plexus.rubric_memory.models module

class plexus.rubric_memory.models.ConfidenceInputs(*, score_version_id: Annotated[str, MinLen(min_length=1)], total_evidence_count: Annotated[int, Ge(ge=0)], score_scope_evidence_count: Annotated[int, Ge(ge=0)], prefix_scope_evidence_count: Annotated[int, Ge(ge=0)] = 0, scorecard_scope_evidence_count: Annotated[int, Ge(ge=0)], unknown_scope_evidence_count: Annotated[int, Ge(ge=0)], high_authority_evidence_count: Annotated[int, Ge(ge=0)], low_authority_evidence_count: Annotated[int, Ge(ge=0)], conflicting_or_stale_evidence_count: Annotated[int, Ge(ge=0)], chronological_evidence_count: Annotated[int, Ge(ge=0)], suggested_confidence: ConfidenceLevel)

Bases: BaseModel

Deterministic inputs used by Python to constrain confidence.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

chronological_evidence_count: int

conflicting_or_stale_evidence_count: int

high_authority_evidence_count: int

low_authority_evidence_count: int

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

prefix_scope_evidence_count: int

score_scope_evidence_count: int

score_version_id: str

scorecard_scope_evidence_count: int

suggested_confidence: ConfidenceLevel

total_evidence_count: int

unknown_scope_evidence_count: int

class plexus.rubric_memory.models.ConfidenceLevel(value)

Bases: str, Enum

HIGH = 'high'

LOW = 'low'

MEDIUM = 'medium'

class plexus.rubric_memory.models.EvidenceClassification(value)

Bases: str, Enum

HISTORICAL_CONTEXT = 'historical_context'

POSSIBLE_STALE_RUBRIC = 'possible_stale_rubric'

RUBRIC_CONFLICTING = 'rubric_conflicting'

RUBRIC_GAP = 'rubric_gap'

RUBRIC_SUPPORTED = 'rubric_supported'

class plexus.rubric_memory.models.EvidenceSnippet(*, snippet_text: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=1)], source_uri: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=1)], scope_level: str = 'unknown', source_type: str = 'unknown', authority_level: str = 'unknown', source_timestamp: ~datetime.datetime | None = None, author: str | None = None, retrieval_score: float = 0.0, policy_concepts: list[str] = <factory>, evidence_classification: ~plexus.rubric_memory.models.EvidenceClassification = EvidenceClassification.HISTORICAL_CONTEXT)

Bases: BaseModel

Corpus evidence with provenance retained from Biblicus retrieval.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

author: str | None

authority_level: str

evidence_classification: EvidenceClassification

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

policy_concepts: list[str]

retrieval_score: float

scope_level: str

snippet_text: str

source_timestamp: datetime | None

source_type: str

source_uri: str

class plexus.rubric_memory.models.RubricAuthority(*, score_version_id: Annotated[str, MinLen(min_length=1)], rubric_text: Annotated[str, MinLen(min_length=1)], score_code: str = '')

Bases: BaseModel

Storage-boundary projection of ScoreVersion authority into rubric terms.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

rubric_text: str

score_code: str

score_version_id: str

class plexus.rubric_memory.models.RubricEvidencePack(*, score_version_id: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=1)], rubric_reading: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=1)], evidence_classification: ~plexus.rubric_memory.models.EvidenceClassification, supporting_evidence: list[~plexus.rubric_memory.models.EvidenceSnippet] = <factory>, conflicting_evidence: list[~plexus.rubric_memory.models.EvidenceSnippet] = <factory>, history_of_change: list[~plexus.rubric_memory.models.RubricHistoryEvent] = <factory>, likely_reason_for_disagreement: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=1)], confidence: ~plexus.rubric_memory.models.ConfidenceLevel, confidence_inputs: ~plexus.rubric_memory.models.ConfidenceInputs, open_questions: list[str] = <factory>)

Bases: BaseModel

Structured answer for one disputed classification.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

confidence: ConfidenceLevel

confidence_inputs: ConfidenceInputs

conflicting_evidence: list[EvidenceSnippet]

evidence_classification: EvidenceClassification

history_of_change: list[RubricHistoryEvent]

likely_reason_for_disagreement: str

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

open_questions: list[str]

rubric_reading: str

score_version_id: str

supporting_evidence: list[EvidenceSnippet]

class plexus.rubric_memory.models.RubricEvidencePackRequest(*, scorecard_identifier: Annotated[str, MinLen(min_length=1)], score_identifier: Annotated[str, MinLen(min_length=1)], score_version_id: Annotated[str, MinLen(min_length=1)], rubric_text: Annotated[str, MinLen(min_length=1)], score_code: str = '', transcript_text: str = '', model_value: str = '', model_explanation: str = '', feedback_value: str = '', feedback_comment: str = '', topic_hint: str | None = None)

Bases: BaseModel

Inputs needed to explain one disputed classification.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

feedback_comment: str

feedback_value: str

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_explanation: str

model_value: str

rubric_text: str

score_code: str

score_identifier: str

score_version_id: str

scorecard_identifier: str

topic_hint: str | None

transcript_text: str

class plexus.rubric_memory.models.RubricHistoryEvent(*, source_timestamp: datetime | None = None, source_uri: Annotated[str, MinLen(min_length=1)], scope_level: str = 'unknown', authority_level: str = 'unknown', summary: Annotated[str, MinLen(min_length=1)], evidence_classification: EvidenceClassification = EvidenceClassification.HISTORICAL_CONTEXT)

Bases: BaseModel

Chronological policy-memory event derived from corpus evidence.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

authority_level: str

evidence_classification: EvidenceClassification

model_config = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

scope_level: str

source_timestamp: datetime | None

source_uri: str

summary: str