Merge pull request #1310 from TauricResearch/v0.4.2

Point-in-time fixes, honest failure reporting, and housekeeping

.github/workflows/ci.yml

@@ -57,5 +57,5 @@ jobs:
         run: pip install "ruff>=0.15"
       - name: Lint the repository
         # The repo is fully clean under the strict select, so we lint everything
-        # (results/ and worklog/ are excluded via pyproject extend-exclude).
+        # (generated results/ is excluded via pyproject extend-exclude).
         run: ruff check .

pyproject.toml

@@ -69,7 +69,7 @@ filterwarnings = [
 [tool.ruff]
 line-length = 100
 target-version = "py310"
-extend-exclude = ["results", "worklog"]
+extend-exclude = ["results"]
 
 [tool.ruff.lint]
 # Standard "good defaults" rule set (pyflakes + pycodestyle + isort + bugbear +

tests/test_alpha_vantage_hardening.py

@@ -3,7 +3,8 @@
 Regressions for #990 (no request timeout -> can hang), #991 (invalid-key
 responses mislabeled as rate limits and silently treated as transient), and
 #1115 (fundamentals look-ahead filter never ran because the payload is a JSON
-string, not a dict).
+string, not a dict), and the date trim that keeps post-end_date bars out of a
+historical run.
 """
 import json
 
@@ -11,6 +12,7 @@ import pytest
 
 import tradingagents.dataflows.alpha_vantage_common as av
 import tradingagents.dataflows.alpha_vantage_fundamentals as avf
+import tradingagents.dataflows.alpha_vantage_stock as avs
 
 
 class _FakeResponse:
@@ -94,3 +96,40 @@ def test_fundamentals_no_curr_date_passes_through(monkeypatch):
 def test_fundamentals_non_json_body_unchanged(monkeypatch):
     monkeypatch.setattr(avf, "_make_api_request", lambda fn, params: "not-json")
     assert avf.get_cashflow("AAPL", curr_date="2024-01-01") == "not-json"
+
+
+# ---------------------------------------------------------------------------
+# Date trim (see the rationale on the unguarded trim in alpha_vantage_common)
+# ---------------------------------------------------------------------------
+
+_DAILY_CSV = (
+    "timestamp,open,high,low,close,volume\n"
+    "2024-05-13,1,1,1,1,10\n"   # after end_date -> must never be served
+    "2024-05-10,1,1,1,1,10\n"
+    "2024-05-09,1,1,1,1,10\n"
+)
+
+
+@pytest.mark.unit
+def test_stock_data_is_trimmed_to_the_requested_window(monkeypatch):
+    monkeypatch.setattr(avs, "_make_api_request", lambda *a, **k: _DAILY_CSV)
+    out = avs.get_stock("IBM", "2024-05-09", "2024-05-10")
+    assert "2024-05-10" in out and "2024-05-09" in out
+    assert "2024-05-13" not in out, "bar after end_date leaked into the window"
+
+
+@pytest.mark.unit
+def test_unparseable_body_is_never_served_untrimmed(monkeypatch):
+    """The trim used to swallow the failure and return the whole body, putting
+    bars after end_date into a backtest. It must raise instead."""
+    monkeypatch.setattr(avs, "_make_api_request",
+                        lambda *a, **k: "timestamp,close\nnot-a-date,1\n")
+
+    with pytest.raises(ValueError):
+        avs.get_stock("IBM", "2024-05-09", "2024-05-10")
+
+
+@pytest.mark.unit
+def test_empty_body_still_passes_through(monkeypatch):
+    monkeypatch.setattr(avs, "_make_api_request", lambda *a, **k: "")
+    assert avs.get_stock("IBM", "2024-05-09", "2024-05-10") == ""

