All Toolsโ€บMulti-Agent Orchestrator
๐Ÿ”ง Agentic Coding TrendsMay 19, 2026โœ… Tests passing

Multi-Agent Orchestrator

A Python library that allows developers to create, configure, and manage multiple AI coding agents working on interdependent tasks. It provides tools to define agent roles, communicate between agents, and monitor their progress, making it useful for collaborative or multi-step coding workflows.

What It Does

  • Define and manage multiple AI agents with distinct roles.
  • Built-in support for inter-agent communication via pub/sub.
  • Event-driven architecture to handle task dependencies.

Installation

pip install -r requirements.txt

Usage

[Agent1] Completed task 'Task1': Simulated response for Task1 by Developer
[Agent1] Completed task 'Task2': Simulated response for Task2 by Developer
[Agent2] Completed task 'Task3': Simulated response for Task3 by Reviewer

Source Code

import argparse
import asyncio
import json
from typing import List, Dict, Any
from pydantic import BaseModel, ValidationError
import openai

class AgentConfig(BaseModel):
    name: str
    role: str
    tasks: List[str]

class TaskMessage(BaseModel):
    sender: str
    task: str
    content: str

class MultiAgentOrchestrator:
    def __init__(self, config: Dict[str, Any]):
        self.agents = [AgentConfig(**agent) for agent in config.get("agents", [])]
        self.messages = asyncio.Queue()

    async def run(self):
        tasks = [self._run_agent(agent) for agent in self.agents]
        await asyncio.gather(*tasks)

    async def _run_agent(self, agent: AgentConfig):
        for task in agent.tasks:
            await self._process_task(agent, task)

    async def _process_task(self, agent: AgentConfig, task: str):
        try:
            response = await self._simulate_openai_call(agent, task)
            message = TaskMessage(sender=agent.name, task=task, content=response)
            await self.messages.put(message)
            print(f"[{agent.name}] Completed task '{task}': {response}")
        except Exception as e:
            print(f"[{agent.name}] Error processing task '{task}': {e}")

    async def _simulate_openai_call(self, agent: AgentConfig, task: str) -> str:
        await asyncio.sleep(1)  # Simulate API delay
        return f"Simulated response for {task} by {agent.role}"

def parse_args():
    parser = argparse.ArgumentParser(description="Multi-Agent Orchestrator")
    parser.add_argument("--config", required=True, help="Path to configuration JSON file")
    return parser.parse_args()

def main():
    args = parse_args()

    try:
        with open(args.config, "r") as f:
            config = json.load(f)
    except FileNotFoundError:
        print("Error: Configuration file not found.")
        return
    except json.JSONDecodeError:
        print("Error: Invalid JSON in configuration file.")
        return

    try:
        orchestrator = MultiAgentOrchestrator(config)
        asyncio.run(orchestrator.run())
    except ValidationError as e:
        print(f"Configuration validation error: {e}")

if __name__ == "__main__":
    main()

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Details

Tool Name
multi_agent_orchestrator
Category
Agentic Coding Trends
Generated
May 19, 2026
Tests
Passing โœ…

Quick Install

Clone just this tool:

git clone --depth 1 --filter=blob:none --sparse \
  https://github.com/ptulin/autoaiforge.git
cd autoaiforge
git sparse-checkout set generated_tools/2026-05-19/multi_agent_orchestrator
cd generated_tools/2026-05-19/multi_agent_orchestrator
pip install -r requirements.txt 2>/dev/null || true
python multi_agent_orchestrator.py
Multi-Agent Orchestrator โ€” AI Tools by AutoAIForge