diff --git a/docs/changelogs/index.md b/docs/changelogs/index.md index 5ccd586..47f8b32 100644 --- a/docs/changelogs/index.md +++ b/docs/changelogs/index.md @@ -2,6 +2,7 @@ Welcome to the TimeCopilot Changelog. Here, you will find a comprehensive list of all the changes, updates, and improvements made to the TimeCopilot project. This section is designed to keep you informed about the latest features, bug fixes, and enhancements as we continue to develop and refine the TimeCopilot experience. Stay tuned for regular updates and feel free to explore the details of each release below. +- [v0.0.29](v0.0.29.md) - [v0.0.28](v0.0.28.md) - [v0.0.27](v0.0.27.md) - [v0.0.26](v0.0.26.md) diff --git a/docs/changelogs/v0.0.29.md b/docs/changelogs/v0.0.29.md new file mode 100644 index 0000000..c4d5413 --- /dev/null +++ b/docs/changelogs/v0.0.29.md @@ -0,0 +1,27 @@ +### Features + +* **transformers 5 support (CVE-2026-1839)**: Widened the `transformers` upper bound to `<6` and `huggingface-hub` to `<2.0` so TimeCopilot can install `transformers>=5.0.0rc3`, which remediates [CVE-2026-1839](https://github.com/advisories). Reaching transformers 5 also required bumping `tfc-t0` to `>=0.2.0`, `timecopilot-granite-tsfm` to `>=0.2.1`, `timecopilot-toto` to `>=0.1.7`, and `timecopilot-timesfm` to `>=0.3.0` (previously pinned `huggingface-hub<1` / `transformers<5`, or broken under `huggingface-hub>=1`). See [#359](https://github.com/TimeCopilot/timecopilot/issues/359) and [#360](https://github.com/TimeCopilot/timecopilot/issues/360). + +* **Clean model cache option**: `Forecaster` now accepts a `clean_cache` flag. When enabled, it runs Python garbage collection and clears the CUDA cache after each model runs, reducing peak memory when chaining many foundation models. See [#358](https://github.com/TimeCopilot/timecopilot/pull/358). + + ```python + from timecopilot import TimeCopilotForecaster + from timecopilot.models.foundation.chronos import Chronos + + forecaster = TimeCopilotForecaster( + models=[Chronos(repo_id="amazon/chronos-bolt-tiny")], + clean_cache=True, + ) + ``` + +### Fixes + +* **Python version guards for granite-backed models**: `FlowState` and `PatchTSTFM` now raise a clear `ImportError` on unsupported Python versions (they require `>=3.11,<3.14`, matching `timecopilot-granite-tsfm`), consistent with the existing `TiRex` and `T0` guards. The `timecopilot-granite-tsfm` dependency is gated with the same Python markers so resolution succeeds on Python 3.10/3.14. + +* **Toto compatibility with huggingface-hub 1.x**: `Toto` failed to load under `huggingface-hub>=1` (`Toto._from_pretrained() missing 2 required keyword-only arguments: 'proxies' and 'resume_download'`). Fixed in `timecopilot-toto>=0.1.7`, which no longer requires those arguments. `Toto` (1.0) and `Toto-2` now load correctly under transformers 5. + +* **TimesFM 2.5 compatibility with huggingface-hub 1.x**: `TimesFM` (2.5) failed to load under `huggingface-hub>=1` (`TimesFM_2p5_200M_torch._from_pretrained() missing 2 required keyword-only arguments: 'proxies' and 'resume_download'`). Fixed in `timecopilot-timesfm>=0.3.0`, which re-syncs the TimesFM 2.5 source with upstream (dropping those arguments and migrating to `PyTorchModelHubMixin`). `TimesFM` now loads correctly under transformers 5. + +--- + +**Full Changelog**: https://github.com/TimeCopilot/timecopilot/compare/v0.0.28...v0.0.29 diff --git a/mkdocs.yml b/mkdocs.yml index c765420..d808a88 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -55,6 +55,7 @@ nav: - api/gift-eval/gift-eval.md - Changelogs: - changelogs/index.md + - changelogs/v0.0.29.md - changelogs/v0.0.28.md - changelogs/v0.0.27.md - changelogs/v0.0.26.md diff --git a/pyproject.toml b/pyproject.toml index cf16bb8..dc5af0a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -51,7 +51,9 @@ classifiers = [ "Topic :: Software Development :: Libraries :: Python Modules", ] # NOTE: dependency version notes -# - huggingface-hub can't bump to v1+ until transformers bumps to v5 +# - transformers>=5 (CVE-2026-1839 fix) requires huggingface-hub>=1; the upper +# bounds were widened together (transformers<6, huggingface-hub<2). Reaching +# transformers 5 also requires tfc-t0>=0.2 (older tfc-t0 capped hub<1). # - lightning and pytorch-lightning are the same library # NOTE: dependencies pinned for faster pip installs # versions chosen from