tests/test_fundamentals_lookahead.py

@@ -0,0 +1,130 @@
+"""Historical fundamentals must not leak a live company profile (#1300).
+
+Vendor "company overview" endpoints (yfinance ``Ticker.info``, Alpha Vantage
+``OVERVIEW``) serve only present-day values: market cap, valuation multiples,
+the 52-week range and TTM income all move with today's quote, and even name,
+sector and industry shift when a company renames or is reclassified. None of it
+carries a historical vintage, so emitting it into a run dated in the past puts
+post-decision information into the analyst's context, in the same family as the
+FRED (#1275), social (#1220) and memory (#1251) leaks.
+
+Both vendors withhold on one shared rule (``date_window.withhold_live_profile``)
+so switching ``fundamental_data`` between them cannot reintroduce the leak. The
+statement tools stay point-in-time by filtering on ``curr_date``, and a live run
+is unchanged. All API access is mocked.
+"""
+from __future__ import annotations
+
+from unittest import mock
+
+import pytest
+
+from tradingagents.dataflows import alpha_vantage_fundamentals as av, date_window, y_finance
+
+_TODAY = "2026-09-07"
+_PAST = "2024-05-10"
+
+# A profile payload mixing stable-looking identity fields with market-dependent ones.
+_INFO = {
+    "longName": "Apple Inc.",
+    "sector": "Technology",
+    "industry": "Consumer Electronics",
+    "marketCap": 3_500_000_000_000,
+    "trailingPE": 34.2,
+    "fiftyTwoWeekHigh": 260.1,
+    "totalRevenue": 391_000_000_000,
+}
+
+# Values that must never reach a historical run.
+_LEAKY = ("3500000000000", "34.2", "260.1", "391000000000",
+          "Apple Inc.", "Technology", "Consumer Electronics")
+
+
+def _yf(curr_date, info=_INFO, today=_TODAY):
+    with mock.patch.object(date_window, "get_current_date", return_value=today), \
+         mock.patch.object(y_finance, "yf_retry", lambda fn: info), \
+         mock.patch.object(y_finance.yf, "Ticker"):
+        return y_finance.get_fundamentals("AAPL", curr_date)
+
+
+def _av(curr_date, today=_TODAY):
+    """Alpha Vantage path; the API call is mocked so a leak would be visible."""
+    with mock.patch.object(date_window, "get_current_date", return_value=today), \
+         mock.patch.object(av, "_make_api_request",
+                           return_value="MarketCapitalization: 3500000000000") as req:
+        return av.get_fundamentals("AAPL", curr_date), req
+
+
+@pytest.mark.unit
+class TestYFinanceHistoricalRun:
+    def test_no_profile_value_survives(self):
+        out = _yf(_PAST)
+        for leaked in _LEAKY:
+            assert leaked not in out, f"leaked live-profile value {leaked!r}"
+
+    def test_states_the_as_of_date_and_explains_itself(self):
+        # The analyst must be told why the figures are absent, so it does not
+        # read the gap as a real signal or fabricate around it.
+        out = _yf(_PAST)
+        assert f"Point-in-time as of: {_PAST}" in out
+        assert "withheld" in out
+        assert _PAST in out and _TODAY in out
+
+    def test_no_wall_clock_retrieval_stamp(self):
+        # The old header stamped datetime.now(), which is what surfaced the leak.
+        assert "Data retrieved on:" not in _yf(_PAST)
+
+    def test_the_request_is_not_even_made(self):
+        # The response would only be discarded; skipping it also avoids burning
+        # vendor quota on a call whose result cannot be used.
+        with mock.patch.object(date_window, "get_current_date", return_value=_TODAY), \
+             mock.patch.object(y_finance.yf, "Ticker") as tk:
+            y_finance.get_fundamentals("AAPL", _PAST)
+        tk.assert_not_called()
+
+
+@pytest.mark.unit
+class TestAlphaVantageHistoricalRun:
+    """The same rule must hold for the other fundamentals vendor, or switching
+    data_vendors["fundamental_data"] would silently reintroduce the leak."""
+
+    def test_overview_is_withheld(self):
+        out, _ = _av(_PAST)
+        assert "3500000000000" not in out
+        assert "withheld" in out
+        assert f"Point-in-time as of: {_PAST}" in out
+
+    def test_the_api_call_is_not_made(self):
+        _, req = _av(_PAST)
+        req.assert_not_called()
+
+    def test_live_run_still_calls_the_api(self):
+        out, req = _av(_TODAY)
+        req.assert_called_once()
+        assert "3500000000000" in out
+
+
+@pytest.mark.unit
+class TestLiveRunUnchanged:
+    def test_yfinance_current_date_returns_the_full_profile(self):
+        out = _yf(_TODAY)
+        for value in _LEAKY:
+            assert value in out
+        assert "Data retrieved on:" in out
+        assert "withheld" not in out
+
+    def test_yfinance_absent_curr_date_returns_the_full_profile(self):
+        out = _yf(None)
+        assert "Market Cap: 3500000000000" in out
+        assert "withheld" not in out
+
+
+@pytest.mark.unit
+class TestNoUsableFieldsStillRaises:
+    def test_stub_payload_raises_no_market_data(self):
+        # yfinance returns {"trailingPegRatio": None} for unknown symbols; on a
+        # live run that must stay a hard "no data", not a bare header.
+        from tradingagents.dataflows.symbol_utils import NoMarketDataError
+
+        with pytest.raises(NoMarketDataError):
+            _yf(_TODAY, info={"trailingPegRatio": None})

tests/test_ohlcv_latest_bar.py

@@ -4,8 +4,12 @@ yfinance can return the newest in-range bar with a NaN close (an unsettled or
 glitched session). The old path parsed dates without normalizing timezone and
 dropped every NaN-close row before applying the curr_date cutoff, so the latest
 bar disappeared and the previous trading day looked like the latest. Now dates
-are normalized, and a latest in-range bar with no close raises rather than
+are normalized before the cutoff, so the frame ends at the last settled bar
-silently falling back.
+instead of carrying a fabricated close.
+
+Refusing the whole frame instead (the first attempt at #1201) reported a
+tradable symbol as invalid or delisted (#1289), so only a range with no close
+anywhere counts as no data and the staleness check judges the rest.
 """
 from __future__ import annotations
 
@@ -92,19 +96,46 @@ def _run_load(monkeypatch, tmp_path, frame, curr_date):
     def _fail_download(*a, **k):
         raise AssertionError("should use the seeded cache, not download")
     monkeypatch.setattr(su.yf, "download", _fail_download)
-    monkeypatch.setattr(su, "_assert_ohlcv_not_stale", lambda *a, **k: None)
     return su.load_ohlcv("AAPL", curr_date)
 
 
 @pytest.mark.unit
-def test_latest_in_range_nan_close_raises_not_silent_fallback(monkeypatch, tmp_path):
+def test_unsettled_latest_bar_is_served_as_the_last_settled_bar(monkeypatch, tmp_path):
-    # Newest bar (the curr_date) has no close -> raise, don't return Thursday.
+    # Newest bar (the curr_date) has no close: serve the last settled bar rather
+    # than reporting the whole symbol as unavailable (#1289).
     frame = pd.DataFrame({
         "Date": ["2026-05-07", "2026-05-08"],
         "Open": [100.0, 101.0], "High": [101.0, 102.0], "Low": [99.0, 100.0],
         "Close": [100.5, float("nan")], "Volume": [1_000_000, 1_000_000],
     })
-    with pytest.raises(NoMarketDataError, match="no closing price"):
+    out = _run_load(monkeypatch, tmp_path, frame, "2026-05-08")
+    assert out["Date"].iloc[-1] == pd.Timestamp("2026-05-07")
+    assert out["Close"].iloc[-1] == 100.5
+
+
+@pytest.mark.unit
+def test_no_settled_bar_at_all_is_still_no_data(monkeypatch, tmp_path):
+    frame = pd.DataFrame({
+        "Date": ["2026-05-07", "2026-05-08"],
+        "Open": [100.0, 101.0], "High": [101.0, 102.0], "Low": [99.0, 100.0],
+        "Close": [float("nan"), float("nan")], "Volume": [1_000_000, 1_000_000],
+    })
+    with pytest.raises(NoMarketDataError, match="no bar in range has a closing price"):
+        _run_load(monkeypatch, tmp_path, frame, "2026-05-08")
+
+
+@pytest.mark.unit
+def test_serving_the_last_settled_bar_does_not_bypass_the_staleness_check(
+    monkeypatch, tmp_path
+):
+    # Falling back must not resurrect a long-dead series: once the closeless
+    # tail is gone, the remaining bar is judged on its age like any other.
+    frame = pd.DataFrame({
+        "Date": ["2026-01-05", "2026-05-08"],
+        "Open": [100.0, 101.0], "High": [101.0, 102.0], "Low": [99.0, 100.0],
+        "Close": [100.5, float("nan")], "Volume": [1_000_000, 1_000_000],
+    })
+    with pytest.raises(NoMarketDataError, match="stale"):
         _run_load(monkeypatch, tmp_path, frame, "2026-05-08")
 
