AI Hedge Fund

flowchart TD
  subgraph CLI["Command Line Interface"]
    main_py["main.py"]
    cli_input["cli/input.py"]
    main_py --> cli_input
  end

  subgraph Agents["AI Agent Pipeline"]
    start_node["start_node"]
    investor_agents["19 Investor Agents\n(fan-out parallel)"]
    risk_manager["risk_manager"]
    portfolio_manager["portfolio_manager"]
    start_node --> investor_agents
    investor_agents --> risk_manager
    risk_manager --> portfolio_manager
  end

  subgraph Core["Core Infrastructure"]
    graph_state["graph/state"]
    llm_models["llm/models"]
    tools_api["tools/api"]
    data_cache["data/cache"]
  end

  subgraph Backend["FastAPI Backend"]
    routes["routes"]
    services["services"]
    database["database"]
    routes --> services
    services --> database
  end

  subgraph Frontend["React Frontend"]
    react_flow["ReactFlow Editor"]
    hooks["hooks"]
    fe_services["services"]
    react_flow --> hooks
    hooks --> fe_services
  end

  subgraph V2["v2 Pipeline"]
    signals["signals"]
    portfolio_opt["portfolio optimizer"]
    v2_risk["risk"]
    v2_exec["execution"]
    signals --> portfolio_opt
    portfolio_opt --> v2_risk
    v2_risk --> v2_exec
  end

  CLI --> Agents
  Agents --> Core
  Backend --> Agents
  Frontend --> Backend
  V2 --> Core

sequenceDiagram
    participant User
    participant CLI
    participant StateGraph
    participant Agents
    participant RiskMgr as Risk Manager
    participant PortfolioMgr as Portfolio Manager

    User->>CLI: ticker + date range
    CLI->>StateGraph: create workflow
    StateGraph->>Agents: fan-out to all analysts (parallel)
    Note over Agents: Each agent calls Financial API + LLM
    Agents->>RiskMgr: aggregate signals
    RiskMgr->>PortfolioMgr: risk-adjusted signals
    PortfolioMgr->>User: trading decisions (JSON)

sequenceDiagram
    participant Browser
    participant FastAPI
    participant GraphService
    participant Agents
    participant ReactFlow

    Browser->>FastAPI: POST /hedge-fund/run
    FastAPI->>GraphService: build LangGraph from React Flow
    GraphService->>Agents: execute pipeline
    Note over Agents: SSE events streamed back
    Agents-->>FastAPI: progress events
    FastAPI-->>Browser: SSE stream (Start/Progress/Complete)
    Browser->>ReactFlow: update node statuses

flowchart LR
  subgraph EntryPoints["Entry Points"]
    cli["CLI (main.py)"]
    webapp["WebApp (FastAPI + React)"]
  end

  subgraph SharedCore["Shared Core"]
    pipeline["Agent Pipeline\n(19 analysts + managers)"]
    infra["Core Infrastructure\n(graph, LLM, data, tools)"]
    pipeline --> infra
  end

  cli --> pipeline
  webapp --> pipeline