weaviate_agents.personalization.classes package
- pydantic model weaviate_agents.personalization.classes.Persona[source]
Bases:
BaseModelCreate 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[source]
Bases:
BaseModelInteraction 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[source]
Bases:
BaseModelResponse 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[source]
Bases:
BaseModelCreate 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
- pydantic model weaviate_agents.personalization.classes.PersonalizedObject[source]
Bases:
BaseModelCreate 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)[source]
- !!! abstract “Usage Documentation”
[model_dump](../concepts/serialization.md#python-mode)
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.
exclude_computed_fields – Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended tu use the dedicated round_trip parameter instead.
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].
fallback – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
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[source]
Bases:
BaseModelCreate 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[source]
Bases:
BaseModel,QueryReturnCreate 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.
- pydantic model weaviate_agents.personalization.classes.GetObjectsRequest[source]
Bases:
BaseModelCreate 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[source]
Bases:
BaseModelCreate 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[source]
Bases:
BaseModelCreate 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 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 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[source]
Bases:
BaseModelCreate 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 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 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[source]
Bases:
BaseModelCreate 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 include_vector: bool | str | List[str] = False
- field limit: int | None = None
- field offset: int | None = None
- field query: List[str] | str [Required]
- field query_method: Literal['near_text'] = 'near_text'
- 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[source]
Bases:
BaseModelCreate 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]