 

tests/test_ollama_base_url.py

@@ -3,9 +3,20 @@
 from __future__ import annotations
 
 import importlib
+import re
 
 import pytest
 
+# Rich colorizes console output and highlights numbers and URLs, which splits
+# asserted substrings with escape codes ("port \x1b[1;33m11434"). Whether it
+# does so depends on the ambient terminal, so strip the codes to keep these
+# assertions independent of where the suite runs.
+_ANSI = re.compile(r"\x1b\[[0-9;]*m")
+
+
+def _console_out(capsys) -> str:
+    return _ANSI.sub("", capsys.readouterr().out)
+
 
 @pytest.fixture(scope="module", autouse=True)
 def _resync_reloaded_modules():
@@ -122,7 +133,7 @@ def test_confirm_endpoint_shows_default(monkeypatch, capsys):
     import cli.utils as cli_utils
     importlib.reload(cli_utils)
     cli_utils.confirm_ollama_endpoint("http://localhost:11434/v1")
-    out = capsys.readouterr().out
+    out = _console_out(capsys)
     assert "http://localhost:11434/v1" in out
     assert "OLLAMA_BASE_URL" not in out  # not from env
     assert "Note" not in out  # no warnings for the canonical default
@@ -133,7 +144,7 @@ def test_confirm_endpoint_marks_env_origin(monkeypatch, capsys):
     import cli.utils as cli_utils
     importlib.reload(cli_utils)
     cli_utils.confirm_ollama_endpoint("http://remote-host:11434/v1")
-    out = capsys.readouterr().out
+    out = _console_out(capsys)
     assert "http://remote-host:11434/v1" in out
     assert "OLLAMA_BASE_URL" in out
 
@@ -144,7 +155,7 @@ def test_confirm_endpoint_warns_on_missing_scheme(monkeypatch, capsys):
     import cli.utils as cli_utils
     importlib.reload(cli_utils)
     cli_utils.confirm_ollama_endpoint("0.0.0.128")
-    out = capsys.readouterr().out
+    out = _console_out(capsys)
     assert "missing a scheme" in out
     assert "http://<host>:11434/v1" in out
 
@@ -155,7 +166,7 @@ def test_confirm_endpoint_warns_on_non_default_port_remote(monkeypatch, capsys):
     import cli.utils as cli_utils
     importlib.reload(cli_utils)
     cli_utils.confirm_ollama_endpoint("http://remote-host/v1")
-    out = capsys.readouterr().out
+    out = _console_out(capsys)
     assert "port 11434" in out
 
 
@@ -165,7 +176,7 @@ def test_confirm_endpoint_quiet_on_local_no_port(monkeypatch, capsys):
     import cli.utils as cli_utils
     importlib.reload(cli_utils)
     cli_utils.confirm_ollama_endpoint("http://localhost/v1")
-    out = capsys.readouterr().out
+    out = _console_out(capsys)
     assert "Note" not in out  # localhost is fine without explicit port
 
 

tests/test_reddit_fallback.py

@@ -86,9 +86,9 @@ class TestRssParsing:
         assert posts[0]["created_utc"] > 0
         assert "datacenter unit" in posts[0]["selftext"]
 
-    def test_malformed_xml_fails_open(self):
+    def test_malformed_xml_reports_unavailable(self):
         with patch.object(reddit, "urlopen", return_value=_resp(lambda: b"<<not xml>>")):
-            assert reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0) == []
+            assert reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0) is None
 
 
 @pytest.mark.unit
@@ -139,7 +139,7 @@ class TestRss429Backoff:
              patch.object(reddit.time, "sleep"):
             posts = reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0)
         assert op.call_count == 2          # one retry, then gives up cleanly
-        assert posts == []
+        assert posts is None
 
     def test_retry_after_header_is_honoured(self):
         err = HTTPError("url", 429, "Too Many Requests", {"Retry-After": "12"}, None)
@@ -166,7 +166,7 @@ class TestRss429Backoff:
             reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0)
         slept.assert_called_once()
         (wait,), _ = slept.call_args
-        assert 4.0 <= wait <= 6.0  # 5s +/-20% jitter
+        assert 48.0 <= wait <= 72.0  # 60s +/-20% jitter
 
 
 @pytest.mark.unit
@@ -174,9 +174,9 @@ class TestChunkedTransferErrorsHandled:
     """IncompleteRead/RemoteDisconnected come from http.client and are NOT
     OSErrors, so they were previously uncaught and crashed the pipeline (#1024)."""
 
