theheavenlyd3mon TradingAgents — Multi-Agent Financial Analysis Engine
Location: ~/tools/TradingAgents
Python env: uv managed (no conda needed)
Config: ~/tools/TradingAgents/.env
What It Does
Runs a full trading firm simulation with specialized LLM agents:
Analyst Team:
Fundamentals Analyst → company financials, intrinsic value
Sentiment Analyst → news, StockTwits, Reddit sentiment
News Analyst → macroeconomic news and events
Technical Analyst → MACD, RSI, pattern detection
Researcher Team:
Bullish Researcher → makes the bull case
Bearish Researcher → makes the bear case
(configurable debate rounds)
Decision:
Trader Agent → synthesizes all reports → trade decision
Risk Management → portfolio risk, volatility, liquidity
Portfolio Manager → final approval/rejection + reflection
Usage
Python API (preferred for Hermes integration)
cd ~/tools/TradingAgents
# Single analysis
uv run python -c "
from tradingagents.graph.trading_graph import TradingAgentsGraph
from tradingagents.default_config import DEFAULT_CONFIG
config = DEFAULT_CONFIG.copy()
ta = TradingAgentsGraph(debug=True, config=config)
_, decision = ta.propagate('NVDA', '2026-05-21')
print(decision)
"
CLI (interactive)
cd ~/tools/TradingAgents
uv run tradingagents
CLI (non-interactive, via Python)
cd ~/tools/TradingAgents
uv run python -c "
from tradingagents.graph.trading_graph import TradingAgentsGraph
from tradingagents.default_config import DEFAULT_CONFIG
import json
config = DEFAULT_CONFIG.copy()
config['llm_provider'] = 'deepseek'
config['deep_think_llm'] = 'deepseek-v3.2'
config['quick_think_llm'] = 'deepseek-v3.2'
config['max_debate_rounds'] = 1
ta = TradingAgentsGraph(debug=False, config=config)
_, decision = ta.propagate('TICKER', 'YYYY-MM-DD')
print(json.dumps(decision, indent=2))
"
Configuration (via .env)
Set in ~/tools/TradingAgents/.env:
DEEPSEEK_API_KEY=... # Required
ALPHA_VANTAGE_API_KEY=... # Required for market data
TRADINGAGENTS_LLM_PROVIDER=deepseek # Provider
TRADINGAGENTS_DEEP_THINK_LLM=deepseek-v3.2 # Complex reasoning
TRADINGAGENTS_QUICK_THINK_LLM=deepseek-v3.2 # Quick tasks
TRADINGAGENTS_MAX_DEBATE_ROUNDS=1 # Bull vs bear debate rounds
TRADINGAGENTS_OUTPUT_LANGUAGE=English
Decision Memory
Always-on. Logs to ~/.tradingagents/memory/trading_memory.md.
On re-runs for same ticker, fetches realized returns and injects past lessons into Portfolio Manager prompt.
Override path: TRADINGAGENTS_MEMORY_LOG_PATH
Checkpoint Resume
Opt-in via code:
config['checkpoint_enabled'] = True
Checkpoints at ~/.tradingagents/cache/checkpoints/<TICKER>.db
Cost Estimate
Per full analysis run (7+ LLM calls):
- DeepSeek v3.2: ~$0.01-0.03
- OpenAI GPT-4: ~$0.10-0.30
Pitfalls
- Requires Alpha Vantage API key (free tier: 25 req/day)
- Each analysis = 7+ LLM calls — don't run on every ticker every minute
- Decision memory accumulates — periodically review/clean
~/.tradingagents/memory/ - Date must be in YYYY-MM-DD format
- Ticker symbols use Yahoo Finance format (e.g., NVDA, BTC-USD, ^GSPC)
- v0.2.5 (May 2026) — check for updates periodically