uv's dependency resolution @@ -66,7 +68,7 @@ dependencies = [ "fire", "fsspec>=2025.9.0", "gluonts[torch]", - "huggingface-hub>=0.36.2,<1.0", + "huggingface-hub>=0.36.2,<2.0", "hydra-core>=1.3.2", "lightgbm>=4.6.0", "lightning-utilities>=0.15.2", @@ -91,18 +93,17 @@ dependencies = [ "statsforecast>=2.0.2", "tabpfn-time-series==1.0.3 ; python_full_version < '3.13'", "tensorboard>=2.20.0", - "tfc-t0>=0.1.2 ; python_full_version >= '3.11' and python_full_version < '3.14'", - "timecopilot-chronos-forecasting>=0.2.1", - "timecopilot-granite-tsfm>=0.1.2", - "timecopilot-timesfm>=0.2.1", - "timecopilot-tirex>=0.1.0 ; python_full_version >= '3.11'", - "timecopilot-tirex>=0.1.1", + "tfc-t0>=0.2.0 ; python_full_version >= '3.11' and python_full_version < '3.14'", + "timecopilot-chronos-forecasting>=0.2.2", + "timecopilot-granite-tsfm>=0.2.1 ; python_full_version >= '3.11' and python_full_version < '3.14'", + "timecopilot-timesfm>=0.3.0", + "timecopilot-tirex>=0.1.1 ; python_full_version >= '3.11'", "timecopilot-toto-2>=0.1.1", - "timecopilot-toto>=0.1.6", + "timecopilot-toto>=0.1.7", "timecopilot-uni2ts>=0.1.2 ; python_full_version < '3.14'", "torchmetrics>=1.8.2", - "transformers>=4.41,<5 ; python_full_version < '3.13'", - "transformers>=4.48,<5 ; python_full_version >= '3.13'", + "transformers>=4.41,<6 ; python_full_version < '3.13'", + "transformers>=4.48,<6 ; python_full_version >= '3.13'", "tsfeatures>=0.4.5", "utilsforecast[plotting]>=0.2.15", "xgboost>=3.2.0", @@ -112,7 +113,7 @@ license = "MIT" name = "timecopilot" readme = "README.md" requires-python = ">=3.10" -version = "0.0.28" +version = "0.0.29" [project.optional-dependencies] distributed = [ diff --git a/tests/models/conftest.py b/tests/models/conftest.py index 1c32679..bd5b88f 100644 --- a/tests/models/conftest.py +++ b/tests/models/conftest.py @@ -4,9 +4,7 @@ from timecopilot.models.ensembles.median import MedianEnsemble from timecopilot.models.foundation.chronos import Chronos -from timecopilot.models.foundation.flowstate import FlowState from timecopilot.models.foundation.moirai import Moirai -from timecopilot.models.foundation.patchtst_fm import PatchTSTFM from timecopilot.models.foundation.timesfm import TimesFM from timecopilot.models.foundation.toto import Toto from timecopilot.models.ml import ( @@ -99,14 +97,6 @@ def disable_mps_session(monkeypatch): Chronos(repo_id="amazon/chronos-bolt-tiny", alias="Chronos-Bolt"), Chronos(repo_id="amazon/chronos-2", alias="Chronos-2"), Chronos(repo_id="amazon/chronos-2", alias="Chronos-2", batch_size=2), - FlowState(repo_id="ibm-research/flowstate"), - FlowState( - repo_id="ibm-granite/granite-timeseries-flowstate-r1", - alias="FlowState-Granite", - ), - PatchTSTFM( - context_length=2_048, - ), Toto(context_length=256, batch_size=2), Toto( repo_id="Datadog/Toto-2.0-4m", @@ -150,6 +140,19 @@ def disable_mps_session(monkeypatch): models.append(T0(context_length=256, batch_size=2)) +if (3, 11) <= sys.version_info < (3, 14): + from timecopilot.models.foundation.flowstate import FlowState + from timecopilot.models.foundation.patchtst_fm import PatchTSTFM + + models.append(FlowState(repo_id="ibm-research/flowstate")) + models.append( + FlowState( + repo_id="ibm-granite/granite-timeseries-flowstate-r1", + alias="FlowState-Granite", + ) + ) + models.append(PatchTSTFM(context_length=2_048)) + if sys.version_info < (3, 13): from tabpfn_time_series import TabPFNMode diff --git a/tests/models/foundation/test_flowstate.py b/tests/models/foundation/test_flowstate.py index 6e0cfe4..39e8826 100644 --- a/tests/models/foundation/test_flowstate.py +++ b/tests/models/foundation/test_flowstate.py @@ -1,5 +1,14 @@ +import sys + import numpy as np import pandas as pd +import pytest + +if sys.version_info < (3, 11) or sys.version_info >= (3, 14): + pytest.skip( + "FlowState requires Python >= 3.11 and < 3.14", + allow_module_level=True, + ) from timecopilot import TimeCopilotForecaster from timecopilot.models.foundation.flowstate import FlowState diff --git a/tests/models/foundation/test_timesfm.py b/tests/models/foundation/test_timesfm.py index 2cc3e39..75955c7 100644 --- a/tests/models/foundation/test_timesfm.py +++ b/tests/models/foundation/test_timesfm.py @@ -47,13 +47,9 @@ def test_load_model_from_local_path(mocker, model_class, mock_paths): expected_path = os.path.join(local_path, "torch_model.ckpt") mock_loader[0].assert_called_once_with(path=expected_path) elif