bf25282518
This major update adds four powerful features to TradingAgents: 1. Multi-LLM Provider Support - LLMFactory for OpenAI, Anthropic Claude, and Google Gemini - Easy provider switching via configuration - Recommended models for each provider - Updated TradingAgentsGraph to use factory pattern 2. Paper Trading Integration - BaseBroker abstract interface for consistency - AlpacaBroker implementation with free paper trading - Support for market, limit, stop, and stop-limit orders - Real-time position tracking and P&L calculation - Example scripts for basic and integrated trading 3. Web Interface - Beautiful Chainlit-based GUI - Chat interface for stock analysis - Interactive trading commands - Portfolio management - Settings configuration - Real-time updates 4. Docker Support - Production-ready Dockerfile - Docker Compose for multi-service setup - Persistent data volumes - Optional Jupyter notebook service - Comprehensive deployment documentation Additional improvements: - Enhanced .env.example with all provider configurations - Comprehensive documentation (NEW_FEATURES.md, DOCKER.md) - Broker integration guide - Example scripts for all features - Verification script to test new features - Made example scripts executable Files changed: - New: tradingagents/llm_factory.py (400+ lines) - New: tradingagents/brokers/ (base.py, alpaca_broker.py, __init__.py) - New: web_app.py (Chainlit web interface) - New: Dockerfile, docker-compose.yml, .dockerignore - New: examples/use_claude.py, paper_trading_alpaca.py, tradingagents_with_alpaca.py - New: NEW_FEATURES.md, DOCKER.md, tradingagents/brokers/README.md - New: verify_new_features.py - Modified: tradingagents/graph/trading_graph.py (use LLMFactory) - Modified: .env.example (added all providers) All features verified and tested. |
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| .. | ||
| __init__.py | ||
| conditional_logic.py | ||
| propagation.py | ||
| reflection.py | ||
| setup.py | ||
| signal_processing.py | ||
| trading_graph.py | ||