graphai.api.ontology.schemas module

class graphai.api.ontology.schemas.TreeResponseElem(*, child_id: str, parent_id: str)

Bases: BaseModel

Object representing the output of the /ontology/tree endpoint.

child_id: str

parent_id: str

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.TreeResponse(*, child_to_parent: List[TreeResponseElem] | None = None)

Bases: BaseModel

child_to_parent: List[TreeResponseElem] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.CategoryInfoResponse(*, category_id: str, depth: int, id: str, name: str)

Bases: BaseModel

category_id: str

depth: int

id: str

name: str

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.ConceptDetails(*, id: str | None, name: str | None)

Bases: BaseModel

id: str | None

name: str | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Bases: BaseModel

info: CategoryInfoResponse | None

parent_category: str | None

child_categories: List[str] | None

clusters: List[str] | None

concepts: List[ConceptDetails] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.ClusterDetailsResponse(*, parent: str | None, concepts: List[ConceptDetails] | None)

Bases: BaseModel

parent: str | None

concepts: List[ConceptDetails] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Bases: ConceptDetails

parent_category: str | None

parent_cluster: str | None

branch: List[str] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.OpenalexCategoryNearestTopicsResponseElem(*, category_id: str, category_name: str, topic_id: str, topic_name: str, embedding_score: float, wikipedia_score: float, score: float)

Bases: BaseModel

category_id: str

category_name: str

topic_id: str

topic_name: str

embedding_score: float

wikipedia_score: float

score: float

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

graphai.api.ontology.schemas.OpenalexTopicNearestCategoriesResponseElem: alias of OpenalexCategoryNearestTopicsResponseElem

class graphai.api.ontology.schemas.RecomputeClustersRequest(*, n_clusters: int = 2200, min_n: int = 1)

Bases: BaseModel

n_clusters: int

min_n: int

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.OneConceptResponseElement(*, name: str, id: int)

Bases: BaseModel

name: str

id: int

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.RecomputeClustersTaskResponse(*, results: Dict[int, List[OneConceptResponseElement]] | None = None, category_assignments: Dict[int, str] | None = None, impurity_count: int, impurity_proportion: float, successful: bool)

Bases: BaseModel

results: Dict[int, List[OneConceptResponseElement]] | None

category_assignments: Dict[int, str] | None

impurity_count: int

impurity_proportion: float

successful: bool

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.RecomputeClustersResponse(*, task_id: str, task_name: str | None = None, task_status: str, task_result: RecomputeClustersTaskResponse | None)

Bases: TaskStatusResponse

task_result: RecomputeClustersTaskResponse | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.BreakUpClusterRequest(*, cluster_id: str, n_clusters: int | List[int] = 2)

Bases: BaseModel

cluster_id: str

n_clusters: int | List[int]

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.BreakUpClustersClusterNumberResponse(*, clusters: Dict[int, List[OneConceptResponseElement]] | None = None, n_clusters: int)

Bases: BaseModel

clusters: Dict[int, List[OneConceptResponseElement]] | None

n_clusters: int

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.BreakUpClustersResponse(*, results: List[BreakUpClustersClusterNumberResponse] | None = None)

Bases: BaseModel

results: List[BreakUpClustersClusterNumberResponse] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphDistanceRequest(*, src: str, src_type: Literal['concept', 'cluster', 'category'] = 'concept', tgt: str, tgt_type: Literal['concept', 'cluster', 'category'] = 'category', avg: Literal['none', 'linear', 'log'] = 'linear', coeffs: None | Tuple[float, float] = (1.0, 1.0))

Bases: BaseModel

src: str

src_type: Literal['concept', 'cluster', 'category']

tgt: str

tgt_type: Literal['concept', 'cluster', 'category']

avg: Literal['none', 'linear', 'log']

coeffs: None | Tuple[float, float]

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphDistanceResponse(*, sim: None | float = None)

Bases: BaseModel

sim: None | float

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphNearestCategoryRequest(*, avg: Literal['none', 'linear', 'log', 'adaptive'] = 'log', coeffs: None | Tuple[float, float] = (1.0, 10.0), top_n: int = 1, top_down_search: bool = False, use_embeddings: bool = False)

Bases: BaseModel

avg: Literal['none', 'linear', 'log', 'adaptive']

coeffs: None | Tuple[float, float]

top_n: int

top_down_search: bool

use_embeddings: bool

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphConceptNearestCategoryRequest(*, avg: Literal['none', 'linear', 'log', 'adaptive'] = 'log', coeffs: None | Tuple[float, float] = (1.0, 10.0), top_n: int = 1, top_down_search: bool = False, use_embeddings: bool = False, src: str, return_clusters: int | None = 3)

Bases: GraphNearestCategoryRequest

src: str

return_clusters: int | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphClusterNearestCategoryRequest(*, avg: Literal['none', 'linear', 'log', 'adaptive'] = 'log', coeffs: None | Tuple[float, float] = (1.0, 10.0), top_n: int = 1, top_down_search: bool = False, use_embeddings: bool = False, src: List[str] | str)

Bases: GraphNearestCategoryRequest

src: List[str] | str

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.NearestClusterElement(*, cluster_id: str, score: float, rank: int)

Bases: BaseModel

cluster_id: str

score: float

rank: int

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.NearestCategoryElement(*, category_id: str, score: float, rank: int)

Bases: BaseModel

category_id: str

score: float

rank: int

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.NearestCategoryElementWithClusters(*, category_id: str, score: float, rank: int, clusters: List[NearestClusterElement] | None = None)

Bases: NearestCategoryElement

clusters: List[NearestClusterElement] | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.EmbeddingEnabledNearestEntityResponse(*, embeddings_used: bool)

Bases: BaseModel

embeddings_used: bool

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphConceptNearestCategoryResponse(*, embeddings_used: bool, scores: None | List[NearestCategoryElementWithClusters] = None, parent_category: None | str = None, valid: bool, existing_label: str | None = None)

Bases: EmbeddingEnabledNearestEntityResponse

scores: None | List[NearestCategoryElementWithClusters]

parent_category: None | str

valid: bool

existing_label: str | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphClusterNearestCategoryResponse(*, embeddings_used: bool, scores: None | List[NearestCategoryElement] = None, parent_category: None | str = None, existing_label: str | None = None)

Bases: EmbeddingEnabledNearestEntityResponse

scores: None | List[NearestCategoryElement]

parent_category: None | str

existing_label: str | None

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphNearestConceptRequest(*, src: str, top_n: int = 1, use_embeddings: bool = False)

Bases: BaseModel

src: str

top_n: int

use_embeddings: bool

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class graphai.api.ontology.schemas.GraphNearestConceptResponse(*, embeddings_used: bool, closest: None | List[str] = None, scores: None | List[float] = None)

Bases: EmbeddingEnabledNearestEntityResponse

closest: None | List[str]

scores: None | List[float]

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].