The file `tradingagents/dataflows/alpha_vantage.py` previously acted as an aggregator but did not use the imports it defined, leading to linter warnings (ruff). The dependencies in `tradingagents/dataflows/interface.py` were refactored to import directly from the specialized modules instead. This safely allowed removing all unused imports from `alpha_vantage.py`, improving code health and module clarity without affecting functionality.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* 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>
* feat: add extract_json() utility for robust LLM JSON parsing
Handles DeepSeek R1 <think> blocks, markdown code fences, and
preamble/postamble text that LLMs wrap around JSON output.
Applied to macro_synthesis, macro_bridge, and CLI scan output.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: opt-in vendor fallback — fail-fast by default (ADR 011)
Silent cross-vendor fallback corrupts signal quality when data contracts
differ (e.g., AV news has sentiment scores yfinance lacks). Only methods
with fungible data contracts (OHLCV, indices, sector/industry perf,
market movers) now get fallback. All others raise immediately.
- Add FALLBACK_ALLOWED whitelist to interface.py
- Rewrite route_to_vendor() with fail-fast/fallback branching
- Improve error messages with method name, vendors tried, and exception chaining
- Add 11 new tests in test_vendor_failfast.py
- Update ADRs 002 (superseded), 008, 010; create ADR 011
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* docs: add implementation plan for medium-term positioning upgrade
Covers 4 objectives: increased debate rounds, 8-quarter TTM fundamentals,
sector/peer relative performance, and macro regime classification.
https://claude.ai/code/session_01TuPpssTo83whKkNgSu57HH
* feat: medium-term positioning upgrade (debate rounds, TTM, peer comparison, macro regime)
## Changes
### Step 1: Agentic Debate Depth
- Increase `max_debate_rounds` and `max_risk_discuss_rounds` from 1 → 2 in `default_config.py`
- Fix bug in `trading_graph.py`: wire config values into `ConditionalLogic()` (was ignoring config, using hardcoded defaults)
### Step 2: 8-Quarter TTM Fundamental Analysis
- New `tradingagents/dataflows/ttm_analysis.py`: parses quarterly income/balance/cashflow CSV strings, computes TTM (sum of last 4 quarters), QoQ/YoY growth rates, margin trends across 8 quarters
- New `@tool get_ttm_analysis` in `fundamental_data_tools.py`
- Wire into fundamentals ToolNode; register in `TOOLS_CATEGORIES`
- Update fundamentals analyst prompt: "last 8 quarters (2 years)" focus
### Step 3: Sector & Peer Relative Performance
- New `tradingagents/dataflows/peer_comparison.py`: sector peer lookup, 1W/1M/3M/6M/YTD return ranking, alpha vs sector ETF
- New `@tool get_peer_comparison` and `@tool get_sector_relative`
- Wire into fundamentals ToolNode
### Step 4: Macro Regime Flag
- New `tradingagents/dataflows/macro_regime.py`: 6-signal classifier (VIX level/trend, credit spread HYG/LQD, yield curve TLT/SHY, market breadth SPX vs 200-SMA, sector rotation) → risk-on / transition / risk-off
- New `@tool get_macro_regime`; add `macro_regime_report` field to AgentState
- Wire into market ToolNode; feed into research_manager and risk_manager prompts
### Step 5: Tests (88 new unit tests, 0 integration)
- `tests/test_debate_rounds.py` (17 tests)
- `tests/test_ttm_analysis.py` (18 tests)
- `tests/test_peer_comparison.py` (11 tests)
- `tests/test_macro_regime.py` (16 tests)
- `tests/test_config_wiring.py` (12 tests)
All 88 new unit tests pass; no regressions in existing tests.
https://claude.ai/code/session_01TuPpssTo83whKkNgSu57HH
* test: mark live yfinance network tests as integration
TestYfinanceIndustryPerformance, TestRouteToVendorFallback, and TestFallbackRouting
all make live HTTP calls to yfinance (yfinance.Sector / market movers). Mark them
@pytest.mark.integration so they're skipped in standard offline runs.
https://claude.ai/code/session_01TuPpssTo83whKkNgSu57HH
* docs: update memory files for medium-term positioning upgrade
- PROGRESS.md: add milestone section with all new files and changes
- DECISIONS.md: add decisions 008-010 (macro regime, TTM data source, peer comparison)
- MISTAKES.md: add mistakes 10-11 (Python 3.11 f-string, mock data precision)
https://claude.ai/code/session_01TuPpssTo83whKkNgSu57HH
* docs: document git remote setup (origin = aguzererler fork)
origin points to aguzererler/TradingAgents which IS the fork.
