everything in Docker + docker-compose, create an example .env and a clear README for launching.
I am ready to describe the architecture step by step specifically for your scenarios (DevOps, working with code, business processes, etc.) and estimate timelines/budget. Please let me know what types of tasks you plan to automate first.
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2264 18 3 Good day! I specialize in Python automation and deploying AI solutions in Docker. I offer a stack: Python + CrewAI + Celery/Redis + PostgreSQL. This will ensure the fulfillment of all your criteria: queues, statuses, resilience to restarts, and detailed logging. I have experience working with git/shell tools for agents. I have indicated the approximate timelines and costs, but I am ready to clarify them after discussing the preferred interface (Telegram or Web). Write to me.
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8193 63 1 Good day,
I am ready to complete your project for developing an AI assistant or multi-agent system. My technology stack includes PHP, Laravel, Selenium, Puppeteer, HTML\CSS, JavaScript\jQuery, Vue.JS, Mysql, Postgres, MongoDB, GIT, CMS (WordPress, Opencart, Shopify, Simpla), and others.
I will use Laravel to build the architecture, Docker for deploying the system. I plan to integrate with the Telegram bot for task management. I will ensure secure storage of API keys and complete logging of actions.
I am ready to start working and create a fully functional system that meets all the requirements of the project.
Thank you,
… Arthur
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1182 8 1 Hello, Webster Online
I can implement this PoC after preliminary research and a paid consultation.
Please send the application via private message.
Yours, Paul
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882 1 0 Good day.
Your main risk is the agent who "lost" the task or completed it twice after a restart. I will build a system where this is structurally impossible: each task receives a unique ID, the state is stored in PostgreSQL, and Redis serves as a reliable queue. Restarting the container will result in no data loss.
Stack: Go + Redis + PostgreSQL + Claude API + Docker Compose. The agent executes tasks via shell and Git, stores artifacts, and generates a report for each task. The Telegram Bot allows submitting tasks, viewing statuses, and receiving reports in real-time.
Retry and idempotency are not an additional option but part of the core from day one.
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248 Good day. I represent the Nexus Core team.
We have fully studied the task — an autonomous multi-agent system that accepts tasks, executes them without losses, maintains a queue with statuses, supports retries, logging, reporting, and long-term memory for projects. Working with tools: shell, scripts, git repositories, plugin architecture for expansion.
For implementation, we propose the following stack: OpenClaw (our own framework) as the core — we already have a ready base for agents, memory, and tools; Bull + Redis for the task queue — reliability, retries, and persistence out of the box; ChromaDB as a local open-source vector database for long-term memory; Claude 3.5 Sonnet or GPT-4 as the LLM brain for reasoning and code generation; Telegram bot and Next.js Dashboard as management interfaces; PostgreSQL + Docker Compose for storing task history, logs, and artifacts — simple deployment and backups. This stack meets all acceptance criteria: 10 tasks in a row, correct handling of failed + retry, preserving the queue after restarting containers.
Cases are under NDA, but we are ready to discuss in detail the implemented projects of a similar class in private messages.
Write in private messages — we will clarify the requirements for the interface, the number of demonstration scenarios, and the infrastructure, after which we will provide a fixed cost with a breakdown by stages and agreed deadlines.
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172 1 1 Hello! I am ready to complete this project and have extensive experience in developing various applications.
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726 9 1 Hello! Your project looks wonderful. I am ready to start working immediately and complete it at a high level.
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2138 22 2 hello
do you want to go with Clawbot
it costs from 2-3 k dollars
just to describe the terms of reference will be 100-200 dollars
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264 1 0 There is experience in implementing similar projects with agent orchestration.
For management, both a chat interface in Telegram and a web version will be implemented.
Let's communicate to discuss the details.
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