model_class is _TimesFMV2_p5: - expected_predictor = mock_loader[ - 0 - ].return_value.model.load_checkpoint.return_value - assert predictor is expected_predictor - mock_loader[0].return_value.model.load_checkpoint.assert_called_once_with( - os.path.join(local_path, "model.safetensors") - ) + # `from_pretrained` handles both local directories and HF repos. + assert predictor is mock_loader[0].from_pretrained.return_value + mock_loader[0].from_pretrained.assert_called_once_with(local_path) @pytest.mark.parametrize("model_class, mock_paths", MODEL_PARAMS) diff --git a/tests/models/test_models.py b/tests/models/test_models.py index 06b1718..b15abb2 100644 --- a/tests/models/test_models.py +++ b/tests/models/test_models.py @@ -39,6 +39,26 @@ def test_t0_import_fails(): assert "requires Python >= 3.11 and < 3.14" in str(excinfo.value) +@pytest.mark.skipif( + (3, 11) <= sys.version_info < (3, 14), + reason="FlowState requires Python >= 3.11 and < 3.14", +) +def test_flowstate_import_fails(): + with pytest.raises(ImportError) as excinfo: + from timecopilot.models.foundation.flowstate import FlowState # noqa: F401 + assert "requires Python >= 3.11 and < 3.14" in str(excinfo.value) + + +@pytest.mark.skipif( + (3, 11) <= sys.version_info < (3, 14), + reason="PatchTSTFM requires Python >= 3.11 and < 3.14", +) +def test_patchtst_fm_import_fails(): + with pytest.raises(ImportError) as excinfo: + from timecopilot.models.foundation.patchtst_fm import PatchTSTFM # noqa: F401 + assert "requires Python >= 3.11 and < 3.14" in str(excinfo.value) + + @pytest.mark.skipif( sys.version_info < (3, 13), reason="Sundial requires Python < 3.13", diff --git a/timecopilot/models/foundation/flowstate.py b/timecopilot/models/foundation/flowstate.py index 81f007c..d8c4145 100644 --- a/timecopilot/models/foundation/flowstate.py +++ b/timecopilot/models/foundation/flowstate.py @@ -1,5 +1,9 @@ +import sys from contextlib import contextmanager +if sys.version_info < (3, 11) or sys.version_info >= (3, 14): + raise ImportError("FlowState requires Python >= 3.11 and < 3.14") + import numpy as np import pandas as pd import torch @@ -121,7 +125,7 @@ def _predict_batch( prediction_length=h, scale_factor=scale_factor, batch_first=False, - ).prediction_outputs + ).quantile_outputs fcst = fcst.squeeze(-1).transpose(-1, -2) # now shape is (batch, h, quantiles) fcst_mean = fcst[..., supported_quantiles.index(0.5)] fcst_mean_np = fcst_mean.detach().numpy(force=True) diff --git a/timecopilot/models/foundation/patchtst_fm.py b/timecopilot/models/foundation/patchtst_fm.py index c971443..6fb69a9 100644 --- a/timecopilot/models/foundation/patchtst_fm.py +++ b/timecopilot/models/foundation/patchtst_fm.py @@ -1,5 +1,9 @@ +import sys from contextlib import contextmanager +if sys.version_info < (3, 11) or sys.version_info >= (3, 14): + raise ImportError("PatchTSTFM requires Python >= 3.11 and < 3.14") + import numpy as np import pandas as pd import torch @@ -128,7 +132,7 @@ def _predict_batch( quantile_levels=quantile_levels, # scale_factor=scale_factor, # batch_first=False, - ).quantile_predictions + ).quantile_outputs fcst = fcst.squeeze(-1).transpose(-1, -2) # now shape is (batch, h, quantiles) # may not be the ideal solution, but this should be more adaptable diff --git a/timecopilot/models/foundation/timesfm.py b/timecopilot/models/foundation/timesfm.py index b16ec01..cc97b33 100644 --- a/timecopilot/models/foundation/timesfm.py +++ b/timecopilot/models/foundation/timesfm.py @@ -142,12 +142,10 @@ def _get_predictor( self, prediction_length: int, ) -> TimesFM_2p5_200M_torch: - # automatically detect the best device - # https://github.com/TimeCopilot/timesfm/blob/b810bbdf9f8a1e66396e7bd5cdb3b005e9116d86/src/timesfm/timesfm_2p5/timesfm_2p5_torch.py#L71 - if os.path.exists(self.repo_id): - path = os.path.join(self.repo_id, "model.safetensors") - tfm = TimesFM_2p5_200M_torch().model.load_checkpoint(path) - elif repo_exists(self.repo_id): + # `from_pretrained` handles both a local directory containing + # `model.safetensors` and a Hugging Face repo id, and the model picks + # the best available device on load. + if os.path.exists(self.repo_id) or repo_exists(self.repo_id): tfm = TimesFM_2p5_200M_torch.from_pretrained(self.repo_id) else: raise OSError( diff 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