1.42.0

1.42.0

New Features

• Registry: Support truncate_dim for SentenceTransformers models. Truncation set at
  construction (SentenceTransformer(..., truncate_dim=N)) is captured when the model is logged
  and restored on reload. On clients with sentence-transformers 5.0.0 or later, truncate_dim
  is also exposed as a runtime parameter in the model signature.

• Registry: log_model() now captures a representative row from sample_input_data and stores it alongside the model
  so inference code snippets shown in the model registry UI can be pre-filled with realistic values. Pass
  options={"capture_sample_input_data": False} to opt out (e.g., for sensitive data); generic placeholder values
  will be used in the snippets instead.

Bug Fixes

• Registry: Pin transformers<5 for additional HuggingFace pipeline tasks removed in
  transformers 5.x (summarization, text2text-generation, question-answering, and
  translation_*), preventing deployment failures from missing pipeline classes.

Behavior Changes

Deprecations

1.41.0

1.41.0

New Features

• Registry: Extended ParamSpec support to MLflow PyFunc, LightGBM, XGBoost, and CatBoost models.
  Parameters declared in the model signature can now be passed at inference time.

Bug Fixes

Behavior Changes

Deprecations

1.40.0

1.40.0

New Features

Bug Fixes

• Feature Store: get_feature_view() now correctly preserves online_config for feature views whose
  names require SQL quoting (mixed case or special characters such as a space). Previously the returned
  FeatureView reported online=False even when online was enabled at registration, causing
  read_feature_view(store_type=ONLINE) to fail with "Online store is not enabled".

Behavior Changes

Deprecations

1.39.0

1.39.0

New Features

Bug Fixes

• Feature Store: update_feature_view now correctly handles every transition between duration-based
  and CRON-based refresh_freq. Previously a CRON expression was forwarded to the Dynamic Table's
  TARGET_LAG (which Snowflake rejects), duration → cron failed because the companion Task did not
  yet exist, and cron → duration left the Task orphaned and continuing to fire on its old schedule.
  All four (old, new) transitions now correctly create, alter, or drop the Task as needed, with
  symmetric rollback on failure.

Behavior Changes

• Feature Store: For CRON-based feature views, get_feature_view(), list_feature_views(), and
  register_feature_view() now return the original cron expression as refresh_freq instead of
  "DOWNSTREAM". The underlying Dynamic Table still uses TARGET_LAG = 'DOWNSTREAM' with a companion
  Task — this is purely a display change so the round-trip preserves what the user passed in.

• Registry: When target_platforms includes WAREHOUSE and pip installs are needed without a user-supplied
  pip artifact repository, log_model injects snowflake.snowpark.pypi_shared_repository after
  verifying access. This applies to explicit pip_requirements and to pip-only packaging when there are
  no user conda dependencies. If pypi_shared_repository is inaccessible in the pip-only case, automatic packaging
  dependencies fall back to conda instead of forcing pip-only without an index.

Deprecations

1.38.0

1.38.0

New Features

Bug Fixes

Behavior Changes

• Registry: For HuggingFace text-generation pipelines whose tokenizer defines a chat template, the
  auto-inferred signature now matches the OpenAI Chat Completions API
  (_OPENAI_CHAT_SIGNATURE_WITH_PARAMS_SPEC). Inputs are a single messages column and inference
  controls (temperature, max_completion_tokens, stop, n, stream, top_p, frequency_penalty,
  presence_penalty) move from inputs to params with default values. Predictions return the OpenAI
  response shape (id, object, created, model, choices, usage); the generated text is at
  choices[0].message.content instead of outputs[0].generated_text.

• Registry: For HuggingFace image-text-to-text, video-text-to-text, and audio-text-to-text
  pipelines, the auto-inferred signature now uses _OPENAI_CHAT_SIGNATURE_WITH_PARAMS_SPEC instead of
  _OPENAI_CHAT_SIGNATURE_SPEC. The input column set narrows to just messages, and the inference
  controls move to params with default values; the output schema is unchanged.

Deprecations

1.37.0

1.37.0

New Features

• Experiment Tracking: end_run now accepts an optional status argument ("FINISHED" or "FAILED") to explicitly
  set the final run status. When a run's context manager exits with an exception, the status is automatically set to
  "FAILED".

Bug Fixes

• Registry: Fixed log_model() failing for some Snowpark ML Pipeline models with explainability when the
  full pipeline could not be converted to a native object; task inference now uses the final estimator instead.

• Registry: run_batch() now raises a clear ValueError when a partitioned model's output signature
  includes the partition column. Previously this produced duplicate columns in the output, causing
  cryptic Ray/Arrow errors (AttributeError or KeyError) deep in the batch inference pipeline.

Behavior Changes

Deprecations

1.36.0

1.36.0

New Features

• Feature Store: for latency-sensitive online feature view reads, set use_session_warehouse=True to
  re-use the warehouse from the current session and achieve the best latency.

Bug Fixes

• Registry: Pin transformers<5 when saving HuggingFace pipeline models that use tasks removed in
  transformers 5.x (image-to-text, visual-question-answering, conversational), preventing
  deployment failures from missing pipeline classes.

Behavior Changes

• Registry: Logging a model with pip_requirements and no artifact_repository_map now raises a ValueError
  when target_platforms explicitly includes "WAREHOUSE". Previously this combination would silently proceed,
  resulting in the warehouse deployment being silently dropped.

Deprecations

1.35.0

1.35.0

New Features

Bug Fixes

• Registry: Fixed ParamSpec.from_mlflow_spec dropping shape, which caused shaped scalar params
  (e.g., array of ints) from MLflow to fail validation during model import.

Behavior Changes

• ML Jobs: spec_overrides now validates container keys and warns when keys other than name and secrets
  are provided. Additional keys are not officially supported and may not behave as expected.

Deprecations

1.34.0

1.34.0

New Features

• Experiment Tracking: Added list_params and list_metrics methods to retrieve parameters and metrics
  for runs within an experiment. Both methods return a Dataframe and accept an optional run_name argument
  to filter to a specific run.

Bug Fixes

• Feature Store: Fixed generate_dataset()/generate_training_set() SQL generation for Unicode and case-sensitive
  identifiers (for example Japanese column names), ensuring columns are quoted exactly once and preventing SQL
  compilation errors such as unexpected '<column_name>'.

Behavior Changes

• Registry: enable_explainability=True is now allowed for SPCS-only and non-warehouse-runnable models. Previously
  this raised a ValueError.

Deprecations

1.33.0

1.33.0

New Features

• Registry: Extended ParamSpec support to PyTorch models. Parameters declared in the model signature
  can now be passed at inference time, matching the existing support for custom models.
• Registry (PrPr): Added model_init_once model save option to log_model. When set to True, the
  model is loaded once per worker process at startup, eliminating model-loading overhead. Defaults to False.
• Experiment Tracking live logging is out of private preview
  and will become generally available over the next few weeks.
• Registry: Bumped transformers upper bound to <6, adding compatibility with Hugging Face Transformers v5.

Bug Fixes

• Experiment Tracking live logging: Fixed a bug where the tracebacks for uncaught exceptions were not logged when
  the code was running in a with exp.start_run() block.
• Registry: Fixed a thread leak in create_service(block=True) where the log-streaming thread could outlive the
  error handler when service deployment fails.

Behavior Changes

Deprecations