curl -fsSL https://raw.githubusercontent.com/Kocoro-lab/Shannon/v0.3.1/scripts/install.sh | bash

cd ~/shannon     # 或你的安装目录
nano .env        # 编辑 API Key
docker compose -f docker-compose.release.yml down
docker compose -f docker-compose.release.yml up -d

# 检查所有服务状态
docker compose -f deploy/compose/docker-compose.release.yml ps

# Gateway 健康检查
curl http://localhost:8080/health

# Admin 健康检查
curl http://localhost:8081/health

pip install shannon-sdk

# 在后端运行后，新开终端
cd desktop
npm install
npm run dev

# 浏览器打开 http://localhost:3000

curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Compare renewable energy adoption in EU vs US",
    "context": {
      "force_research": true,
      "research_strategy": "deep"
    }
  }'
# 编排多个研究智能体，综合发现和引用

curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Analyze this dataset from multiple perspectives",
    "context": {
      "force_swarm": true
    }
  }'

curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Update the production database schema",
    "context": {
      "require_approval": true
    }
  }'
# 工作流暂停，等待明确的人工审批后继续

curl -X POST http://localhost:8080/api/v1/schedules \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Daily Market Analysis",
    "cron_expression": "0 9 * * *",
    "task_query": "Analyze market trends",
    "max_budget_per_run_usd": 0.50
  }'

export OPENAI_API_BASE=http://localhost:8080/v1
# 你的现有 OpenAI 代码保持不变

# 监控智能体执行（SSE）
curl -N "http://localhost:8080/api/v1/stream/sse?workflow_id=task-dev-123"

# 事件类型：
# - WORKFLOW_STARTED, WORKFLOW_COMPLETED
# - AGENT_STARTED, AGENT_COMPLETED
# - TOOL_INVOKED, TOOL_OBSERVATION
# - LLM_PARTIAL, LLM_OUTPUT

curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Run this Python script and save the output",
    "session_id": "my-workspace"
  }'

# 第一轮
curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{"query": "What is GDP?", "session_id": "econ-101"}'

# 后续记得上下文
curl -X POST http://localhost:8080/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{"query": "How does it relate to inflation?", "session_id": "econ-101"}'
# 智能体回忆同一会话的近期对话历史

# config/mcp.yaml
mcp_servers:
  - name: "filesystem"
    command: "npx"
    args: ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
    enabled: true

./scripts/submit_task.sh "Execute Python: import os; os.system('rm -rf /')"
# 结果：OSError - 系统调用被 WASI 沙箱阻止

# 选择提供商
WEB_SEARCH_PROVIDER=serpapi             # serpapi | searchapi | google | bing | exa
SERPAPI_API_KEY=your-serpapi-key        # serpapi.com

# 用于深度研究
WEB_FETCH_PROVIDER=firecrawl            # firecrawl | exa | python
FIRECRAWL_API_KEY=your-firecrawl-key   # firecrawl.dev（生产推荐）

# 重放失败的工作流
./scripts/replay_workflow.sh task-prod-failure-123

# 输出显示每个决策、工具调用和状态变化

# 检查 .env 是否有所需 API Key
cat .env | grep API_KEY

# 确保端口未被占用
netstat -an | grep -E '8080|8081|50052'

# 重启服务
docker compose -f deploy/compose/docker-compose.release.yml down
docker compose -f deploy/compose/docker-compose.release.yml up -d

# 验证 API Key 有效
echo $OPENAI_API_KEY

# 检查 orchestrator 日志
docker compose -f deploy/compose/docker-compose.release.yml logs -f orchestrator

# 确保配置文件存在于 ./config/ 目录
ls -la config/

# 降低 WASI 内存限制（默认：512MB）
WASI_MEMORY_LIMIT_MB=256

# 降低历史窗口（默认：50条消息）
HISTORY_WINDOW_MESSAGES=20

# 检查 Docker 内存限制
docker stats

# 所有服务
docker compose -f deploy/compose/docker-compose.release.yml logs -f

# 指定服务
docker compose -f deploy/compose/docker-compose.release.yml logs -f orchestrator
docker compose -f deploy/compose/docker-compose.release.yml logs -f gateway
docker compose -f deploy/compose/docker-compose.release.yml logs -f llm-service