-    def test_rss_incomplete_read_degrades_to_empty(self):
+    def test_rss_incomplete_read_reports_unavailable(self):
         with patch.object(reddit, "urlopen", return_value=_raise(http.client.IncompleteRead(b""))):
-            assert reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0) == []
+            assert reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0) is None
 
     def test_json_incomplete_read_falls_back_to_rss(self):
         with patch.object(reddit, "urlopen", return_value=_raise(http.client.IncompleteRead(b""))), \
@@ -190,7 +190,7 @@ class TestChunkedTransferErrorsHandled:
         big = _resp(lambda: b"x" * 100)
         with patch.object(reddit, "_MAX_FEED_BYTES", 10), \
              patch.object(reddit, "urlopen", return_value=big):
-            assert reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0) == []
+            assert reddit._fetch_subreddit_rss("NVDA", "stocks", 5, 5.0) is None
 
 
 @pytest.mark.unit
@@ -228,7 +228,7 @@ class TestCryptoSearchTerm:
     def _captured_ticker(self, ticker):
         seen = {}
 
-        def fake_fetch(t, sub, limit, timeout):
+        def fake_fetch(t, sub, limit, timeout, **kwargs):
             seen["ticker"] = t
             return []
 
@@ -241,3 +241,64 @@ class TestCryptoSearchTerm:
 
     def test_equity_passes_through(self):
         assert self._captured_ticker("NVDA") == "NVDA"
+
+
+@pytest.mark.unit
+class TestFailedFetchIsNotSilence:
+    """A throttled fetch must not be rendered as "no posts found" (#1295).
+
+    Returning [] for both a failed request and a genuinely empty search made the
+    sentiment analyst read rate limiting as real silence ("r/stocks and
+    r/investing are silent"), which is a signal that was never observed.
+    """
+
+    _POST = {
+        "title": "NVDA pops", "score": None, "num_comments": None,
+        "created_utc": reddit._iso_to_timestamp("2026-05-20T14:30:00Z"),
+        "selftext": "", "source": "rss",
+    }
+
+    def _run(self, results):
+        """Drive fetch_reddit_posts with a per-subreddit result sequence."""
+        subs = tuple(f"s{i}" for i in range(len(results)))
+        with patch.object(reddit, "_fetch_subreddit", side_effect=list(results)):
+            return reddit.fetch_reddit_posts(
+                "NVDA", subreddits=subs, inter_request_delay=0
+            )
+
+    def test_failed_subreddit_is_marked_unavailable_not_empty(self):
+        out = self._run([None, [self._POST]])
+        assert "unavailable" in out
+        assert "no posts found" not in out.split("unavailable")[0]
+
+    def test_all_sources_failing_does_not_claim_no_posts(self):
+        out = self._run([None, None])
+        assert "Reddit unavailable" in out
+        assert "no Reddit posts found" not in out
+
+    def test_mixed_failure_and_empty_only_claims_silence_for_searched_subs(self):
+        # s0 failed, s1 genuinely returned nothing: the "no posts" claim must
+        # cover only s1, with s0 reported separately as unavailable.
+        out = self._run([None, []])
+        assert "r/s1" in out.split("unavailable (fetch failed)")[0]
+        assert "unavailable (fetch failed): r/s0" in out
+
+    def test_genuine_empty_still_reports_no_posts(self):
+        out = self._run([[], []])
+        assert "no Reddit posts found" in out
+        assert "unavailable" not in out
+
+    def test_retry_is_not_spent_again_after_a_failure(self):
+        # The 60s back-off must be paid at most once per run, so subsequent
+        # subreddits are fetched with retry disabled rather than stalling.
+        seen = []
+
+        def record(t, sub, limit, timeout, _retry=True):
+            seen.append(_retry)
+            return None
+
+        with patch.object(reddit, "_fetch_subreddit", side_effect=record):
+            reddit.fetch_reddit_posts(
+                "NVDA", subreddits=("a", "b", "c"), inter_request_delay=0
+            )
+        assert seen == [True, False, False]

tests/test_structured_agents.py

@@ -97,6 +97,43 @@ class TestNullishFloatCoercion:
         )
         assert d.price_target is None
 
+    def test_percentage_answer_to_a_price_field_becomes_none(self):
+        # The Trader is asked for concrete levels and may answer a price field
+        # with a distance ("15%"), which failed the whole proposal (#1288).
+        # A percentage cannot be salvaged: 15% must not become a $15 stop.
+        for pct in ("15%", " 7.5% ", "-10%"):
+            p = TraderProposal(
+                action=TraderAction.BUY,
+                reasoning="x",
+                entry_price=pct,
+                stop_loss=pct,
+            )
+            assert p.entry_price is None
+            assert p.stop_loss is None
+
+    def test_human_formatted_price_is_reduced_to_its_number(self):
+        p = TraderProposal(
+            action=TraderAction.BUY,
+            reasoning="x",
+            entry_price="$1,234.50",
+            stop_loss="1,180",
+        )
+        assert p.entry_price == 1234.50
+        assert p.stop_loss == 1180.0
+
+    def test_one_bad_field_no_longer_fails_the_whole_proposal(self):
+        # Previously a single '15%' raised, forcing a free-text retry that lost
+        # the action and reasoning; now the rest of the proposal survives.
+        p = TraderProposal(
+            action=TraderAction.SELL,
+            reasoning="downgrade on margin compression",
+            entry_price="612.40",
+            stop_loss="15%",
+        )
+        assert p.action is TraderAction.SELL
+        assert p.entry_price == 612.40
+        assert p.stop_loss is None
+
 
 @pytest.mark.unit
 class TestRenderResearchPlan:
@@ -393,6 +430,21 @@ def _structured_sentiment_llm(captured: dict, report: SentimentReport | None = N
 
 @pytest.mark.unit
 class TestSentimentAnalystAgent:
+    @pytest.fixture(autouse=True)
+    def _stub_prefetched_sources(self, monkeypatch):
+        """Stub the sources the analyst pre-fetches before prompting.
+
+        create_sentiment_analyst fetches news, StockTwits and Reddit itself, so
+        without this these tests hit the live network. A real Reddit 429 then
+        backs the fetcher off for a minute per subreddit, which is what turned
+        this file into a multi-minute hang.
+        """
+        from tradingagents.agents.analysts import sentiment_analyst as sentiment
+
+        monkeypatch.setattr(sentiment, "fetch_stocktwits_messages", lambda *a, **k: "st")
+        monkeypatch.setattr(sentiment, "fetch_reddit_posts", lambda *a, **k: "rd")
+        monkeypatch.setattr(sentiment.get_news, "func", lambda *a, **k: "news", raising=False)
+
     def test_structured_path_produces_rendered_markdown(self):
         captured = {}
         report = SentimentReport(

