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Architecture

TradingAgents v0.2.1 is a multi-agent LLM framework using LangGraph. It has 17 agent factory functions, 3 data vendors (yfinance, Alpha Vantage, Finnhub), and 6 LLM providers (OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama).

3-Tier LLM System

Tier	Config Key	Default Model	Purpose
Quick	`quick_think_llm`	`gpt-5-mini`	Analysts, scanners — fast responses
Mid	`mid_think_llm`	`None` (falls back to quick)	Bull/bear researchers, trader, deep dive
Deep	`deep_think_llm`	`gpt-5.2`	Research manager, risk manager, macro synthesis

Each tier has optional _{tier}_llm_provider and _{tier}_backend_url overrides. All fall back to top-level llm_provider ("openai") and backend_url ("https://api.openai.com/v1").

Source: tradingagents/default_config.py

LLM Provider Factory

Provider	Config Value	Client	Notes
OpenAI	`"openai"`	`ChatOpenAI`	`openai_reasoning_effort` supported
Anthropic	`"anthropic"`	`ChatAnthropic`	—
Google	`"google"`	`ChatGoogleGenerativeAI`	`google_thinking_level` supported
xAI	`"xai"`	`ChatOpenAI` (OpenAI-compat)	`reasoning_effort` supported
OpenRouter	`"openrouter"`	`ChatOpenAI` (OpenAI-compat)	`reasoning_effort` supported
Ollama	`"ollama"`	`ChatOpenAI` (OpenAI-compat)	Uses configured `base_url`, never hardcode localhost

Source: tradingagents/llm_clients/

Data Vendor Routing

Vendor	Role	Capabilities
yfinance	Primary (free)	OHLCV, fundamentals, news, screener, sector/industry, indices
Alpha Vantage	Fallback	OHLCV, fundamentals, news, sector ETF proxies, market movers
Finnhub	Specialized	Insider transactions (primary), earnings calendar, economic calendar

Routing: 2-level dispatch — category-level (data_vendors config) + tool-level (tool_vendors config). Fail-fast by default; only 5 methods in FALLBACK_ALLOWED get cross-vendor fallback (ADR 011).

Source: tradingagents/dataflows/interface.py

Trading Pipeline

START ──┬── Market Analyst (quick) ── tools_market ──┐
        ├── Social Analyst (quick) ── tools_social ──┤
        ├── News Analyst (quick) ── tools_news ───────┼── Bull Researcher (mid) ⇄ Bear Researcher (mid)
        └── Fundamentals Analyst (quick) ── tools_fund─┘         │ (max_debate_rounds)
                                                          Research Manager (deep)
                                                                  │
                                                            Trader (mid)
                                                                  │
                                                  Aggressive ⇄ Neutral ⇄ Conservative (quick)
                                                         (max_risk_discuss_rounds)
                                                                  │
                                                            Risk Judge (deep)

Analysts run in parallel → investment debate → trading plan → risk debate → final decision.

Source: tradingagents/graph/trading_graph.py, tradingagents/graph/setup.py

Scanner Pipeline

START ──┬── Geopolitical Scanner (quick) ──┐
        ├── Market Movers Scanner (quick) ──┼── Industry Deep Dive (mid) ── Macro Synthesis (deep) ── END
        └── Sector Scanner (quick) ─────────┘

Phase 1: 3 scanners run in parallel. Phase 2: Deep dive cross-references all outputs, calls get_industry_performance per sector. Phase 3: Macro synthesis produces top-10 watchlist as JSON.

Source: tradingagents/graph/scanner_graph.py, tradingagents/graph/scanner_setup.py

Pipeline Bridge

Scanner JSON output → MacroBridge.load() → parse into MacroContext + list[StockCandidate] → filter_candidates() by conviction → run_all_tickers() (async, max_concurrent=2) → per-ticker TradingAgentsGraph.propagate() → save_results() (per-ticker .md + summary.md + results.json).

Source: tradingagents/pipeline/macro_bridge.py

CLI Architecture

3 Typer commands: analyze (interactive per-ticker), scan (macro scanner), pipeline (scan → filter → deep dive). Rich-based live UI with MessageBuffer (deque-backed state manager tracking agent status, reports, tool calls, defined in cli/main.py) and StatsCallbackHandler (token/timing stats, defined in cli/stats_handler.py). 7-step interactive questionnaire in analyze for provider/model selection.

Source: cli/main.py, cli/stats_handler.py

Key Source Files

File	Purpose
`tradingagents/default_config.py`	All config keys, defaults, env var override pattern
`tradingagents/graph/trading_graph.py`	`TradingAgentsGraph` class, LLM wiring, tool nodes
`tradingagents/graph/scanner_graph.py`	`ScannerGraph` class, 3-phase workflow
`tradingagents/graph/setup.py`	`GraphSetup` — agent node creation, graph compilation
`tradingagents/graph/scanner_setup.py`	`ScannerGraphSetup` — scanner graph compilation
`tradingagents/dataflows/interface.py`	`route_to_vendor`, `VENDOR_METHODS`, `FALLBACK_ALLOWED`
`tradingagents/agents/utils/tool_runner.py`	`run_tool_loop()`, `MAX_TOOL_ROUNDS=5`, `MIN_REPORT_LENGTH=2000`
`tradingagents/agents/utils/agent_states.py`	`AgentState`, `InvestDebateState`, `RiskDebateState`
`tradingagents/agents/utils/scanner_states.py`	`ScannerState`, `_last_value` reducer
`tradingagents/pipeline/macro_bridge.py`	`MacroBridge`, data classes, pipeline orchestration
`tradingagents/agents/utils/json_utils.py`	`extract_json()` — handles DeepSeek R1 markdown wrapping
`cli/main.py`	CLI commands, `MessageBuffer`, Rich UI, interactive setup
`tradingagents/dataflows/config.py`	`set_config()`, `get_config()`, `initialize_config()`

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