No upstream remote configured. All feature branches push to origin.
https://claude.ai/code/session_01TuPpssTo83whKkNgSu57HH
* docs: redirect tracking files to memory system
Replace DECISIONS.md/MISTAKES.md/PROGRESS.md references in CLAUDE.md
with instructions to use /remember memory system. A PreToolUse hook
in ~/.claude/settings.json enforces this by blocking writes to those files.
https://claude.ai/code/session_01TuPpssTo83whKkNgSu57HH
* Initial plan
* Add integration tests for yfinance and Alpha Vantage APIs (78 tests, all passing)
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* Initial plan
* fix: allow .env variables to override DEFAULT_CONFIG values
Merged origin/main and resolved all 8 conflicting files:
- CLAUDE.md: merged MISTAKES.md ref + Project Tracking section + env override docs
- cli/main.py: kept top-level json import, kept try/except in run_pipeline
- tool_runner.py: kept descriptive comments for MAX_TOOL_ROUNDS
- alpha_vantage_common.py: kept thread-safe rate limiter, robust error handling
- interface.py: kept broader exception catch (AlphaVantageError + ConnectionError + TimeoutError)
- default_config.py: kept _env()/_env_int() env var overrides with load_dotenv() at module level
- scanner_graph.py: kept debug mode fix (stream for debug, invoke for result)
- macro_bridge.py: kept get_running_loop() over deprecated get_event_loop()
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* fix: move rate limiter sleep outside lock to avoid blocking threads
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* docs: update PROGRESS, DECISIONS, MISTAKES, CLAUDE with env override implementation
- PROGRESS.md: added env override milestone, updated test count (38 total),
marked Mistake #9 as resolved, added all new/modified files from PR #9
- DECISIONS.md: added Decision 008 (env var config overrides),
Decision 009 (thread-safe rate limiter), Decision 010 (broader
vendor fallback exceptions), updated Decision 007 status to superseded
- MISTAKES.md: updated Mistake #9 status to RESOLVED, added Mistake #10
(rate limiter held lock during sleep)
- CLAUDE.md: added env var override convention docs, updated critical
patterns with rate limiter and config fallback key lessons, updated
mistake count to 10
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* merge main into branch (-X theirs) and fix tests to pass against current main code
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* feat: add scanner tests, global demo key in conftest, remove 48 inline key patches
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* feat: add agentic memory scaffold and migrate tracking files to docs/agent/
Migrate DECISIONS.md, MISTAKES.md, PROGRESS.md, agents/, plans/, and
tradingagents/llm_clients/TODO.md into a structured docs/agent/ scaffold
with ADR-style decisions, plans, templates, and a live state tracker.
This gives agent workflows a standard memory structure for decisions,
plans, logs, and session continuity via CURRENT_STATE.md.
Agent-Ref: docs/agent/plans/global-macro-scanner.md
State-Updated: Yes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: improve Industry Deep Dive report quality with enriched data, sector routing, and tool-call nudge
* 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>
* docs: update memory files after PR #13 (Industry Deep Dive quality fix)
- CURRENT_STATE.md: remove Industry Deep Dive blocker (resolved), update
test count 38 → 53, add PR #13 to Recent Progress, update milestone focus
- decisions/009-industry-deep-dive-quality.md: new ADR documenting the
three-pronged fix (enriched data, explicit sector routing, tool-call nudge)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat: add architecture-coordinator skill for mandatory ADR reading protocol
New Claude Code skill that enforces reading docs/agent/CURRENT_STATE.md,
decisions/, and plans/ before any code changes. Includes conflict resolution
protocol that stops work and quotes the violated ADR rule when user requests
conflict with established architectural decisions.
Files:
- .claude/skills/architecture-coordinator/SKILL.md
- .claude/skills/architecture-coordinator/references/adr-template.md
- .claude/skills/architecture-coordinator/references/reading-checklist.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude <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>
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>