97a0d0de53
Feature 1 - Configurable max_auto_tickers:
- Add max_auto_tickers config key (default 10) with TRADINGAGENTS_MAX_AUTO_TICKERS env override
- Macro synthesis agent accepts max_scan_tickers param, injects exact count into LLM prompt
- ScannerGraph passes config value to create_macro_synthesis()
- Backend engine applies safety cap on scan candidates (portfolio holdings always included)
- Frontend adds Max Tickers number input in params panel, sends max_tickers in auto run body
Feature 2 - Run persistence + phase-level node re-run:
- 2A: ReportStore + MongoReportStore gain save/load_run_meta, save/load_run_events,
list_run_metas methods; runs.py persists to disk in finally block; startup hydration
restores historical runs; lazy event loading on GET /{run_id}
- 2B: Analysts + trader checkpoint save/load methods in both stores; engine saves
checkpoints after pipeline completion alongside complete_report.json
- 2C: GraphSetup gains build_debate_subgraph() and build_risk_subgraph() for partial
re-runs; TradingAgentsGraph exposes debate_graph/risk_graph as lazy properties;
NODE_TO_PHASE mapping + run_pipeline_from_phase() engine method;
POST /api/run/rerun-node endpoint with _append_and_store helper
- 2D: Frontend history popover (loads GET /api/run/, sorts by created_at, click to load);
triggerNodeRerun() calls rerun-node endpoint; handleNodeRerun uses phase-level
re-run when active run is loaded
All 890 existing tests pass (10 skipped).
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
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| DESIGN.md | ||
| README.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.