tradingagents/agents/schemas.py

@@ -31,9 +31,23 @@ _NULLISH_FLOAT = {"", "none", "n/a", "na", "null", "nil", "-", "tbd", "unknown"}
 
 
 def _coerce_optional_float(value):
-    if isinstance(value, str) and value.strip().lower() in _NULLISH_FLOAT:
+    """Normalise an LLM-written optional numeric field before validation.
-        return None
+
+    Three shapes show up in practice: a placeholder string ("None", "N/A") in
+    place of an omitted value (#1058); a percentage where a price was asked for
+    ("15%", #1288); and a human-formatted price ("$1,234.50"). A percentage
+    cannot be salvaged into an absolute level -- reading "15%" as 15 would put a
+    stop at $15 on a $600 stock -- so it is dropped like a placeholder, leaving
+    one bad field to null out instead of failing the whole proposal. A formatted
+    price is reduced to its number. Anything else passes through to pydantic.
+    """
+    if not isinstance(value, str):
         return value
+    text = value.strip()
+    if text.lower() in _NULLISH_FLOAT or text.endswith("%"):
+        return None
+    cleaned = text.replace(",", "").lstrip("$€£¥").strip()
+    return cleaned or None
 
 
 # ---------------------------------------------------------------------------
@@ -140,11 +154,19 @@ class TraderProposal(BaseModel):
     )
     entry_price: float | None = Field(
         default=None,
-        description="Optional entry price target in the instrument's quote currency.",
+        description=(
+            "Optional entry price target as an absolute number in the instrument's "
+            "quote currency (e.g. 189.5), never a percentage or a range. Omit it "
+            "if you cannot state a specific level."
+        ),
     )
     stop_loss: float | None = Field(
         default=None,
-        description="Optional stop-loss price in the instrument's quote currency.",
+        description=(
+            "Optional stop-loss as an absolute price in the instrument's quote "
+            "currency (e.g. 172.0), never a percentage. Convert a percentage "
+            "distance to the price level it implies, or omit it."
+        ),
     )
     position_sizing: str | None = Field(
         default=None,

tradingagents/agents/trader/trader.py

@@ -50,6 +50,13 @@ def create_trader(llm):
                     "You are a trading agent analyzing market data to make investment decisions. "
                     "Based on your analysis, provide a specific recommendation to buy, sell, or hold. "
                     + grounding
+                    # Entry/stop are numeric price fields. Asking for concrete
+                    # levels invites a percentage ("15%"), which is not a price
+                    # and fails the structured parse (#1288).
+                    + "State entry price and stop-loss as absolute price levels in the "
+                    "instrument's quote currency (for example 189.5), never a percentage "
+                    "or a range; convert a percentage distance to the price level it "
+                    "implies, or omit the field if you cannot state a number. "
                     + NO_EXTERNAL_TOOLS
                     + get_language_instruction()
                 ),

tradingagents/dataflows/alpha_vantage_common.py

@@ -128,24 +128,18 @@ def _filter_csv_by_date_range(csv_data: str, start_date: str, end_date: str) ->
     if not csv_data or csv_data.strip() == "":
         return csv_data
 
-    try:
+    # Deliberately unguarded: TIME_SERIES_DAILY_ADJUSTED returns the full series
-        # Parse CSV data
+    # up to today, so this trim is the only thing keeping bars after end_date out
+    # of a historical run. Swallowing a parse failure would serve the untrimmed
+    # body, and with it future prices.
     df = pd.read_csv(StringIO(csv_data))
 
     # Assume the first column is the date column (timestamp)
     date_col = df.columns[0]
     df[date_col] = pd.to_datetime(df[date_col])
 
-        # Filter by date range
     start_dt = pd.to_datetime(start_date)
     end_dt = pd.to_datetime(end_date)
-
     filtered_df = df[(df[date_col] >= start_dt) & (df[date_col] <= end_dt)]
 
-        # Convert back to CSV string
     return filtered_df.to_csv(index=False)
-
-    except Exception as e:
-        # If filtering fails, return original data with a warning
-        print(f"Warning: Failed to filter CSV data by date range: {e}")
-        return csv_data

tradingagents/dataflows/alpha_vantage_fundamentals.py

@@ -1,6 +1,7 @@
 import json
 
 from .alpha_vantage_common import _make_api_request
+from .date_window import withhold_live_profile
 
 
 def _filter_reports_by_date(result, curr_date: str):
@@ -31,13 +32,22 @@ def get_fundamentals(ticker: str, curr_date: str = None) -> str:
     """
     Retrieve comprehensive fundamental data for a given ticker symbol using Alpha Vantage.
 
+    OVERVIEW serves only present-day values and carries no historical vintage, so
+    a past ``curr_date`` withholds it rather than leaking post-decision figures
+    into a backtest (#1300); the statement endpoints below stay point-in-time via
+    ``_filter_reports_by_date``.
+
     Args:
         ticker (str): Ticker symbol of the company
-        curr_date (str): Current date you are trading at, yyyy-mm-dd (not used for Alpha Vantage)
+        curr_date (str): Analysis date, yyyy-mm-dd
 
     Returns:
         str: Company overview data including financial ratios and key metrics
     """
+    withheld = withhold_live_profile(curr_date, ticker)
+    if withheld:
+        return withheld
+
     params = {
         "symbol": ticker,
     }

tradingagents/dataflows/alpha_vantage_indicator.py

@@ -1,5 +1,9 @@
+import logging
+
 from .alpha_vantage_common import AlphaVantageNotConfiguredError, _make_api_request
 
