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12e6a69
feat(ai): add data classes for time series forecasting and imputation
miladh Oct 2, 2026
22810f5
fix(ai): return an empty frame from to_pandas on an empty result list
miladh Nov 2, 2026
8772cc0
fix(ai): use the pandas helper for the empty index in to_pandas
miladh Nov 2, 2026
a3ec603
fix(ai): read forecast and impute results from the items array
miladh Nov 4, 2026
f71110f
refactor(ai): rename the input classes to ForecastInputDatapoint and …
miladh Nov 4, 2026
d04aa67
refactor(ai): take ForecastInputDatapoint only as datapoints, and add…
miladh Nov 4, 2026
b675bee
docs(ai): explain how value and missing affect what the model sees
miladh Nov 4, 2026
5856c41
docs(ai): explain how to use cohort
miladh Nov 4, 2026
6216571
refactor(ai): parse every quantile key as a level
miladh Nov 4, 2026
2d5e38a
refactor(ai): read the response metadata as the API returns it
miladh Nov 4, 2026
6a5bbcd
refactor(ai): look up forecast and impute results by label only
miladh Nov 4, 2026
cb8eba8
test(ai): skip the quantile classes in the unknown-key loading test
miladh Nov 4, 2026
9ab0e18
feat(ai): include only the median in to_pandas by default
miladh Nov 6, 2026
cd8d112
Apply batched suggestions from code review
miladh Nov 6, 2026
a66cef7
refactor(ai): use match/case to load a ForecastInputDatapoint
miladh Nov 6, 2026
19394d0
refactor(ai): load results with _load_raw_api_response
miladh Nov 6, 2026
4383741
refactor(ai): replace quantile_levels with include_all_quantiles in t…
miladh Nov 6, 2026
d38ce4c
refactor(ai): keep the response metadata as an object on the result l…
miladh Nov 9, 2026
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