Added comprehensive unit tests for `fundamentals_analyst`, `market_analyst`,
`social_media_analyst`, and `news_analyst` to verify that they correctly
handle recursive tool calling via `run_tool_loop`. A MockLLM was created
to simulate a two-turn conversation (tool call request followed by a final
report generation) to ensure the `.invoke()` bug does not regress. Added
missing `build_instrument_context` imports to those agents to prevent
NameErrors.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
This commit updates the `fundamentals_analyst`, `market_analyst`,
`social_media_analyst`, and `news_analyst` files to use `run_tool_loop`
instead of `.invoke()`. Using `.invoke()` resulted in the LLM execution
stopping immediately upon a tool call request without executing the tool,
returning an empty report or raw JSON. The `run_tool_loop` function
ensures tools are executed recursively and the final text content is
returned.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.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.
- Point requirements.txt to pyproject.toml as single source of truth
- Resolve welcome.txt path relative to module for CLI portability
- Include cli/static files in package build
- Extract shared normalize_content for OpenAI Responses API and
Gemini 3 list-format responses into base_client.py
- Update README install and CLI usage instructions
Enable use_responses_api for native OpenAI provider, which supports
reasoning_effort with function tools across all model families.
Removes the UnifiedChatOpenAI subclass workaround.
Closes#403
- y_finance.py: replace print() with logger.warning() in bulk-stats fallback
- macro_bridge.py: add elapsed_seconds field to TickerResult, populate in
run_ticker_analysis (success + error paths)
- cli/main.py: move inline 'import time as _time' and rich.progress imports
to module level; use result.elapsed_seconds for accurate per-ticker timing
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/68fcf34c-8d55-4436-b743-f79fff68713f
Before this change, the pipeline showed a generic 'Analyzing...' spinner
for the entire multi-ticker run with no way to know which ticker was
processing or whether anything was actually working.
Changes:
- macro_bridge.py:
- run_ticker_analysis: logs '▶ Starting', '✓ complete in Xs', '✗ FAILED'
with elapsed time per ticker using logger.info/logger.error
- run_all_tickers: replaced asyncio.gather (swallows all progress) with
asyncio.as_completed + optional on_ticker_done(result, done, total)
callback; uses asyncio.Semaphore for max_concurrent control
- Added time and Callable imports
- cli/main.py run_pipeline:
- Replaced Live(Spinner) with Rich Progress bar (spinner + bar + counter
+ elapsed time)
- Prints '▷ Queued: TICKER' before analysis starts for each ticker
- on_ticker_done callback prints '✓ TICKER (N/M, Xs elapsed) → decision'
or '✗ TICKER failed ...' immediately as each ticker finishes
- Prints total elapsed time when all tickers complete
## Problem (Incident Post-mortem)
The pipeline was emitting hundreds of errors:
'Invalid number of return arguments after parsing column name: Date'
Root cause: after _clean_dataframe() lowercases all columns, stockstats.wrap()
promotes 'date' to the DataFrame index. Subsequent df['Date'] access caused
stockstats to try parsing 'Date' as a technical indicator name.
## Fixes
### 1. Fix df['Date'] stockstats bug (already shipped in prior commit)
- stockstats_utils.py + y_finance.py: use df.index.strftime() instead of
df['Date'] after wrap()
### 2. Extract _load_or_fetch_ohlcv() — single OHLCV authority
- Eliminates duplicated 30-line download+cache boilerplate in two places
- Cache filename is always derived from today's date — hardcoded stale date
'2015-01-01-2025-03-25' in local mode is gone
- Corruption/truncation detection: files <50 rows or unparseable are deleted
and re-fetched rather than silently returning bad data
- Drops on_bad_lines='skip' — malformed CSVs now raise instead of silently
dropping rows that would distort indicator calculations
### 3. YFinanceError typed exception
- Defined in stockstats_utils.py; raised instead of print()+return ''
- get_stockstats_indicator now raises YFinanceError on failure so errors
surface to callers rather than delivering empty strings to LLM agents
- interface.py route_to_vendor now catches YFinanceError alongside
AlphaVantageError and FinnhubError — failures appear in observability
telemetry and can trigger vendor fallback
### 4. Explicit date column discovery in alpha_vantage_common
- _filter_csv_by_date_range: replaced df.columns[0] positional assumption
with explicit search for 'time'/'timestamp'/'date' column
- ValueError re-raised (not swallowed) so bad API response shape is visible
### 5. Structured logging
- Replaced all print() calls in changed files with logging.getLogger()
