feat: include portfolio holdings in auto mode pipeline analysis (#104)
* Initial plan * feat: include portfolio holdings in auto mode pipeline analysis In run_auto (both AgentOS and CLI), Phase 2 now loads current portfolio holdings and merges their tickers with scan candidates before running the per-ticker pipeline. This ensures the portfolio manager has fresh analysis for both new opportunities and existing positions. Key changes: - macro_bridge.py: add candidates_from_holdings() factory - langgraph_engine.py run_auto: merge holding tickers with scan tickers - cli/main.py auto: load holdings, create StockCandidates, pass to run_pipeline - cli/main.py run_pipeline: accept optional holdings_candidates parameter - 9 new unit tests covering holdings inclusion, dedup, and graceful fallback Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com> Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/53065a07-d9f8-47be-9956-0eb4ee8c87da * fix: normalize ticker case in dedup and clarify count display Address code review feedback: - Use .upper() for case-insensitive ticker comparison in run_pipeline - Display accurate filtered scan count instead of raw candidate count Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com> Agent-Logs-Url: https://github.com/aguzererler/TradingAgents/sessions/53065a07-d9f8-47be-9956-0eb4ee8c87da --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
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parent
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fdf54ae279
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@ -492,16 +492,53 @@ class LangGraphEngine:
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async for evt in self.run_scan(f"{run_id}_scan", {"date": date}):
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yield evt
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# Phase 2: Pipeline analysis — get tickers from saved scan report
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# Phase 2: Pipeline analysis — get tickers from scan report + portfolio holdings
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yield self._system_log("Phase 2/3: Loading stocks from scan report…")
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scan_data = store.load_scan(date)
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tickers = self._extract_tickers_from_scan_data(scan_data)
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scan_tickers = self._extract_tickers_from_scan_data(scan_data)
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# Also include tickers from current portfolio holdings so the PM agent
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# has fresh analysis for existing positions (hold/sell/add decisions).
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portfolio_id = params.get("portfolio_id", "main_portfolio")
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holding_tickers: list[str] = []
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try:
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from tradingagents.portfolio.repository import PortfolioRepository
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_repo = PortfolioRepository()
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_, holdings = _repo.get_portfolio_with_holdings(portfolio_id)
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holding_tickers = [h.ticker.upper() for h in holdings]
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except Exception as exc:
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logger.warning("run_auto: could not load holdings for pipeline: %s", exc)
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# Merge & deduplicate (scan candidates first, then holdings-only tickers)
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seen: set[str] = set()
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tickers: list[str] = []
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for t in scan_tickers:
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up = t.upper()
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if up not in seen:
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seen.add(up)
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tickers.append(up)
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holdings_only: list[str] = []
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for t in holding_tickers:
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if t not in seen:
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seen.add(t)
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tickers.append(t)
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holdings_only.append(t)
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if scan_tickers:
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yield self._system_log(
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f"Phase 2/3: {len(scan_tickers)} ticker(s) from scan report"
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)
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if holdings_only:
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yield self._system_log(
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f"Phase 2/3: {len(holdings_only)} additional ticker(s) from portfolio holdings: "
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+ ", ".join(holdings_only)
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)
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if not tickers:
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yield self._system_log(
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"Warning: no stocks found in scan summary — ensure the scan completed "
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"successfully and produced a 'stocks_to_investigate' list. "
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"Skipping pipeline phase."
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"Warning: no stocks found in scan summary and no portfolio holdings — "
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"ensure the scan completed successfully and produced a "
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"'stocks_to_investigate' list. Skipping pipeline phase."
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)
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else:
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max_concurrent = int(self.config.get("max_concurrent_pipelines", 2))
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43
cli/main.py
43
cli/main.py
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@ -1500,6 +1500,7 @@ def run_pipeline(
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ticker_filter_list: Optional[list[str]] = None,
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analysis_date_opt: Optional[str] = None,
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dry_run_opt: Optional[bool] = None,
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holdings_candidates: Optional[list] = None,
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):
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"""Full pipeline: scan -> filter -> per-ticker deep dive."""
