fdf54ae279
* Initial plan * feat: include portfolio holdings in auto mode pipeline analysis In run_auto (both AgentOS and CLI), Phase 2 now loads current portfolio holdings and merges their tickers with scan candidates before running the per-ticker pipeline. This ensures the portfolio manager has fresh analysis for both new opportunities and existing positions. Key changes: - macro_bridge.py: add candidates_from_holdings() factory - langgraph_engine.py run_auto: merge holding tickers with scan tickers - cli/main.py auto: load holdings, create StockCandidates, pass to run_pipeline - cli/main.py run_pipeline: accept optional holdings_candidates parameter - 9 new unit tests covering holdings inclusion, dedup, and graceful fallback Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com> Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/53065a07-d9f8-47be-9956-0eb4ee8c87da * fix: normalize ticker case in dedup and clarify count display Address code review feedback: - Use .upper() for case-insensitive ticker comparison in run_pipeline - Display accurate filtered scan count instead of raw candidate count Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com> Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/53065a07-d9f8-47be-9956-0eb4ee8c87da --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com> |
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| DESIGN.md | ||
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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.