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Ahmet Guzererler 860968835c feat: add Reset Decision button to clear portfolio stage and re-run 
- ReportStore.clear_portfolio_stage(date, portfolio_id): deletes pm_decision
  (.json + .md) and execution_result files for a given date/portfolio
- DELETE /api/run/portfolio-stage endpoint: calls clear_portfolio_stage
  and returns list of deleted files
- Dashboard: 'Reset Decision' button calls the endpoint, then user can
  run Auto to re-run Phase 3 from scratch while skipping Phase 1 & 2

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 		2026-03-24 00:34:53 +01:00
..
backend feat: add Reset Decision button to clear portfolio stage and re-run 2026-03-24 00:34:53 +01:00
frontend feat: add Reset Decision button to clear portfolio stage and re-run 2026-03-24 00:34:53 +01:00
DESIGN.md docs: finalize AgentOS documentation 2026-03-22 22:54:20 +01:00
README.md docs: finalize AgentOS documentation 2026-03-22 22:54:20 +01:00
__init__.py fix: add missing __init__.py files to agent_os package tree 2026-03-23 07:16:38 +00:00

README.md

AgentOS: Visual Observability & Command Center

AgentOS is a real-time observability and command center for the TradingAgents framework. It provides a visual interface to monitor multi-agent workflows, analyze portfolio risk metrics, and trigger automated trading pipelines.

System Architecture

  • Backend: FastAPI (Python)
    • Orchestrates LangGraph executions.
    • Streams real-time events via WebSockets.
    • Serves portfolio data from Supabase.
    • Port: 8088 (default)
  • Frontend: React (TypeScript) + Vite
    • Visualizes agent workflows using React Flow.
    • Displays high-fidelity risk metrics (Sharpe, Regime, Drawdown).
    • Provides a live terminal for deep tracing.
    • Port: 5173 (default)

Getting Started

1. Prerequisites

  • Python 3.10+
  • Node.js 18+
  • uv (recommended for Python environment management)

2. Backend Setup

# From the project root
export PYTHONPATH=$PYTHONPATH:.
uv run python agent_os/backend/main.py

The backend will start on http://127.0.0.1:8088.

3. Frontend Setup

cd agent_os/frontend
npm install
npm run dev

The frontend will start on http://localhost:5173.

Key Features

  • Literal Graph Visualization: Real-time DAG rendering of agent interactions.
  • Top 3 Metrics: High-level summary of Sharpe Ratio, Market Regime, and Risk/Drawdown.
  • Live Terminal: Color-coded logs with token usage and latency metrics.
  • Run Controls: Trigger Market Scans, Analysis Pipelines, and Portfolio Rebalancing directly from the UI.

Port Configuration

AgentOS uses port 8088 for the backend to avoid conflicts with common macOS services. The frontend is configured to communicate with 127.0.0.1:8088.