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import asyncio
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@ -1559,9 +1560,26 @@ def run_pipeline(
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# Parse macro output
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macro_context, all_candidates = parse_macro_output(macro_path)
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candidates = filter_candidates(all_candidates, min_conviction, ticker_filter)
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num_scan_candidates = len(candidates)
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# Append portfolio-holding candidates that aren't already in the scan list
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num_holdings_added = 0
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if holdings_candidates:
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scan_tickers = {c.ticker.upper() for c in candidates}
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extra = [h for h in holdings_candidates if h.ticker.upper() not in scan_tickers]
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if extra:
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console.print(
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f"[cyan]Adding {len(extra)} ticker(s) from portfolio holdings: "
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+ ", ".join(c.ticker for c in extra)
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+ "[/cyan]"
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)
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candidates = list(candidates) + extra
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num_holdings_added = len(extra)
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console.print(
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f"\n[cyan]Candidates: {len(candidates)} of {len(all_candidates)} stocks passed filter[/cyan]"
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f"\n[cyan]Candidates: {len(candidates)} total "
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f"({num_scan_candidates} from scan, "
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f"{num_holdings_added} from holdings)[/cyan]"
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)
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table = Table(title="Selected Stocks", box=box.ROUNDED)
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@ -1881,6 +1899,28 @@ def auto(
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console.print("\n[bold magenta]--- Step 1: Market Scan ---[/bold magenta]")
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run_scan(date=date)
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# Load portfolio holdings so existing positions also get pipeline analysis.
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# This gives the portfolio manager fresh data for hold/sell/add decisions.
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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extra_candidates: list = []
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try:
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from tradingagents.portfolio.repository import PortfolioRepository
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repo = PortfolioRepository()
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_, holdings = repo.get_portfolio_with_holdings(portfolio_id)
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if holdings:
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extra_candidates = candidates_from_holdings(holdings)
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console.print(
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f"[cyan]Portfolio '{portfolio_id}' has {len(holdings)} holding(s) — "
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f"{len(extra_candidates)} will be added to pipeline analysis[/cyan]"
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)
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except Exception as e:
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console.print(
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f"[yellow]Could not load portfolio holdings: {e} — "
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f"proceeding with scan candidates only[/yellow]"
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)
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console.print("\n[bold magenta]--- Step 2: Per-Ticker Pipeline ---[/bold magenta]")
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macro_path = get_market_dir(date) / "scan_summary.json"
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run_pipeline(
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@ -1889,6 +1929,7 @@ def auto(
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ticker_filter_list=None,
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analysis_date_opt=date,
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dry_run_opt=False,
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holdings_candidates=extra_candidates or None,
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)
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console.print("\n[bold magenta]--- Step 3: Portfolio Manager ---[/bold magenta]")
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@ -947,6 +947,145 @@ class TestRunAutoTickerSource(unittest.TestCase):
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f"Expected a warning log about AAPL failure. Got: {log_messages}",
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)
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def test_run_auto_includes_holdings_tickers_in_pipeline(self):
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"""run_auto should also run pipeline for portfolio holdings not in scan report."""
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scan_data = {"stocks_to_investigate": ["AAPL"]}
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pipeline_calls = []
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engine = LangGraphEngine()
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async def fake_run_pipeline(run_id, params):
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pipeline_calls.append(params.get("ticker"))
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for _ in ():
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yield {}
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engine.run_pipeline = fake_run_pipeline
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# Create mock holdings
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mock_holding = MagicMock()
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mock_holding.ticker = "MSFT"
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mock_repo = MagicMock()
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mock_repo.get_portfolio_with_holdings.return_value = (MagicMock(), [mock_holding])
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with patch("agent_os.backend.services.langgraph_engine.ScannerGraph",
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return_value=self._make_noop_scanner()), \
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patch("agent_os.backend.services.langgraph_engine.PortfolioGraph",
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return_value=self._make_noop_portfolio_graph()), \
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patch("agent_os.backend.services.langgraph_engine.get_market_dir") as mock_gmd, \
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patch("agent_os.backend.services.langgraph_engine.get_ticker_dir"), \
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patch("tradingagents.report_paths.get_daily_dir") as mock_gdd, \
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patch("agent_os.backend.services.langgraph_engine.ReportStore") as mock_rs_cls, \
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patch("agent_os.backend.services.langgraph_engine.append_to_digest"), \
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patch("agent_os.backend.services.langgraph_engine.extract_json", return_value=scan_data), \
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patch("tradingagents.portfolio.repository.PortfolioRepository", return_value=mock_repo):
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fake_mdir = MagicMock(spec=Path)
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fake_mdir.__truediv__ = MagicMock(return_value=MagicMock(spec=Path))
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fake_mdir.mkdir = MagicMock()
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mock_gmd.return_value = fake_mdir
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fake_daily = MagicMock(spec=Path)
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fake_daily.exists.return_value = False
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mock_gdd.return_value = fake_daily
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mock_rs_cls.return_value = self._make_mock_store(scan_data)
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asyncio.run(_collect(engine.run_auto("auto1", {"date": "2026-01-01"})))
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# Both scan ticker and holdings ticker should be analyzed
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self.assertIn("AAPL", pipeline_calls)
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self.assertIn("MSFT", pipeline_calls)
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def test_run_auto_deduplicates_scan_and_holdings_tickers(self):
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"""A ticker appearing in both scan and holdings should only run once."""
