* Initial plan
* Improve Industry Deep Dive quality: enrich tool data, explicit sector keys, tool-call nudge
- Enrich get_industry_performance_yfinance with 1-day/1-week/1-month price returns
via batched yf.download() for top 10 tickers (Step 1)
- Add VALID_SECTOR_KEYS, _DISPLAY_TO_KEY, _extract_top_sectors() to industry_deep_dive.py
to pre-extract top sectors from Phase 1 report and inject them into the prompt (Step 2)
- Add tool-call nudge to run_tool_loop: if first LLM response has no tool calls and is
under 500 chars, re-prompt with explicit instruction to call tools (Step 3)
- Update scanner_tools.py get_industry_performance docstring to list all valid sector keys (Step 4)
- Add 15 unit tests covering _extract_top_sectors, tool_runner nudge, and enriched output (Step 5)
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* Address code review: move cols[3] access into try block for IndexError safety
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* fix: align display row count with download count in get_industry_performance_yfinance
The enriched function downloads price data for top 10 tickers but displayed
20 rows, causing rows 11-20 to show N/A in all price columns. This broke
test_industry_perf_falls_back_to_yfinance which asserts N/A count < 5.
Now both download and display use head(10) for consistency.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Co-authored-by: Ahmet Guzererler <guzererler@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
The scanner pipeline now runs end-to-end: Phase 1 (geopolitical, market
movers, sector scanners in parallel via Ollama), Phase 2 (industry deep
dive), Phase 3 (macro synthesis via OpenRouter/DeepSeek R1).
Key changes:
- Add tool_runner.py with run_tool_loop() for inline tool execution in
scanner agents (scanner graph has no ToolNode, unlike trading graph)
- Fix vendor fallback: catch AlphaVantageError base class, raise on
total failure instead of embedding errors in return values
- Rewrite yfinance sector perf to use SPDR ETF proxies (Sector.overview
has no performance data)
- Fix Ollama remote host support in openai_client.py
- Add LangGraph state reducers for parallel fan-out writes
- Add --date CLI flag for non-interactive scanner invocation
- Fix .env loading to find keys from both CWD and project root
- Add hybrid LLM config (per-tier provider/backend_url)
- Add project tracking: DECISIONS.md, PROGRESS.md, MISTAKES.md
- Add 9 new test files covering exceptions, fallback, and routing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Added market-wide analysis capabilities (movers, indices, sectors, industries, topic news)
- Implemented yfinance and Alpha Vantage data fetching modules
- Added LangChain tools for scanner functions
- Created scanner state definitions and graph components
- Integrated scan command into CLI
- Added configuration for scanner_data vendor routing
- Included test files for scanner components
This implements a new feature for global macro scanning to identify market-wide trends and opportunities.
- 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
Copilot
Ahmet Guzererler
Yijia Xiao
luohy15
Max Wong
Yijia Xiao
Geeta Chauhan
Edward Sun
maxer137