Feature 1 - Configurable max_auto_tickers:
- Add max_auto_tickers config key (default 10) with TRADINGAGENTS_MAX_AUTO_TICKERS env override
- Macro synthesis agent accepts max_scan_tickers param, injects exact count into LLM prompt
- ScannerGraph passes config value to create_macro_synthesis()
- Backend engine applies safety cap on scan candidates (portfolio holdings always included)
- Frontend adds Max Tickers number input in params panel, sends max_tickers in auto run body
Feature 2 - Run persistence + phase-level node re-run:
- 2A: ReportStore + MongoReportStore gain save/load_run_meta, save/load_run_events,
list_run_metas methods; runs.py persists to disk in finally block; startup hydration
restores historical runs; lazy event loading on GET /{run_id}
- 2B: Analysts + trader checkpoint save/load methods in both stores; engine saves
checkpoints after pipeline completion alongside complete_report.json
- 2C: GraphSetup gains build_debate_subgraph() and build_risk_subgraph() for partial
re-runs; TradingAgentsGraph exposes debate_graph/risk_graph as lazy properties;
NODE_TO_PHASE mapping + run_pipeline_from_phase() engine method;
POST /api/run/rerun-node endpoint with _append_and_store helper
- 2D: Frontend history popover (loads GET /api/run/, sorts by created_at, click to load);
triggerNodeRerun() calls rerun-node endpoint; handleNodeRerun uses phase-level
re-run when active run is loaded
All 890 existing tests pass (10 skipped).
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Add effort parameter (high/medium/low) for Claude 4.5+ and 4.6 models,
consistent with OpenAI reasoning_effort and Google thinking_level.
Also add content normalization for Anthropic responses.
* gitignore
* feat: unify report paths under reports/daily/{date}/ hierarchy
All generated artifacts now land under a single reports/ tree:
- reports/daily/{date}/market/ for scan results (was results/macro_scan/)
- reports/daily/{date}/{TICKER}/ for per-ticker analysis (was reports/{TICKER}_{timestamp}/)
- reports/daily/{date}/{TICKER}/eval/ for eval logs (was eval_results/{TICKER}/...)
Adds tradingagents/report_paths.py with centralized path helpers used by
CLI commands, trading graph, and pipeline.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: structured observability logging for LLM, tool, and vendor calls
Add RunLogger (tradingagents/observability.py) that emits JSON-lines events
for every LLM call (model, agent, tokens in/out, latency), tool invocation
(tool name, args, success, latency), data vendor call (method, vendor,
success/failure, latency), and report save.
Integration points:
- route_to_vendor: log_vendor_call() on every try/catch
- run_tool_loop: log_tool_call() on every tool invoke
- ScannerGraph: new callbacks param, passes RunLogger.callback to all LLM tiers
- pipeline/macro_bridge: picks up RunLogger from thread-local, passes to TradingAgentsGraph
- cli/main.py: one RunLogger per command (analyze/scan/pipeline), write_log()
at end, summary line printed to console
Log files co-located with reports:
reports/daily/{date}/{TICKER}/run_log.jsonl (analyze)
reports/daily/{date}/market/run_log.jsonl (scan)
reports/daily/{date}/run_log.jsonl (pipeline)
Also fix test_long_response_no_nudge: update "A"*600 → "A"*2100 to match
MIN_REPORT_LENGTH=2000 threshold set in an earlier commit.
Update memory system context files (ARCHITECTURE, COMPONENTS, CONVENTIONS,
GLOSSARY, CURRENT_STATE) to document observability and report path systems.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.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>
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