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scan_data = {"stocks_to_investigate": ["AAPL", "TSLA"]}
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pipeline_calls = []
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engine = LangGraphEngine()
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async def fake_run_pipeline(run_id, params):
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pipeline_calls.append(params.get("ticker"))
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for _ in ():
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yield {}
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engine.run_pipeline = fake_run_pipeline
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# Holding that overlaps with scan candidate
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mock_holding = MagicMock()
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mock_holding.ticker = "AAPL"
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mock_repo = MagicMock()
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mock_repo.get_portfolio_with_holdings.return_value = (MagicMock(), [mock_holding])
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with patch("agent_os.backend.services.langgraph_engine.ScannerGraph",
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return_value=self._make_noop_scanner()), \
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patch("agent_os.backend.services.langgraph_engine.PortfolioGraph",
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return_value=self._make_noop_portfolio_graph()), \
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patch("agent_os.backend.services.langgraph_engine.get_market_dir") as mock_gmd, \
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patch("agent_os.backend.services.langgraph_engine.get_ticker_dir"), \
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patch("tradingagents.report_paths.get_daily_dir") as mock_gdd, \
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patch("agent_os.backend.services.langgraph_engine.ReportStore") as mock_rs_cls, \
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patch("agent_os.backend.services.langgraph_engine.append_to_digest"), \
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patch("agent_os.backend.services.langgraph_engine.extract_json", return_value=scan_data), \
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patch("tradingagents.portfolio.repository.PortfolioRepository", return_value=mock_repo):
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fake_mdir = MagicMock(spec=Path)
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fake_mdir.__truediv__ = MagicMock(return_value=MagicMock(spec=Path))
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fake_mdir.mkdir = MagicMock()
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mock_gmd.return_value = fake_mdir
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fake_daily = MagicMock(spec=Path)
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fake_daily.exists.return_value = False
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mock_gdd.return_value = fake_daily
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mock_rs_cls.return_value = self._make_mock_store(scan_data)
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asyncio.run(_collect(engine.run_auto("auto1", {"date": "2026-01-01"})))
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# AAPL should appear only once (not duplicated)
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self.assertEqual(pipeline_calls.count("AAPL"), 1)
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self.assertIn("TSLA", pipeline_calls)
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def test_run_auto_proceeds_when_holdings_load_fails(self):
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"""Pipeline should still run scan tickers even if holdings fail to load."""
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scan_data = {"stocks_to_investigate": ["AAPL"]}
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pipeline_calls = []
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engine = LangGraphEngine()
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async def fake_run_pipeline(run_id, params):
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pipeline_calls.append(params.get("ticker"))
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for _ in ():
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yield {}
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engine.run_pipeline = fake_run_pipeline
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mock_repo = MagicMock()
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mock_repo.get_portfolio_with_holdings.side_effect = RuntimeError("DB unavailable")
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with patch("agent_os.backend.services.langgraph_engine.ScannerGraph",
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return_value=self._make_noop_scanner()), \
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patch("agent_os.backend.services.langgraph_engine.PortfolioGraph",
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return_value=self._make_noop_portfolio_graph()), \
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patch("agent_os.backend.services.langgraph_engine.get_market_dir") as mock_gmd, \
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patch("agent_os.backend.services.langgraph_engine.get_ticker_dir"), \
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patch("tradingagents.report_paths.get_daily_dir") as mock_gdd, \
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patch("agent_os.backend.services.langgraph_engine.ReportStore") as mock_rs_cls, \
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patch("agent_os.backend.services.langgraph_engine.append_to_digest"), \
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patch("agent_os.backend.services.langgraph_engine.extract_json", return_value=scan_data), \
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patch("tradingagents.portfolio.repository.PortfolioRepository", return_value=mock_repo):
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fake_mdir = MagicMock(spec=Path)
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fake_mdir.__truediv__ = MagicMock(return_value=MagicMock(spec=Path))
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fake_mdir.mkdir = MagicMock()
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mock_gmd.return_value = fake_mdir
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fake_daily = MagicMock(spec=Path)
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fake_daily.exists.return_value = False
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mock_gdd.return_value = fake_daily
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mock_rs_cls.return_value = self._make_mock_store(scan_data)
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asyncio.run(_collect(engine.run_auto("auto1", {"date": "2026-01-01"})))
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# Should still run pipeline for scan tickers despite holdings failure
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self.assertIn("AAPL", pipeline_calls)
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# ---------------------------------------------------------------------------
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# TestExtractTickersFromScanData
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@ -212,3 +212,64 @@ class TestReportRendering:
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assert (output_dir / "summary.md").exists()
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assert (output_dir / "results.json").exists()
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assert (output_dir / "NVDA" / "2026-03-17_deep_dive.md").exists()
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class TestCandidatesFromHoldings:
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"""Tests for candidates_from_holdings — portfolio holdings → StockCandidate."""
