Generate API

Autogenerated reference for the generation module.

generate

Feature value generation helpers built on top of discovered schemas.

The functions in this module take discovery artifacts produced by llm_feature_gen.discover and apply them to class-organized folders of raw inputs, producing CSV files that are ready for downstream analysis.

Functions:

• assign_feature_values_from_folder –

  Generate feature values for every supported file in one class folder.

• generate_features –

  Run the full feature-generation pipeline for a class-organized dataset.

• generate_features_from_images –

  Generate features using outputs/discovered_image_features.json by default.

• generate_features_from_tabular –

  Generate features using outputs/discovered_tabular_features.json by default.

• generate_features_from_texts –

  Generate features using outputs/discovered_text_features.json by default.

• generate_features_from_videos –

  Generate features using outputs/discovered_video_features.json by default.

• load_discovered_features –

  Load and normalize a discovered-features JSON artifact.

• parse_json_from_markdown –

  Parse JSON content that may be wrapped in a fenced Markdown block.

assign_feature_values_from_folder(folder_path: Union[str, Path], class_name: str, discovered_features: Dict[str, Any], provider: Optional[OpenAIProvider] = None, output_dir: Union[str, Path] = 'outputs', use_audio: bool = True, text_column: Optional[str] = None, label_column: Optional[str] = None) -> Path

Generate feature values for every supported file in one class folder.

Parameters:

• folder_path

  (Union[str, Path]) –

  Root dataset folder containing one subdirectory per class.

• class_name

  (str) –

  Name of the class subdirectory to process.

• discovered_features

  (Dict[str, Any]) –

  Discovery payload containing the feature schema.

• provider

  (Optional[OpenAIProvider], default: None ) –

  Provider instance used to generate values. Defaults to OpenAIProvider.

• output_dir

  (Union[str, Path], default: 'outputs' ) –

  Directory where the per-class CSV should be written.

• use_audio

  (bool, default: True ) –

  Whether video files should include audio transcription context when supported by the provider.

• text_column

  (Optional[str], default: None ) –

  Required when processing tabular files. Identifies the column sent to the LLM.

• label_column

  (Optional[str], default: None ) –

  Optional tabular column whose values override the class label for row-level outputs.

Returns:

• Path –

  The path to the generated per-class CSV file.

Raises:

• FileNotFoundError –

  If the requested class folder does not exist.

• ValueError –

  If tabular generation is attempted without text_column.

generate_features(root_folder: Union[str, Path], discovered_features_path: Union[str, Path], output_dir: Union[str, Path] = 'outputs', classes: Optional[List[str]] = None, provider: Optional[OpenAIProvider] = None, merge_to_single_csv: bool = False, merged_csv_name: str = 'all_feature_values.csv', use_audio: bool = True, text_column: Optional[str] = None, label_column: Optional[str] = None) -> Dict[str, str]

Run the full feature-generation pipeline for a class-organized dataset.

Parameters:

• root_folder

  (Union[str, Path]) –

  Dataset root containing one subfolder per class.

• discovered_features_path

  (Union[str, Path]) –

  Path to a JSON artifact produced by one of the discovery helpers.

• output_dir

  (Union[str, Path], default: 'outputs' ) –

  Directory where CSV outputs should be written.

• classes

  (Optional[List[str]], default: None ) –

  Optional subset of class-folder names to process. When omitted, all immediate subdirectories are used.

• provider

  (Optional[OpenAIProvider], default: None ) –

  Provider instance used to generate values.

• merge_to_single_csv

  (bool, default: False ) –

  Whether to concatenate per-class CSVs into one additional file.

• merged_csv_name

  (str, default: 'all_feature_values.csv' ) –

  Filename to use for the merged CSV artifact.

• use_audio

  (bool, default: True ) –

  Whether video generation should include transcript context.

• text_column

  (Optional[str], default: None ) –

  Required for tabular generation.

• label_column

  (Optional[str], default: None ) –

  Optional row-level label override for tabular generation.

Returns:

• Dict[str, str] –

  A mapping from class name to generated CSV path. When

• Dict[str, str] –

  merge_to_single_csv is enabled, the merged output is returned under

• Dict[str, str] –

  the "__merged__" key.

generate_features_from_images(*args, **kwargs) -> Dict[str, str]

Generate features using outputs/discovered_image_features.json by default.

generate_features_from_tabular(*args, **kwargs) -> Dict[str, str]

Generate features using outputs/discovered_tabular_features.json by default.

generate_features_from_texts(*args, **kwargs) -> Dict[str, str]

Generate features using outputs/discovered_text_features.json by default.

generate_features_from_videos(*args, **kwargs) -> Dict[str, str]

Generate features using outputs/discovered_video_features.json by default.

load_discovered_features(path: Union[str, Path]) -> Dict[str, Any]

Load and normalize a discovered-features JSON artifact.

The helper accepts both the list-oriented structure written by the discovery functions and a direct dictionary payload. It normalizes both into a dictionary with a proposed_features key.

parse_json_from_markdown(text: str) -> Dict[str, Any]

Parse JSON content that may be wrapped in a fenced Markdown block.