+logger = logging.getLogger(__name__)
+
 
 def get_indicator(
     symbol: str,
@@ -211,5 +215,5 @@ def get_indicator(
         # successful-looking error string.
         raise
     except Exception as e:
-        print(f"Error getting Alpha Vantage indicator data for {indicator}: {e}")
+        logger.warning("Alpha Vantage indicator %s failed: %s", indicator, e)
         return f"Error retrieving {indicator} data: {str(e)}"

tradingagents/dataflows/date_window.py

@@ -13,6 +13,8 @@ from __future__ import annotations
 
 from datetime import datetime, timedelta, timezone
 
+from .utils import get_current_date
+
 
 def to_utc(dt: datetime) -> datetime:
     """Normalize a datetime to UTC-aware; a naive value is assumed to be UTC."""
@@ -28,3 +30,32 @@ def in_window(pub_dt: datetime | None, start_dt: datetime, end_dt: datetime) ->
     if pub_dt is not None:
         return to_utc(start_dt) <= to_utc(pub_dt) < end + timedelta(days=1)
     return end >= datetime.now(timezone.utc) - timedelta(days=1)
+
+
+def withhold_live_profile(curr_date: str | None, label: str) -> str | None:
+    """Notice to serve instead of a live-only company profile, or None to serve it.
+
+    Vendor "company overview" endpoints (yfinance ``Ticker.info``, Alpha Vantage
+    ``OVERVIEW``) carry no historical vintage — not even name, sector and
+    industry, which move when a company renames or is reclassified — so serving
+    one into a run dated in the past leaks post-decision information (#1300).
+    Every fundamentals vendor withholds on this rule, so switching between them
+    cannot reintroduce the leak.
+    """
+    if not curr_date:
+        return None
+    today = get_current_date()
+    if curr_date >= today:
+        return None
+    return (
+        f"# Company Fundamentals for {label}\n"
+        f"# Point-in-time as of: {curr_date}\n\n"
+        f"Profile fundamentals are withheld for this date. This vendor serves "
+        f"only present-day values ({today}) with no historical vintage: market "
+        f"cap, valuation multiples, the 52-week range and TTM income move with "
+        f"today's quote, and even the name, sector and industry reflect today "
+        f"rather than {curr_date} (companies rename and get reclassified). "
+        f"Serving them would put post-decision information into a {curr_date} "
+        f"analysis. Point-in-time fundamentals for {curr_date} are available "
+        f"from the balance sheet, income statement, and cash flow tools."
+    )

tradingagents/dataflows/reddit.py

@@ -10,6 +10,10 @@ off once (honouring ``Retry-After``). RSS lacks score / comment counts, so those
 posts are marked and the formatter omits the metrics rather than printing fake
 zeros.
 
+A fetch that fails is reported as ``<unavailable>``, never as "no posts found":
+the two are different claims, and passing a rate-limited fetch off as silence
+hands the sentiment analyst a signal that was never observed (#1295).
+
 No API key required. Returns formatted plaintext blocks ready for prompt
 injection and degrades gracefully — returns a placeholder string rather than
 raising, so callers never special-case missing data.
@@ -102,9 +106,12 @@ def _strip_html(content: str) -> str:
     return " ".join(html.unescape(text).split())
 
 
-# Headerless-429 backoff when Reddit gives no Retry-After. Jittered so several
+# Headerless-429 backoff when Reddit gives no Retry-After. Measured against
-# analyses sharing an IP don't retry in lockstep and re-collide on the limit.
+# /r/{sub}/search.rss, a retry still 429s at 8s, 10s and 30s of spacing and
-_RETRY_FALLBACK_SECONDS = 5.0
+# succeeds at 60s, so a shorter wait spends the one retry on a request that
+# cannot succeed (#1295). Jittered so several analyses sharing an IP don't
+# retry in lockstep and re-collide on the limit.
+_RETRY_FALLBACK_SECONDS = 60.0
 
 
 def _jitter(seconds: float, frac: float = 0.2) -> float:
@@ -114,14 +121,18 @@ def _jitter(seconds: float, frac: float = 0.2) -> float:
 
 
 def _retry_after_seconds(exc: HTTPError) -> float | None:
-    """Seconds to wait from a 429's ``Retry-After`` header, capped at 30s.
+    """Seconds to wait from a 429's ``Retry-After`` header, capped at 60s.
+
+    The cap matches ``_RETRY_FALLBACK_SECONDS``: honouring less than we would
+    wait on our own would spend the one retry on a request we already know is
+    too early.
 
     Returns ``None`` only when the header is absent or unparseable; a valid
     ``Retry-After: 0`` returns ``0.0`` (retry at once), not ``None``.
     """
     try:
         val = exc.headers.get("Retry-After") if getattr(exc, "headers", None) else None
-        return min(float(val), 30.0) if val is not None else None
+        return min(float(val), 60.0) if val is not None else None
     except (ValueError, TypeError, AttributeError):
         return None
 
@@ -149,13 +160,18 @@ def _fetch_subreddit_rss(
     limit: int,
     timeout: float,
     _retry: bool = True,
-) -> list[dict]:
+) -> list[dict] | None:
     """Default path: parse the public Atom search feed for a subreddit.
 
     Carries no score / comment counts, so those fields are left None and the
     post is tagged ``source="rss"`` for honest display. On a 429 (Reddit's
     per-IP rate limit) we back off once — honouring ``Retry-After`` when
     present — before giving up, so a transient burst doesn't blank the feed.
+
+    Returns ``[]`` when the search ran and matched nothing, and ``None`` when
+    the fetch itself failed. The caller must keep these apart: rendering a
+    failed fetch as "no posts found" hands the sentiment analyst an absence of
+    discussion that was never observed (#1295).
     """
     url = _RSS.format(sub=sub, qs=_search_qs(ticker, limit))
     req = Request(url, headers={"User-Agent": _UA})
@@ -175,12 +191,12 @@ def _fetch_subreddit_rss(
             time.sleep(wait)
             return _fetch_subreddit_rss(ticker, sub, limit, timeout, _retry=False)
         logger.warning("Reddit RSS fetch failed for r/%s · %s: %s", sub, ticker, exc)
-        return []
+        return None
     except (OSError, http.client.HTTPException, ET.ParseError) as exc:
         # OSError covers URLError/TimeoutError/connection resets; HTTPException
         # covers chunked-transfer errors (IncompleteRead/BadStatusLine, #1024).
         logger.warning("Reddit RSS fetch failed for r/%s · %s: %s", sub, ticker, exc)
-        return []
+        return None
 
     posts = []
     for entry in root.findall("atom:entry", _ATOM_NS)[:limit]:
@@ -234,14 +250,15 @@ def _fetch_subreddit(
     sub: str,
     limit: int,
     timeout: float,
-) -> list[dict]:
+    _retry: bool = True,
-    """Fetch one subreddit, RSS-first.
+) -> list[dict] | None:
+    """Fetch one subreddit, RSS-first. ``None`` means the fetch failed.
 
     The JSON search endpoint is reliably WAF-blocked (403) for public clients,
     so we go straight to the RSS feed — which serves our identified User-Agent
     reliably — halving our request volume against Reddit's per-IP rate limit.
     """
-    return _fetch_subreddit_rss(ticker, sub, limit, timeout)
+    return _fetch_subreddit_rss(ticker, sub, limit, timeout, _retry=_retry)
 
 
 def fetch_reddit_posts(
@@ -267,13 +284,26 @@ def fetch_reddit_posts(
     # Crypto reaches us as a Yahoo pair (BTC-USD); search Reddit for the base
     # ("BTC") so the query actually matches discussion instead of near-nothing.
     ticker = crypto_base(ticker) or ticker
+    subreddits = list(subreddits)
     blocks = []
     total_posts = 0
+    unavailable = []
+    allow_retry = True
     for i, sub in enumerate(subreddits):
         if i > 0 and inter_request_delay:
             time.sleep(_jitter(inter_request_delay))
-        posts = _within_window(_fetch_subreddit(ticker, sub, limit_per_sub, timeout),
+        fetched = _fetch_subreddit(ticker, sub, limit_per_sub, timeout, _retry=allow_retry)
-                               start_date, end_date)
+        if fetched is None:
+            # A failed fetch is not an absence of discussion, so it must not be
+            # rendered as "no posts found" (#1295). One failure also means the
+            # per-IP budget is likely gone, so skip the (now 60s) back-off on
+            # the remaining subreddits rather than stalling the run on retries
+            # that cannot succeed; #1286 tracks coordinating this properly.
+            allow_retry = False
+            unavailable.append(sub)
+            blocks.append(f"r/{sub}: <unavailable: fetch failed, not an absence of posts>")
+            continue
+        posts = _within_window(fetched, start_date, end_date)
         total_posts += len(posts)
         if not posts:
             blocks.append(f"r/{sub}: <no posts found mentioning {ticker.upper()} in the past 7 days>")
@@ -306,8 +336,23 @@ def fetch_reddit_posts(
         blocks.append("\n".join(lines))
 
     if total_posts == 0:
+        searched = [s for s in subreddits if s not in unavailable]
+        if not searched:
+            # Every source failed: claiming "no posts" here would assert a
+            # silence we never observed.
             return (
-            f"<no Reddit posts found mentioning {ticker.upper()} across "
+                f"<Reddit unavailable: every source failed to fetch "
-            f"{', '.join(f'r/{s}' for s in subreddits)} in the past 7 days>"
+                f"({', '.join(f'r/{s}' for s in unavailable)}); this is not an "
+                f"absence of discussion>"
             )
+        summary = (
+            f"<no Reddit posts found mentioning {ticker.upper()} across "
+            f"{', '.join(f'r/{s}' for s in searched)} in the past 7 days>"
+        )
+        if unavailable:
+            summary += (
+                f"\n<unavailable (fetch failed): "
+                f"{', '.join(f'r/{s}' for s in unavailable)}>"
+            )
+        return summary
     return "\n\n".join(blocks)

tradingagents/dataflows/stockstats_utils.py

@@ -250,13 +250,20 @@ def load_ohlcv(symbol: str, curr_date: str) -> pd.DataFrame:
     # Filter to curr_date to prevent look-ahead bias in backtesting.
     data = data[data["Date"] <= curr_date_dt]
 
-    # Guard the latest in-range bar before dropping incomplete rows: a newest bar
+    # A closeless newest bar is an unsettled session, not a symbol without data.
-    # with no close is "not settled yet", not "does not exist". Silently dropping
+    # _fill_price_gaps below drops it, here and mid-series alike, so the frame
-    # it would make the previous trading day look like the latest (#1201); raise
+    # ends at the last settled bar; only a range with no close anywhere is no
-    # instead so the router surfaces it rather than fabricating a fallback.
+    # data (#1201, #1289).
     if not data.empty and pd.isna(data["Close"].iloc[-1]):
+        settled = data["Close"].notna().to_numpy().nonzero()[0]
+        if settled.size == 0:
             raise NoMarketDataError(
-            symbol, canonical, "latest in-range OHLCV bar has no closing price"
+                symbol, canonical, "no bar in range has a closing price"
+            )
+        logger.warning(
+            "%s: %d trailing bar(s) through %s have no closing price; using %s "
+            "as the latest close.", canonical, len(data) - settled[-1] - 1,
+            data["Date"].iloc[-1].date(), data["Date"].iloc[settled[-1]].date(),
         )
 
     data = _fill_price_gaps(data)

tradingagents/dataflows/utils.py

@@ -1,10 +1,5 @@
 import re
-from datetime import date, datetime, timedelta
+from datetime import date
-from typing import Annotated
-
-import pandas as pd
-
-SavePathType = Annotated[str, "File path to save data. If None, data is not saved."]
 
 # Tickers can contain letters, digits, dot, dash, underscore, caret
 # (index symbols like ^GSPC), equals (futures like GC=F), and plus
@@ -42,34 +37,5 @@ def safe_ticker_component(value: str, *, max_len: int = 32) -> str:
     return value
 
 
-def save_output(data: pd.DataFrame, tag: str, save_path: SavePathType = None) -> None:
-    if save_path:
-        data.to_csv(save_path, encoding="utf-8")
-        print(f"{tag} saved to {save_path}")
-
-
 def get_current_date():
     return date.today().strftime("%Y-%m-%d")
-
-
-def decorate_all_methods(decorator):
-    def class_decorator(cls):
-        for attr_name, attr_value in cls.__dict__.items():
-            if callable(attr_value):
-                setattr(cls, attr_name, decorator(attr_value))
-        return cls
-
-    return class_decorator
-
-
-def get_next_weekday(date):
-
-    if not isinstance(date, datetime):
-        date = datetime.strptime(date, "%Y-%m-%d")
-
-    if date.weekday() >= 5:
-        days_to_add = 7 - date.weekday()
-        next_weekday = date + timedelta(days=days_to_add)
-        return next_weekday
-    else:
-        return date

tradingagents/dataflows/y_finance.py

@@ -1,3 +1,4 @@
+import logging
 from datetime import datetime
 from typing import Annotated
 
@@ -5,6 +6,7 @@ import pandas as pd
 import yfinance as yf
 from dateutil.relativedelta import relativedelta
 
+from .date_window import withhold_live_profile
 from .stockstats_utils import (
     StockstatsUtils,
     _assert_ohlcv_not_stale,
@@ -14,6 +16,8 @@ from .stockstats_utils import (
 )
 from .symbol_utils import NoMarketDataError, normalize_symbol
 
+logger = logging.getLogger(__name__)
+
 
 def get_YFin_data_online(
     symbol: Annotated[str, "ticker symbol of the company"],
@@ -188,7 +192,7 @@ def get_stock_stats_indicators_window(
     except NoMarketDataError:
         raise  # Unknown/delisted symbol — let the router emit the sentinel
     except Exception as e:
-        print(f"Error getting bulk stockstats data: {e}")
+        logger.warning("Bulk stockstats fetch failed, falling back per-day: %s", e)
         # Fallback to original implementation if bulk method fails
         ind_string = ""
         curr_date_dt = datetime.strptime(curr_date, "%Y-%m-%d")
@@ -263,9 +267,7 @@ def get_stockstats_indicator(
     except NoMarketDataError:
         raise  # Unknown/delisted symbol — let the router emit the sentinel
     except Exception as e:
-        print(
+        logger.warning("Stockstats indicator %s failed on %s: %s", indicator, curr_date, e)
-            f"Error getting stockstats indicator data for indicator {indicator} on {curr_date}: {e}"
-        )
         return ""
 
     return str(indicator_value)
@@ -273,10 +275,22 @@ def get_stockstats_indicator(
 
 def get_fundamentals(
     ticker: Annotated[str, "ticker symbol of the company"],
-    curr_date: Annotated[str, "current date (not used for yfinance)"] = None
+    curr_date: Annotated[str, "analysis date in YYYY-MM-DD format"] = None
 ):
-    """Get company fundamentals overview from yfinance."""
+    """Get company fundamentals overview from yfinance.
+
+    ``Ticker.info`` is a present-day snapshot with no historical vintage, so a
+    past ``curr_date`` withholds it through the shared point-in-time guard
+    (``date_window.withhold_live_profile``, #1300).
+    """
     canonical = normalize_symbol(ticker)
+
+    # Guard before the request: the response would only be discarded, and the
+    # answer does not depend on it.
+    withheld = withhold_live_profile(curr_date, canonical)
+    if withheld:
+        return withheld
+
     try:
         ticker_obj = yf.Ticker(canonical)
         info = yf_retry(lambda: ticker_obj.info)
@@ -315,10 +329,7 @@ def get_fundamentals(
             ("Free Cash Flow", info.get("freeCashflow")),
         ]
 
-        lines = []
+        lines = [f"{label}: {v}" for label, v in fields if v is not None]
-        for label, value in fields:
-            if value is not None:
-                lines.append(f"{label}: {value}")
 
         # yfinance returns a stub dict (e.g. {"trailingPegRatio": None}) for
         # unknown symbols, so `info` is truthy but every field is empty. Treat

tradingagents/llm_clients/model_catalog.py

@@ -61,6 +61,23 @@ _QWEN_MODELS: dict[str, list[ModelOption]] = {
 # Shared model list for MiniMax's global and CN endpoints (same IDs).
 # Full official lineup per platform.minimax.io/docs/api-reference/text-openai-api.
 # M3 carries a 1M-token context window; the M2.x line is 204,800 tokens.
+# Kimi (Moonshot). Source: platform.kimi.ai/docs/models. "Custom model ID" stays
+# available for models newer than this list. The k2.7-code variants are omitted:
+# they are coding specialists, not analysis models.
+_KIMI_MODELS: dict[str, list[ModelOption]] = {
+    "quick": [
+        ("Kimi K2.6 - 256K ctx, thinking modes, agent tasks", "kimi-k2.6"),
+        ("Kimi K3 - Flagship, 1M ctx", "kimi-k3"),
+        ("Custom model ID", "custom"),
+    ],
+    "deep": [
+        ("Kimi K3 - Flagship, 1M ctx, native visual understanding", "kimi-k3"),
+        ("Kimi K2.6 - 256K ctx, thinking modes, agent tasks", "kimi-k2.6"),
+        ("Custom model ID", "custom"),
+    ],
+}
+
+
 _MINIMAX_MODELS: dict[str, list[ModelOption]] = {
     "quick": [
         ("MiniMax-M3 - Latest, 1M ctx, native multimodal", "MiniMax-M3"),
@@ -151,6 +168,7 @@ MODEL_OPTIONS: ProviderModeOptions = {
     "glm-cn": _GLM_MODELS,
     # MiniMax: same model IDs across global (.io) and China (.com) regions,
     # so the two provider keys share one model list.
+    "kimi": _KIMI_MODELS,
     "minimax": _MINIMAX_MODELS,
     "minimax-cn": _MINIMAX_MODELS,
     # OpenRouter: fetched dynamically. Azure: any deployed model name.
@@ -183,7 +201,6 @@ MODEL_OPTIONS: ProviderModeOptions = {
     # stale. The endpoint + key are wired by the provider; the user picks the
     # model their account has access to.
     "mistral": _CUSTOM_ONLY,
-    "kimi": _CUSTOM_ONLY,
     "groq": _CUSTOM_ONLY,
     "nvidia": _CUSTOM_ONLY,
     # Bedrock model IDs / cross-region inference profile IDs are user-specified.