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>
- Add .env.example file with API key placeholders
- Update README.md with .env file setup instructions
- Add dotenv loading in main.py for environment variables
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Co-Authored-By: Claude <noreply@anthropic.com>
Add data vendor configuration examples in README and main.py showing how to configure Alpha Vantage as the primary data provider. Update documentation to reflect the current default behavior of using Alpha Vantage for real-time market data access.
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Co-Authored-By: Claude <noreply@anthropic.com>
- Added support for running CLI and Ollama server via Docker
- Introduced tests for local embeddings model and standalone Docker setup
- Enabled conditional Ollama server launch via LLM_PROVIDER