๐ง Agentic Coding TrendsMay 19, 2026โ
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.txtUsage
[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 ReviewerSource 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()Community
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Details
- Tool Name
- multi_agent_orchestrator
- Category
- Agentic Coding Trends
- Generated
- May 19, 2026
- Tests
- Passing โ
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