repo_description: The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework. Website: https://swarms.ai
repo_topics: agentic-ai agentic-workflow agents ai artificial-intelligence chatgpt gpt4 gpt4all huggingface langchain langchain-python machine-learning multi-agent-systems prompt-engineering prompt-toolkit prompting swarms tree-of-thoughts
code: from swarms import Agent, HierarchicalSwarm
  
  # Create specialized agents
  research_agent = Agent(
      agent_name="Research-Analyst",
      agent_description="Specialized in comprehensive research and data gathering",
      model_name="gpt-5.4",
      max_loops=1,
      verbose=False,
  )
  
  analysis_agent = Agent(
      agent_name="Data-Analyst",
      agent_description="Expert in data analysis and pattern recognition",
      model_name="gpt-5.4",
      max_loops=1,
      verbose=False,
  )
  
  strategy_agent = Agent(
      agent_name="Strategy-Consultant",
      agent_description="Specialized in strategic planning and recommendations",
      model_name="gpt-5.4",
      max_loops=1,
      verbose=False,
  )
  
  # Create hierarchical swarm with interactive dashboard
  swarm = HierarchicalSwarm(
      name="Swarms Corporation Operations",
      description="Enterprise-grade hierarchical swarm for complex task execution",
      agents=[research_agent, analysis_agent, strategy_agent],
      max_loops=1,
      director_model_name="claude-haiku-4-5",
      director_temperature=1.0,
      director_top_p=None,
      parallel_execution=True,
      agent_as_judge=True,
      judge_agent_model_name="gpt-5.4",
      planning_enabled=False,
  )
  
  
  # print(swarm.display_hierarchy())
  
  out = swarm.run(
      "Conduct a research analysis on water stocks and etfs"
  )
  print(out)
  