Major additions:
- ML win probability scanner: scans ticker universe using trained
LightGBM/TabPFN model, surfaces candidates with P(WIN) above threshold
- 30-feature engineering pipeline (20 base + 10 interaction features)
computed from OHLCV data via stockstats + pandas
- Triple-barrier labeling for training data generation
- Dataset builder and training script with calibration analysis
- Discovery enrichment: confluence scoring, short interest extraction,
earnings estimates, options signal normalization, quant pre-score
- Configurable prompt logging (log_prompts_console flag)
- Enhanced ranker investment thesis (4-6 sentence reasoning)
- Typed DiscoveryConfig dataclass for all discovery settings
- Console price charts for visual ticker analysis
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Created nested "filters" section for all filter-stage settings
(min_average_volume, same-day movers, recent movers, etc.)
- Created nested "enrichment" section for batch news settings
- Updated CandidateFilter to read from new nested structure
- Added backward compatibility fallback for old flat config
- Improved config organization and clarity
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Final fix for scanner registration issue. Previous attempts
to add scanner import at module level were removed by the
pre-commit hook's ruff --fix auto-formatter.
Solution:
- Import scanners inside DiscoveryGraph.__init__() method
- Use the import (assign to _) so it's not "unused"
- Linter won't remove imports that are actually used
This ensures scanners always load when DiscoveryGraph is instantiated.
Verified: 8 scanners now properly registered
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
The scanner import needs # noqa: F401 to prevent linters from
removing it as "unused". The import is required for side effects
(triggering scanner registration).
Without this:
- Pre-commit hook removes the import
- Scanners don't register
- Discovery returns 0 candidates
Fix:
- Added # noqa: F401 comment to scanner import
- Linter will now preserve this import
- Verified 8 scanners properly registered
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Critical bugfix: Scanner modules weren't being imported, causing
SCANNER_REGISTRY to remain empty and discovery to return 0 candidates.
Root Cause:
- Import line "from tradingagents.dataflows.discovery import scanners"
was accidentally removed during concurrent execution refactoring
- Without this import, scanner @register() decorators never execute
- Result: SCANNER_REGISTRY.get_all_scanners() returns empty list
Fix:
- Restored scanner import in discovery_graph.py line 6
- Scanners now properly register on module import
- Verified 8 scanners now registered and working
Impact:
- Before: 0 candidates, 0 recommendations
- After: 60-70 candidates, 15 recommendations (normal operation)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Tests verify:
- Single vendor stops after first success
- Multi-vendor stops after all primaries (even if they fail)
- Fallback vendors are not attempted when primaries are configured
- Tool-level config overrides category-level config
Tests use pytest with fixtures and mocked vendors, can run without API keys in CI/CD.
Run with: pytest tests/test_multi_vendor_routing.py -v
When multiple primary vendors are configured (e.g., 'reddit,alpha_vantage'),
the system now correctly stops after attempting all primary vendors instead
of continuing through all fallback vendors.
Changes:
- Track which primary vendors have been attempted in a list
- Add stopping condition when all primary vendors are attempted
- Preserve existing single-vendor behavior (stop after first success)
This prevents unnecessary API calls and ensures predictable behavior.
- 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
🤖 Generated with [Claude Code](https://claude.ai/code)
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.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Replace hardcoded column indices with column name lookup
- Add mapping for all supported indicators to their expected CSV column names
- Handle missing columns gracefully with descriptive error messages
- Strip whitespace from header parsing for reliability
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Replace FinnHub with Alpha Vantage API in README documentation
- Implement comprehensive Alpha Vantage modules:
- Stock data (daily OHLCV with date filtering)
- Technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands, ATR)
- Fundamental data (overview, balance sheet, cashflow, income statement)
- News and sentiment data with insider transactions
- Update news analyst tools to use ticker-based news search
- Integrate Alpha Vantage vendor methods into interface routing
- Maintain backward compatibility with existing vendor system
🤖 Generated with [Claude Code](https://claude.ai/code)
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
Youssef Aitousarrah
Aitous
Edward Sun
Edward Sun
Yijia Xiao
luohy15
mirza-samad-ahmed-baig
Max Wong
Geeta Chauhan
Huijae Lee
Zhongyi Lu
Atharv Sabde