# TradingAgents Framework - Project Knowledge ## Project Overview Multi-agent LLM trading framework using LangGraph for financial analysis and decision making. ## Development Environment **Conda Environment**: `tradingagents` Before starting any development work, activate the conda environment: ```bash conda activate tradingagents ``` ## Architecture - **Agent Factory Pattern**: `create_X(llm)` → closure pattern - **3-Tier LLM System**: - Quick thinking (fast responses) - Mid thinking (balanced analysis) - Deep thinking (complex reasoning) - **Data Vendor Routing**: yfinance (primary), Alpha Vantage (fallback) - **Graph-Based Workflows**: LangGraph for agent coordination ## Key Directories - `tradingagents/agents/` - Agent implementations - `tradingagents/graph/` - Workflow graphs and setup - `tradingagents/dataflows/` - Data access layer - `cli/` - Command-line interface ## Agent Flow (Existing Trading Analysis) 1. Analysts (parallel): Fundamentals, Market, News, Social Media 2. Bull/Bear Debate 3. Research Manager 4. Trader 5. Risk Debate 6. Risk Judge ## Scanner Flow (New Market-Wide Analysis) ``` START ──┬── Geopolitical Scanner (quick_think) ──┐ ├── Market Movers Scanner (quick_think) ──┼── Industry Deep Dive (mid_think) ── Macro Synthesis (deep_think) ── END └── Sector Scanner (quick_think) ─────────┘ ``` - Phase 1: Parallel execution of 3 scanners - Phase 2: Industry Deep Dive cross-references all outputs - Phase 3: Macro Synthesis produces top-10 watchlist ## Data Vendors - **yfinance** (primary, free): Screener(), Sector(), Industry(), index tickers - **Alpha Vantage** (alternative, API key required): TOP_GAINERS_LOSERS endpoint only (fallback for market movers) ## LLM Providers OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama ## CLI Entry Point `cli/main.py` with Typer: - `analyze` (per-ticker analysis) - `scan` (new, market-wide scan) ## Configuration `tradingagents/default_config.py`: - LLM tiers configuration - Vendor routing - Debate rounds settings - All values overridable via `TRADINGAGENTS_` env vars (see `.env.example`) ## Patterns to Follow - Agent creation (trading): `tradingagents/agents/analysts/news_analyst.py` - Agent creation (scanner): `tradingagents/agents/scanners/geopolitical_scanner.py` - Tools: `tradingagents/agents/utils/news_data_tools.py` - Scanner tools: `tradingagents/agents/utils/scanner_tools.py` - Graph setup (trading): `tradingagents/graph/setup.py` - Graph setup (scanner): `tradingagents/graph/scanner_setup.py` - Inline tool loop: `tradingagents/agents/utils/tool_runner.py` ## Critical Patterns (see `docs/agent/decisions/008-lessons-learned.md` for full details) - **Tool execution**: Trading graph uses `ToolNode` in graph. Scanner agents use `run_tool_loop()` inline. If `bind_tools()` is used, there MUST be a tool execution path. - **yfinance DataFrames**: `top_companies` has ticker as INDEX, not column. Always check `.index` and `.columns`. - **yfinance Sector/Industry**: `Sector.overview` has NO performance data. Use ETF proxies for performance. - **Vendor fallback**: Functions inside `route_to_vendor` must RAISE on failure, not embed errors in return values. Catch `(AlphaVantageError, ConnectionError, TimeoutError)`, not just `RateLimitError`. - **LangGraph parallel writes**: Any state field written by parallel nodes MUST have a reducer (`Annotated[str, reducer_fn]`). - **Ollama remote host**: Never hardcode `localhost:11434`. Use configured `base_url`. - **.env loading**: `load_dotenv()` runs at module level in `default_config.py` — import-order-independent. Check actual env var values when debugging auth. - **Rate limiter locks**: Never hold a lock during `sleep()` or IO. Release, sleep, re-acquire. - **Config fallback keys**: `llm_provider` and `backend_url` must always exist at top level — `scanner_graph.py` and `trading_graph.py` use them as fallbacks. ## Agentic Memory (docs/agent/) Agent workflows use the `docs/agent/` scaffold for structured memory: - `docs/agent/CURRENT_STATE.md` — Live state tracker (milestone, progress, blockers). Read at session start. - `docs/agent/decisions/` — Architecture decision records (ADR-style, numbered `001-...`) - `docs/agent/plans/` — Implementation plans with checkbox progress tracking - `docs/agent/logs/` — Agent run logs - `docs/agent/templates/` — Commit, PR, and decision templates Before starting work, always read `docs/agent/CURRENT_STATE.md`. Before committing, update it. ## LLM Configuration Per-tier provider overrides in `tradingagents/default_config.py`: - Each tier (`quick_think`, `mid_think`, `deep_think`) can have its own `_llm_provider` and `_backend_url` - Falls back to top-level `llm_provider` and `backend_url` when per-tier values are None - All config values overridable via `TRADINGAGENTS_` env vars - Keys for LLM providers: `.env` file (e.g., `OPENROUTER_API_KEY`, `ALPHA_VANTAGE_API_KEY`) ### Env Var Override Convention ```env # Pattern: TRADINGAGENTS_=value TRADINGAGENTS_LLM_PROVIDER=openrouter TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-r1-0528 TRADINGAGENTS_MAX_DEBATE_ROUNDS=3 TRADINGAGENTS_VENDOR_SCANNER_DATA=alpha_vantage ``` Empty or unset vars preserve the hardcoded default. `None`-default fields (like `mid_think_llm`) stay `None` when unset, preserving fallback semantics. ## Running the Scanner ```bash conda activate tradingagents python -m cli.main scan --date 2026-03-17 ``` ## Running Tests ```bash conda activate tradingagents pytest tests/ -v ```