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def _make_holding(self, ticker, sector=None, industry=None):
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"""Minimal holding-like object with .ticker, .sector, .industry."""
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from types import SimpleNamespace
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return SimpleNamespace(ticker=ticker, sector=sector, industry=industry)
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def test_basic_conversion(self):
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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holdings = [self._make_holding("AAPL", sector="Technology")]
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result = candidates_from_holdings(holdings)
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assert len(result) == 1
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assert result[0].ticker == "AAPL"
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assert result[0].thesis_angle == "portfolio_holding"
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assert result[0].conviction == "medium"
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assert result[0].sector == "Technology"
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def test_skips_existing_tickers(self):
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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holdings = [
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self._make_holding("AAPL"),
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self._make_holding("TSLA"),
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]
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result = candidates_from_holdings(holdings, existing_tickers={"AAPL"})
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assert len(result) == 1
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assert result[0].ticker == "TSLA"
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def test_case_insensitive_dedup(self):
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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holdings = [self._make_holding("aapl")]
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result = candidates_from_holdings(holdings, existing_tickers={"AAPL"})
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assert len(result) == 0
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def test_empty_holdings(self):
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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result = candidates_from_holdings([])
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assert result == []
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def test_deduplicates_within_holdings(self):
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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holdings = [
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self._make_holding("AAPL"),
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self._make_holding("AAPL"),
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]
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result = candidates_from_holdings(holdings)
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assert len(result) == 1
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def test_missing_sector_defaults_to_empty(self):
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from tradingagents.pipeline.macro_bridge import candidates_from_holdings
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holdings = [self._make_holding("TSLA")]
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result = candidates_from_holdings(holdings)
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assert result[0].sector == ""
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@ -138,6 +138,52 @@ def _match_theme(sector: str, themes: list[dict]) -> str:
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return themes[0].get("theme", "") if themes else ""
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# ─── Holdings helpers ─────────────────────────────────────────────────────────
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def candidates_from_holdings(
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holdings: list,
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existing_tickers: set[str] | None = None,
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) -> list[StockCandidate]:
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"""Create StockCandidate objects for portfolio holdings not already in candidates.
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Holdings are assigned ``thesis_angle='portfolio_holding'`` and
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``conviction='medium'`` so the pipeline treats them with equal priority
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while the PM agent can distinguish their source.
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Args:
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holdings: List of Holding objects (must have ``.ticker`` and
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optionally ``.sector`` / ``.industry``).
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existing_tickers: Tickers already present in the scan candidate list
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(uppercase). Holdings matching these are skipped to avoid
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duplicate pipeline runs.
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Returns:
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List of StockCandidate for holdings that aren't already candidates.
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"""
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existing = {t.upper() for t in (existing_tickers or set())}
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result: list[StockCandidate] = []
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for h in holdings:
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ticker = h.ticker.upper()
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if ticker in existing:
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continue
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existing.add(ticker)
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result.append(
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StockCandidate(
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ticker=ticker,
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name=ticker,
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sector=getattr(h, "sector", None) or "",
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rationale="Existing portfolio holding — re-analysis for portfolio review.",
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thesis_angle="portfolio_holding",
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conviction="medium",
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key_catalysts=[],
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risks=[],
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macro_theme="",
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)
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)
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return result
|
||||
|
||||
|
||||
# ─── Core pipeline ────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue