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fix(kronos): pass actual datetime Series to Kronos predictor timestamps

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KronosPredictor.predict() requires x_timestamp and y_timestamp to be
pandas Series of datetime values for its calc_time_stamps() helper.
Previously we passed integer ranges (after reset_index), which raised
AttributeError on .dt.minute. Fixed by extracting datetime index values
before resetting and using future_idx for y_timestamp.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
TPTBusiness
2026-04-18 10:12:51 +02:00
parent 6e52c8a15d
commit cffb9adc38
1 changed files with 5 additions and 3 deletions
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rdagent/components/coder/kronos_adapter.py
+5 -3
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@@ -117,13 +117,15 @@ class KronosAdapter:
if len(ohlcv_df) < context_bars:
raise ValueError(f"Need at least {context_bars} bars, got {len(ohlcv_df)}")
ctx = ohlcv_df.iloc[-context_bars:].copy().reset_index(drop=True)
freq = ohlcv_df.index.freq or pd.infer_freq(ohlcv_df.index[:100])
last_ts = ohlcv_df.index[-1]
future_idx = pd.date_range(start=last_ts, periods=pred_bars + 1, freq=freq or "1min")[1:]
x_timestamp = pd.Series(ctx.index)
y_timestamp = pd.Series(range(len(ctx), len(ctx) + pred_bars))
# Kronos requires actual datetime Series for both timestamps (not integer ranges)
x_timestamp = pd.Series(ohlcv_df.index[-context_bars:].values)
y_timestamp = pd.Series(future_idx)
ctx = ohlcv_df.iloc[-context_bars:].copy().reset_index(drop=True)
pred_df = self._predictor.predict(
df=ctx,