- Added logging import + logger to alpha_vantage_common
## Tests
- tests/unit/test_incident_fixes.py: 12 new unit tests covering all fixes
(dynamic cache filename, corruption re-fetch, YFinanceError propagation,
explicit column lookup, empty download raises)
- tests/integration/test_stockstats_live.py: 11 live tests against real
yfinance API (all major indicators, weekend N/A, regression guard)
- All 70 tests pass (59 unit + 11 live integration)
- Removed unused `import time` from `tradingagents/agents/analysts/news_analyst.py`
- Verified file syntax with `py_compile`
- Confirmed that the import was successfully removed
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Replaces the O(N) database operations in the `TradeExecutor`'s
`execute_decisions` SELL loop with a single `batch_remove_holdings`
call to the repository. The new repository method calculates updates
in memory, resolves duplicate operations on the same ticker, and issues
the updates via newly implemented `psycopg2.extras.execute_batch`
routines on the `SupabaseClient`.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Optimize the _percentile calculation to use heapq.nsmallest or heapq.nlargest when requesting small extreme percentiles (like 5% VaR) from large lists, falling back to sorted() only when necessary. This avoids fully sorting the entire array.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
- New tradingagents/api_usage.py: Pre-run estimation of API calls per vendor
for analyze, scan, and pipeline commands. Includes Alpha Vantage tier
assessment (free: 25/day vs premium: 75/min).
- New CLI command: `estimate-api [analyze|scan|pipeline|all]`
- Enhanced observability: RunLogger.summary() now includes vendor_methods
breakdown (vendor → method → call count)
- Enhanced CLI output: All 3 command summaries (analyze, scan, pipeline)
now show per-vendor breakdown and Alpha Vantage assessment after runs
- 32 new tests in tests/unit/test_api_usage.py
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/bb80e772-3e03-420e-bb0e-76cfdde14a04
- Create docs/FINANCIAL_TOOLS_ANALYSIS.md with comprehensive 4-point analysis:
1. Implementation accuracy review for all indicators and metrics
2. Library assessment (stockstats vs TA-Lib vs pandas-ta)
3. Alpha Vantage debate (local calc vs API-fetched)
4. Data flow & API mapping for every financial tool
- Fix off-by-one in ttm_analysis.py: YoY revenue used quarterly[-4]
(3 quarters back) instead of quarterly[-5] (4 quarters = 1 year back)
- Add test_revenue_yoy_is_four_quarters_back test to validate the fix
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/b594017b-ed84-4786-9b81-200a78eb5d76
- Added edge case test for `_find_col` in `tests/unit/test_ttm_analysis.py` (from PR #56).
- Enhanced `_clean_dataframe` in `tradingagents/dataflows/stockstats_utils.py` to parse dates, drop invalid rows, fill price gaps, and lowercase columns (combining PRs #58 and #60).
- Expanded the test suite in `tests/unit/test_stockstats_utils.py` to cover the new `_clean_dataframe` functionality.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Extracted the API request logic in `finnhub_news.py` to a private `_fetch_company_news_data` helper to properly catch `Exception` and return an empty list without violating the `str` return type of the main `get_company_news` function. Explicitly allows `ThirdPartyTimeoutError` to propagate to preserve timeout behavior.
Added corresponding tests to mock generic API exceptions and invalid response types. Retained the test verifying fallback behavior for invalid numeric values within `get_insider_transactions`.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
- Fixed `_signal_vix_trend` to correctly return neutral for insufficient history (`< 21`).
- Added `test_short_history_is_neutral` to `TestSignalVixTrend`.
- Extended coverage for short history and edge cases in `TestSignalCreditSpread`, `TestSignalYieldCurve`, `TestSignalMarketBreadth`, and `TestSignalSectorRotation`.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
This commit optimizes `PortfolioSnapshot` instantiation when loaded from the DB or JSON dictionaries by removing the immediate `json.loads(holdings_snapshot)` parsing inside the `from_dict` constructor. Instead, it overrides `__getattribute__` to implement a lazy-loading pattern, where the `holdings_snapshot` string is only parsed into a Python dictionary the very first time the field is accessed.
This optimization ensures that parsing large JSON payloads doesn't block the instantiation of snapshots, which is particularly beneficial in workflows that load a large historical series of snapshots but never access their `holdings_snapshot` field.
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
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