Epicure

Compares two ingredients on one named embedding axis, such as sweetness or a cuisine direction. Returns both projections, the difference from ingredient A to ingredient B, percentile labels, and the axis p10/p90 range. Valid axis names are available from list_targets with kind='direction'.

compare_on_axis

Explores complementary ingredients for one or more seed ingredients. It is suited to open-ended pairing questions and recipe or dish design. Returns clustered flavour directions, each seed's strongest secondary connections, and bridge ingredients shared across clusters. Category penalties promote variety, and optional vegan or vegetarian filters remove incompatible suggestions.

find_pairings

Returns the emergent GMM regions that best describe one ingredient. Each result includes a human-labelled mode, cosine similarity to its centroid, dominant cuisine and food group, and representative members. An optional property restricts the search to one axis family.

closest_mode

Returns the nearest ingredients to one seed by cosine similarity in the 300-dimensional embedding. The result is a ranked similarity list with no clustering or dietary filtering, suited to direct substitution and single-ingredient similarity questions.

neighbors

Reports the strongest relationships between named axes in the global flavour space. Positive cosine values indicate aligned axes and negative values indicate opposing axes. Results can be limited and filtered by minimum absolute correlation to keep the response concise.

flavour_correlations

Lists the 20 emergent ICA flavour factors available to ingredient_on_factor and pareto_navigate. Each summary includes the factor index, named axis, pole labels, and coherence ratings. Set include_examples=true to add themes and anchoring ingredients, and use min_coherence to filter the catalogue.

list_factors

Lists valid targets for morph and named axes for compare_on_axis. Directions include cuisines, sensory descriptors, nutrients, NOVA, and diet; modes are emergent GMM regions. Results are paginated by kind and include a concise angle_deg guide for morph.

list_targets

Locates one ingredient on the precomputed 2D UMAP atlas. Returns its coordinate, cuisine and food-group labels, and nearest visual neighbours with 2D distances. The result describes spatial context rather than a named model region.

where_on_atlas

Computes Pareto frontiers that balance similarity to a seed ingredient against movement toward one or more labelled flavour poles. It supports trade-off questions such as finding ingredients that remain rice-like while becoming more aligned with another culinary property. A specific factor and side can be supplied, or relevant poles can be selected automatically.

pareto_navigate

Scores one ingredient against eight macro-region cuisine directions: Japanese, East Asian, Southeast Asian, South Asian, Latin American, Mediterranean, Eastern European, and Western Atlantic. Returns ranked cosine similarities with p10/p90 range context for cuisine-focused questions.

cultural_profile