curl -s -X POST http://localhost:8080/api/v1/tasks/stream \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Analyze the competitive landscape of cloud AI platforms: AWS, Azure, and GCP",
    "context": { "force_swarm": true }
  }' | jq

{
  "workflow_id": "task-def456...",
  "task_id": "task-def456...",
  "stream_url": "/api/v1/stream/sse?workflow_id=task-def456..."
}

curl -N "http://localhost:8080/api/v1/stream/sse?workflow_id=task-def456..."

from shannon import ShannonClient

client = ShannonClient(base_url="http://localhost:8080")

# 提交 Swarm 任务
handle = client.submit_task(
    "Compare AI chip markets across US, Japan, and South Korea",
    force_swarm=True,
    session_id="swarm-demo-001",
)

# 等待完成并获取结果
result = client.wait(handle.task_id)
print(result.result)
client.close()

from shannon import ShannonClient

client = ShannonClient(base_url="http://localhost:8080")

# 一步提交并获取流式传输 URL
handle, stream_url = client.submit_and_stream(
    "Analyze the competitive landscape of cloud AI platforms",
    force_swarm=True,
)

# 实时流式传输事件
for event in client.stream(handle.workflow_id):
    if event.type == "AGENT_STARTED":
        print(f"智能体已启动: {event.agent_id}")
    elif event.type == "LEAD_DECISION":
        print(f"Lead 决策: {event.message}")
    elif event.type == "PROGRESS":
        print(f"进度: {event.message}")
    elif event.type == "AGENT_COMPLETED":
        print(f"智能体已完成: {event.agent_id}")
    elif event.type == "WORKFLOW_COMPLETED":
        print("Swarm 工作流已完成")
        break

# 获取最终结果
result = client.get_status(handle.task_id)
print(result.result)
client.close()

handle = client.submit_task(
    "Research renewable energy policies in the EU, US, and China",
    force_swarm=True,
    context={
        "model_tier": "medium",  # 智能体使用中等级别模型
    },
)

## Your Team (shared session workspace)
- **takao (you)**: "Research US AI chip market"
- mitaka: "Research Japan AI chip market"
- kichijoji: "Research South Korea AI chip market"

## Shared Findings
- takao: NVIDIA dominates US with 80% market share...
- mitaka: Japan focuses on edge AI chips with Preferred Networks leading...

## Inbox Messages
- From mitaka (info): {"message": "Check Samsung's foundry plans for AI chips"}

{"action": "request_help", "help_description": "Need help analyzing EU regulatory impact on AI chips", "help_skills": ["web_search"]}

workflows:
  swarm:
    enabled: true
    max_agents: 10                    # 最大智能体总数（初始 + 动态）
    max_iterations_per_agent: 25      # 每个智能体的最大推理-行动循环次数
    agent_timeout_seconds: 1800       # 每个智能体超时（30 分钟）
    max_messages_per_agent: 20        # 每个智能体的 P2P 消息上限
    workspace_snippet_chars: 800      # 提示中每个工作区条目的最大字符数
    workspace_max_entries: 5          # 向每个智能体显示的最近条目数
    max_total_llm_calls: 200          # 全局 LLM 调用预算
    max_total_tokens: 1000000         # 全局 Token 预算 (1M)
    max_wall_clock_minutes: 30        # 最大挂钟时间

curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Review the Python files in /workspace/src for security vulnerabilities, code quality issues, and missing test coverage. Write fixes and add tests.",
    "context": { "force_swarm": true }
  }'

curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Compare pricing and features of AWS, Azure, and GCP for a startup needing GPU instances, object storage, and managed Kubernetes",
    "context": {
      "force_swarm": true,
      "model_tier": "medium"
    }
  }'

{
  "metadata": {
    "workflow_type": "swarm",
    "total_agents": 3,
    "total_tokens": 598235,
    "model_breakdown": [
      {
        "model": "claude-haiku-4-5-20251001",
        "provider": "anthropic",
        "executions": 38,
        "tokens": 297524,
        "cost_usd": 0.372
      },
      {
        "model": "shannon_web_search",
        "provider": "shannon-scraper",
        "executions": 12,
        "tokens": 90000,
        "cost_usd": 0.048
      }
    ]
  },
  "usage": {
    "input_tokens": 289164,
    "output_tokens": 309071,
    "total_tokens": 598235,
    "estimated_cost": 0.780
  }
}