weaviate_agents.personalization.classes package

pydantic model weaviate_agents.personalization.classes.Persona

Bases: BaseModel

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.

field persona_id: UUID [Required]

field properties: Dict[str, Any] [Required]

pydantic model weaviate_agents.personalization.classes.PersonaInteraction

Bases: BaseModel

Interaction between a persona and an item.

If replace_previous_interactions is True, the interaction history for that specific item and persona pair will be replaced with the new interaction.

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.

field created_at: datetime | None = None

field item_id: UUID [Required]

field persona_id: UUID [Required]

field replace_previous_interactions: bool = False

field weight: float [Required]

pydantic model weaviate_agents.personalization.classes.PersonaInteractionResponse

Bases: BaseModel

Response model for persona interactions when retrieving them.

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.

field created_at: str [Required] (alias 'createdAt')

field item_id: UUID [Required] (alias 'uuid')

field weight: float [Required]

pydantic model weaviate_agents.personalization.classes.PersonalizationAgentGetObjectsResponse

Bases: BaseModel

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.

field objects: list[PersonalizedObject] [Required]

field ranking_rationale: str | None = None

field usage: Usage [Required]

pydantic model weaviate_agents.personalization.classes.PersonalizedObject

Bases: BaseModel

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.

field original_rank: int [Required]

field personalized_rank: int | None [Required]

field properties: Dict[str, Any] [Required]

field uuid: UUID [Required]

model_dump(**kwargs)

Usage docs: https://docs.pydantic.dev/2.8/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include – A set of fields to include in the output.

• exclude – A set of fields to exclude from the output.

• context – Additional context to pass to the serializer.

• by_alias – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset – Whether to exclude fields that have not been explicitly set.

• exclude_defaults – Whether to exclude fields that are set to their default value.

• exclude_none – Whether to exclude fields that have a value of None.

• round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A dictionary representation of the model.

pydantic model weaviate_agents.personalization.classes.Usage

Bases: BaseModel

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.

field details: Dict[str, int] | Dict[str, str] | None = None

field request_tokens: int | str | None = None

field requests: int | str = 0

field response_tokens: int | str | None = None

field total_tokens: int | str | None = None

pydantic model weaviate_agents.personalization.classes.PersonalizedQueryResponse

Bases: BaseModel, QueryReturn

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.

field objects: List[Object[P, R]] [Required]

Validated by:

• _ensure_metadata_type

field usage: Usage [Required]

pydantic model weaviate_agents.personalization.classes.GetObjectsRequest

Bases: BaseModel

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.

field decay_rate: float = 0.1

field exclude_interacted_items: bool = True

field exclude_items: List[str] = []

field explain_results: bool = True

field filters: Annotated[_Filters, PlainSerializer(func=serialise_filter, return_type=PydanticUndefined, when_used=always)] | None = None

field instruction: str | None = None

field limit: int = 10

field persona_id: UUID [Required]

field recent_interactions_count: int = 100

field use_agent_ranking: bool = True

pydantic model weaviate_agents.personalization.classes.PersonalizationRequest

Bases: BaseModel

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.

field collection_name: str [Required]

field create: bool = True

field headers: Dict[str, str] | None = None

field item_collection_vector_name: str | None = None

field persona_properties: Dict[str, str] | None = None

pydantic model weaviate_agents.personalization.classes.BM25QueryParameters

Bases: BaseModel

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.

field auto_limit: int | None = None

field filters: Annotated[_Filters, serialise_filter] | None = None

field include_vector: bool | str | List[str] = False

field limit: int | None = None

field offset: int | None = None

field query: str | None [Required]

field query_method: Literal['bm25'] = 'bm25'

field query_properties: List[str] | None = None

field rerank: Rerank | None = None

field return_metadata: METADATA | None = None

field return_properties: ReturnProperties[dict] | None = None

field return_references: ReturnReferences[dict] | None = None

pydantic model weaviate_agents.personalization.classes.HybridQueryParameters

Bases: BaseModel

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.

field alpha: int | float = 0.7

field auto_limit: int | None = None

field filters: Annotated[_Filters, serialise_filter] | None = None

field fusion_type: HybridFusion | None = None

field include_vector: bool | str | List[str] = False

field limit: int | None = None

field max_vector_distance: int | float | None = None

field offset: int | None = None

field query: str | None [Required]

field query_method: Literal['hybrid'] = 'hybrid'

field query_properties: List[str] | None = None

field rerank: Rerank | None = None

field return_metadata: METADATA | None = None

field return_properties: ReturnProperties[dict] | None = None

field return_references: ReturnReferences[dict] | None = None

field target_vector: TargetVectorJoinType | None = None

field vector: Annotated[HybridVectorType, serialise_hybrid_vector_type] | None = None

pydantic model weaviate_agents.personalization.classes.NearTextQueryParameters

Bases: BaseModel

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.

field auto_limit: int | None = None

field certainty: int | float | None = None

field distance: int | float | None = None

field filters: Annotated[_Filters, serialise_filter] | None = None

field include_vector: bool | str | List[str] = False

field limit: int | None = None

field move_away: Annotated[Move, serialise_move] | None = None

field move_to: Annotated[Move, serialise_move] | None = None

field offset: int | None = None

field query: List[str] | str [Required]

field query_method: Literal['near_text'] = 'near_text'

field rerank: Rerank | None = None

field return_metadata: METADATA | None = None

field return_properties: ReturnProperties[dict] | None = None

field return_references: ReturnReferences[dict] | None = None

field target_vector: TargetVectorJoinType | None = None

pydantic model weaviate_agents.personalization.classes.QueryRequest

Bases: BaseModel

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.

field decay_rate: float [Required]

field overfetch_factor: float [Required]

field persona_id: UUID [Required]

field query_parameters: QueryParameters [Required]

field recent_interactions_count: int [Required]

field strength: float [Required]