ai-trading-crew

# AI Trading Crew USE FOR: - "50-agent trading crew simulation" - "AutoGen multi-agent stock analysis" - "devil's advocate + risk veto trading system" - "US stock consensus trading agent" - "multi-team agent debate for trading decisions" - "ChromaDB RAG for trading knowledge" tags: [AutoGen, multi-agent, trading, US-stocks, Alpaca, Polygon, ChromaDB, RAG, risk-veto, paper-trading] kind: framework category: quant-ml-trading --- ## What Is AI Trading Crew? 50-agent AutoGen system simulating a collaborative trading firm for US equities. - Repo: https://github.com/omer475/ai-trading-crew - Framework: **AutoGen** (Microsoft multi-agent) - LLM: OpenAI - Broker: Alpaca (paper trading) - Data: Polygon.io real-time market data - Memory: ChromaDB RAG knowledge base --- ## Agent Architecture: 8 Teams + Head Coach ``` Head Coach (Supervisor) ↑ synthesis ┌──────────┬──────────┼──────────┬──────────┐ │ │ │ │ │ Technical Fundamental Macro Sentiment Quant (7 agents) (7 agents) (6 agents) (6 agents) (6 agents) │ │ │ │ │ └──────────┴──────────┼──────────┴──────────┘ │ Risk Management (5 agents) ← VETO POWER │ approved? Execution & Ops (5 agents) Strategy & Special (8 agents) │ Devil's Advocate ← contrarian challenge │ Final Decision + Order ``` --- ## Team Responsibilities | Team | Agents | Specialty | |------|--------|-----------| | Technical Analysis | 7 | Chart patterns, indicators, price action | | Fundamental Analysis | 7 | Earnings, P/E, balance sheet, moat | | Macro & Economics | 6 | Fed policy, rates, sectors, macro | | Sentiment & News | 6 | News NLP, social sentiment, analyst ratings | | Quantitative | 6 | Statistical models, factor analysis, signals | | **Risk Management** | 5 | **VETO authority** over all trades | | Execution & Ops | 5 | Order routing, timing, slippage management | | Strategy & Special | 8 | Special situations, M&A, catalysts | --- ## Trading Workflow ``` 1. Input: python main.py --symbol AAPL 2. Teams debate internally via AutoGen GroupChat → Each team reaches internal consensus 3. Team leaders report to Head Coach → Cross-team synthesis 4. Risk Management review → Can VETO any trade (overrides Head Coach) 5. Devil's Advocate challenges recommendation → Forces bull/bear stress test 6. Head Coach final decision 7. Human approval gate (configurable) 8. Execution team submits order to Alpaca ``` --- ## Installation ```bash git clone https://github.com/omer475/ai-trading-crew cd agents pip install -r requirements.txt cp .env.example .env ``` **`.env` keys required:** ```bash OPENAI_API_KEY="sk-..." ALPACA_API_KEY="..." ALPACA_SECRET_KEY="..." POLYGON_API_KEY="..." ``` --- ## Usage ```bash # Full 50-agent analysis python main.py --symbol AAPL # Quick 5-agent test mode python main.py --symbol NVDA --test # Output: consensus decision + rationale + risk assessment + order ``` --- ## Key Design Patterns ### AutoGen GroupChat per Team ```python # Each team runs internal debate groupchat = autogen.GroupChat( agents=[tech_agent_1, tech_agent_2, ..., tech_agent_7], messages=[], max_round=5 ) manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config) ``` ### Risk Veto Pattern ```python class RiskManager(autogen.AssistantAgent): def check_veto(self, proposal: dict) -> bool: if proposal["position_size"] > self.max_risk: return True # VETO if proposal["volatility"] > self.vol_threshold: return True # VETO return False # Approved ``` ### ChromaDB RAG Knowledge Base ```python import chromadb client = chromadb.Client() collection = client.get_or_create_collection("trading_knowledge") # Query before analysis results = collection.query( query_texts=["AAPL earnings history semiconductor cycle"], n_results=5 ) ``` --- ## Unique Features vs Other Trading Agent Frameworks | Feature | AI Trading Crew | TradingAgents | AutoHedge | |---------|----------------|---------------|-----------| | Agent count | **50 agents** | ~8 agents | ~4 agents | | Veto mechanism | Risk team veto | Risk approval | Risk gate | | Contrarian agent | Devil's Advocate | Bearish researcher | No | | Framework | AutoGen | LangGraph | Swarms | | Knowledge base | ChromaDB RAG | None | None | | Markets | US stocks only | US stocks | Solana crypto | ---