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ontocast.api.match_models

Pydantic request/response models for match API routes.

Classes

AlignEntitiesRequest

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class AlignEntitiesRequest(BaseModel):
    graphs: list[TaggedGraphInput]
    regime: MatchRegime = MatchRegime.ONTOLOGY_LOOSE
    similarity_threshold: float | None = Field(
        default=None,
        ge=0.0,
        le=1.0,
        description="Unset uses AGG_SIMILARITY_THRESHOLD.",
    )
    embedding_model: str | None = Field(
        default=None, description="Unset uses AGG_EMBEDDING_MODEL."
    )

Attributes

embedding_model = Field(default=None, description='Unset uses AGG_EMBEDDING_MODEL.') class-attribute instance-attribute
graphs instance-attribute
regime = MatchRegime.ONTOLOGY_LOOSE class-attribute instance-attribute
similarity_threshold = Field(default=None, ge=0.0, le=1.0, description='Unset uses AGG_SIMILARITY_THRESHOLD.') class-attribute instance-attribute

AlignEntitiesResponse

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class AlignEntitiesResponse(BaseModel):
    data: dict

Attributes

data instance-attribute

DeriveMatchesRequest

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class DeriveMatchesRequest(BaseModel):
    clusters: list[EntityCluster]
    predicted_graph_id: str
    gt_graph_id: str
    similarity_threshold: float = Field(default=0.0, ge=0.0, le=1.0)

    model_config = ConfigDict(arbitrary_types_allowed=True)

Attributes

clusters instance-attribute
gt_graph_id instance-attribute
model_config = ConfigDict(arbitrary_types_allowed=True) class-attribute instance-attribute
predicted_graph_id instance-attribute
similarity_threshold = Field(default=0.0, ge=0.0, le=1.0) class-attribute instance-attribute

DeriveMatchesResponse

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class DeriveMatchesResponse(BaseModel):
    data: dict

Attributes

data instance-attribute

EvaluateMatchRequest

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class EvaluateMatchRequest(BaseModel):
    predicted_graph: RDFGraph
    gt_graph: RDFGraph
    entity_matches: list[EntityMatch]

    model_config = ConfigDict(arbitrary_types_allowed=True)

Attributes

entity_matches instance-attribute
gt_graph instance-attribute
model_config = ConfigDict(arbitrary_types_allowed=True) class-attribute instance-attribute
predicted_graph instance-attribute

EvaluateMatchResponse

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class EvaluateMatchResponse(BaseModel):
    data: dict

Attributes

data instance-attribute

TaggedGraphInput

Bases: BaseModel

Source code in ontocast/api/match_models.py 
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class TaggedGraphInput(BaseModel):
    id: str
    graph: RDFGraph

    model_config = ConfigDict(arbitrary_types_allowed=True)

Attributes

graph instance-attribute
id instance-attribute
model_config = ConfigDict(arbitrary_types_allowed=True) class-attribute instance-attribute