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TradingAgents
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TradingAgents/agent_os
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copilot-swe-agent[bot] b08ce7199e feat: fix prompt display, add event detail modal, run buttons, and node animations 
Backend:
- Extract full prompt from all LLM messages (not just first)
- Add prompt/response fields to streamed event payloads
- Improve model name extraction with multiple fallback strategies
- Add run_portfolio and run_auto streaming methods
- Wire portfolio/auto in websocket router
- New tool_result event type for tool completion

Frontend:
- Add full event detail modal with tabs (Prompt, Response, Summary, Metrics)
- Show actual prompt content in drawer instead of "Prompting unknown..."
- Add Scan, Pipeline, Portfolio, Auto buttons to control panel
- Fix node animation: completed nodes never revert to running
- Handle tool_result type for marking tool nodes as done
- Drawer events have "Full Detail →" button to open modal

Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/7997c579-ab7e-4071-afd0-18703a8e5618
 		2026-03-23 08:04:53 +00:00
..
backend feat: fix prompt display, add event detail modal, run buttons, and node animations 2026-03-23 08:04:53 +00:00
frontend feat: fix prompt display, add event detail modal, run buttons, and node animations 2026-03-23 08:04:53 +00:00
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.