- Add tradingagents/config.py with TradingAgentsSettings Pydantic model
- Centralize all environment variable handling and API key management
- Add validation for log_level, llm_provider, and numeric bounds
- Update dataflows/config.py to use central config as backend
- Update logging.py to get settings from central config
- Update API key access in alpha_vantage, brave, and tavily modules
- Replace DEFAULT_CONFIG imports with get_config() calls
- Add 20 comprehensive tests for config module
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Co-Authored-By: Claude <noreply@anthropic.com>
- Create tradingagents/validation.py with comprehensive validation functions:
- validate_ticker/validate_tickers for ticker symbol validation
- validate_date/validate_date_range for date validation
- parse_date for flexible date parsing (multiple formats)
- Helper functions: is_valid_ticker, is_valid_date, is_trading_day
- get_previous_trading_day, get_next_trading_day utilities
- Add validation to y_finance.py (get_YFin_data_online, get_stock_stats_indicators_window)
- Add validation to trading_graph.py propagate method
- Create comprehensive test suite (55 tests) in tests/test_validation.py
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add complete backtesting engine with portfolio simulation, metrics calculation
(Sharpe, Sortino, max drawdown), and agent integration
- Add Pydantic data models for market data, trading, portfolio, and backtest results
- Add backtest CLI command with SMA, RSI, and hold strategies
- Fix 24+ bare exception handlers with specific exception types
- Fix hardcoded path in default_config.py (use TRADINGAGENTS_DATA_DIR env var)
- Fix unclosed file handle in local.py with context manager
- Disable store=True in OpenAI API calls for data privacy
- Fix typo: rename aggresive_debator.py to aggressive_debator.py
- Add request timeouts (30s) to alpha_vantage_common.py and googlenews_utils.py
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add MultiStageLoader and LoadingIndicator classes to cli/utils.py
- Improve CLI main.py with explicit imports and UI enhancements
- Update entity_extractor.py with improved LLM provider handling
- Add Ollama embedding model configuration to memory.py
- Add get_bulk_news_alpha_vantage function to alpha_vantage_news.py
- Add discovery imports to trading_graph.py
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Co-Authored-By: Claude <noreply@anthropic.com>
Implement a multi-stage pipeline to discover trending stocks from news:
- Entity extraction from news articles using LLM
- Stock ticker resolution via Yahoo Finance
- Sector classification and event categorization
- Scoring algorithm based on mentions, sentiment, and recency
- CLI integration with interactive stock selection and analysis flow
- Persistence layer for saving discovery results
- Comprehensive test suite for all discovery components
Update README with uv-based installation instructions and remove emojis.
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Co-Authored-By: Claude <noreply@anthropic.com>
Joseph O'Brien
luohy15
mirza-samad-ahmed-baig
Edward Sun
maxer137
Yijia-Xiao