1. executor.shutdown(wait=True) still blocked after global timeout (critical)
The previous fix added timeout= to as_completed() but used `with
ThreadPoolExecutor() as executor`, whose __exit__ calls shutdown(wait=True).
This meant the process still hung waiting for stuck threads (ml_signal) even
after the TimeoutError was caught. Fixed by creating the executor explicitly
and calling shutdown(wait=False) in a finally block.
2. ml_signal hangs on every run — "Batch-downloading 592 tickers (1y)..." never
completes. Root cause: a single yfinance request for 592 tickers × 1 year of
daily OHLCV is a very large payload that regularly times out at the network
layer. Fixed by:
- Reducing default lookback from "1y" to "6mo" (halves download size)
- Splitting downloads into 150-ticker chunks so a slow chunk doesn't kill
the whole scan (partial results are still returned)
3. C (Citigroup) and other single-letter NYSE tickers rejected as invalid.
validate_ticker_format used ^[A-Z]{2,5}$ requiring at least 2 letters.
Real tickers like C, A, F, T, X, M are 1 letter. Fixed to ^[A-Z]{1,5}$.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Two issues caused the agent to get stuck after the last log message
from a completed scanner (e.g. "✓ reddit_trending: 11 candidates"):
1. `as_completed()` had no global timeout. If a scanner thread blocked
in a non-interruptible I/O call, `as_completed()` waited forever
because it only yields a future once it has finished — the per-future
`future.result(timeout=N)` call was never even reached.
Fixed by passing `timeout=global_timeout` to `as_completed()` so
the outer iterator raises TimeoutError after a capped wall-clock
budget, then logs which scanners didn't complete and continues.
2. `SectorRotationScanner` called `get_ticker_info()` (one HTTP request
per ticker) in a serial loop for up to 100 tickers from a 592-ticker
file, easily exceeding the 30 s per-scanner budget.
Fixed by batch-downloading close prices for all tickers in a single
`download_history()` call, computing 5-day returns locally, and only
calling `get_ticker_info()` for the small subset of laggard tickers
(<2% 5d move) that actually need a sector label.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Two bugs were causing the signal card HTML to display as literal text:
1. CommonMark HTML block termination: Streamlit's markdown parser
(CommonMark-compliant) terminates a <div> block at the first blank
line. Empty optional fields (name_html, desc_html, risk_badge_html)
left whitespace-only lines in the f-string template, ending the HTML
block and causing the parser to render subsequent tags as text.
Fixed by building HTML from a parts list and only appending optional
elements when non-empty — no blank lines can appear in output.
2. Unescaped HTML chars in LLM-generated text: reason fields from the
ranker contained raw > and & characters (e.g. '>5% move',
'50 & 200 SMA') that corrupted the HTML structure. Fixed by running
all LLM-generated fields through html.escape() before interpolation.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Call get_finviz_insider_buying with return_structured=True and deduplicate=False
to get all raw transaction dicts instead of parsing markdown
- Group transactions by ticker for cluster detection (2+ unique insiders = CRITICAL)
- Smart priority: CEO/CFO + >$100K = CRITICAL, director + >$50K = HIGH, etc.
- Preserve insider_name, insider_title, transaction_value, num_insiders_buying in output
- Rich context strings: "CEO John Smith purchased $250K of AAPL shares"
- Update finviz_scraper alias to pass through return_structured and deduplicate params
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add daily price movement display with color coding (green/red)
- Add 1D (intraday) and 7D chart options with granular data:
- 1D: 5-minute interval for detailed intraday view
- 7D: hourly interval for smooth 7-day chart
- Fix discontinuous chart rendering by plotting against sequential index for intraday data
- Eliminate overnight/weekend gaps in hourly charts
- Add timezone normalization for consistent date handling between daily and intraday data
- Improve fallback logic when data is sparse
- Better handling of yfinance column names (Datetime vs Date)
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
- Add GitHub Actions workflow for daily discovery (8:30 AM ET, weekdays)
- Add headless run_daily_discovery.py script for scheduling
- Expand options_flow scanner to use tickers.txt with parallel execution
- Add recommendation history section to Performance page with filters and charts
- Fix strategy name normalization (momentum/Momentum/Momentum-Hype → momentum)
- Fix strategy metrics to count all recs, not just evaluated ones
- Add error handling to Streamlit page rendering
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add ML signal scanner results table logging
- Add log_prompts_console config flag for prompt visibility control
- Expand ranker investment thesis to 4-6 sentence structured reasoning
- Linter auto-formatting across modified files
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
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.
- 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
Edward Sun
luohy15
mirza-samad-ahmed-baig
Yijia Xiao
Max Wong
Geeta Chauhan
Huijae Lee
Atharv Sabde