weaviate_agents.classes

class weaviate_agents.classes.QueryAgentCollectionConfig(*, name, tenant=None, view_properties=None, target_vector=None, additional_filters=None)[source]

Bases: BaseModel

A collection configuration for the QueryAgent.

Parameters:

  • name (str)

  • tenant (str | None)

  • view_properties (list[str] | None)

  • target_vector (str | list[str] | None)

  • additional_filters (Annotated[_Filters, PlainSerializer(func=~weaviate_agents.serialise.serialise_filter, return_type=PydanticUndefined, when_used=always)] | None)

name

The name of the collection to query.

Type:

str

tenant

Tenant name for collections with multi-tenancy enabled.

Type:

str | None

view_properties

Optional list of property names the agent has the ability to view for this specific collection.

Type:

list[str] | None

target_vector

Optional target vector name(s) for collections with named vectors. Can be a single vector name or a list of vector names.

Type:

str | list[str] | None

additional_filters

Optional filters to apply when the query is executed, in addition to filters selected by the Query Agent (i.e., there are AND combined).

Type:

Annotated[weaviate.collections.classes.filters._Filters, pydantic.functional_serializers.PlainSerializer(func=weaviate_agents.serialise.serialise_filter, return_type=PydanticUndefined, when_used=always)] | None

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 = {'arbitrary_types_allowed': True}

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

name: str
tenant: str | None
view_properties: list[str] | None
target_vector: str | list[str] | None
additional_filters: Annotated[_Filters, PlainSerializer(func=serialise_filter, return_type=PydanticUndefined, when_used=always)] | None
class weaviate_agents.classes.QueryAgentResponse(*, output_type='final_state', original_query, collection_names, searches, aggregations, usage, total_time, is_partial_answer, missing_information, final_answer, sources)[source]

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.

Parameters:
output_type: Literal['final_state']
original_query: str
collection_names: list[str]
searches: list[list[QueryResultWithCollection]]
aggregations: list[list[AggregationResultWithCollection]]
usage: Usage
total_time: float
is_partial_answer: bool
missing_information: list[str]
final_answer: str
sources: list[Source]
display()[source]

Display a pretty-printed summary of the QueryAgentResponse object.

Return type:

None

model_config = {}

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

class weaviate_agents.classes.Source(*, object_id, collection)[source]

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.

Parameters:

  • object_id (str)

  • collection (str)

object_id: str
collection: str
model_config = {}

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

class weaviate_agents.classes.ComparisonOperator(*values)[source]

Bases: str, Enum

EQUALS = '='
LESS_THAN = '<'
GREATER_THAN = '>'
LESS_EQUAL = '<='
GREATER_EQUAL = '>='
NOT_EQUALS = '!='
LIKE = 'LIKE'
CONTAINS_ANY = 'contains_any'
CONTAINS_ALL = 'contains_all'
class weaviate_agents.classes.IntegerPropertyFilter(*, filter_type=KnownFilterType.INTEGER, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter numeric properties using comparison operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.INTEGER])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (float)

filter_type: Literal[KnownFilterType.INTEGER]
operator: ComparisonOperator
value: float
model_config = {}

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

class weaviate_agents.classes.TextPropertyFilter(*, filter_type=KnownFilterType.TEXT, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter text properties using equality or LIKE operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.TEXT])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (str)

filter_type: Literal[KnownFilterType.TEXT]
operator: ComparisonOperator
value: str
model_config = {}

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

class weaviate_agents.classes.BooleanPropertyFilter(*, filter_type=KnownFilterType.BOOLEAN, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter boolean properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.BOOLEAN])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (bool)

filter_type: Literal[KnownFilterType.BOOLEAN]
operator: ComparisonOperator
value: bool
model_config = {}

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

class weaviate_agents.classes.QueryResult(*, queries, filters=[], filter_operators)[source]

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.

Parameters:
queries: list[str | None]
filters: list[list[PropertyFilter]]
filter_operators: Literal['AND', 'OR']
model_config = {}

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

class weaviate_agents.classes.NumericMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
MAX = 'MAXIMUM'
MEAN = 'MEAN'
MEDIAN = 'MEDIAN'
MIN = 'MINIMUM'
MODE = 'MODE'
SUM = 'SUM'
TYPE = 'TYPE'
class weaviate_agents.classes.TextMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
TYPE = 'TYPE'
TOP_OCCURRENCES = 'TOP_OCCURRENCES'
class weaviate_agents.classes.BooleanMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
TYPE = 'TYPE'
TOTAL_TRUE = 'TOTAL_TRUE'
TOTAL_FALSE = 'TOTAL_FALSE'
PERCENTAGE_TRUE = 'PERCENTAGE_TRUE'
PERCENTAGE_FALSE = 'PERCENTAGE_FALSE'
class weaviate_agents.classes.IntegerPropertyAggregation(*, aggregation_type=KnownAggregationType.INTEGER, property_name, metrics)[source]

Bases: KnownPropertyAggregationBase

Aggregate numeric properties using statistical functions.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.INTEGER])

  • property_name (str)

  • metrics (NumericMetrics)

aggregation_type: Literal[KnownAggregationType.INTEGER]
metrics: NumericMetrics
model_config = {}

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

class weaviate_agents.classes.TextPropertyAggregation(*, aggregation_type=KnownAggregationType.TEXT, property_name, metrics, top_occurrences_limit=None)[source]

Bases: KnownPropertyAggregationBase

Aggregate text properties using frequency analysis.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.TEXT])

  • property_name (str)

  • metrics (TextMetrics)

  • top_occurrences_limit (int | None)

aggregation_type: Literal[KnownAggregationType.TEXT]
metrics: TextMetrics
top_occurrences_limit: int | None
model_config = {}

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

class weaviate_agents.classes.BooleanPropertyAggregation(*, aggregation_type=KnownAggregationType.BOOLEAN, property_name, metrics)[source]

Bases: KnownPropertyAggregationBase

Aggregate boolean properties using statistical functions.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.BOOLEAN])

  • property_name (str)

  • metrics (BooleanMetrics)

aggregation_type: Literal[KnownAggregationType.BOOLEAN]
metrics: BooleanMetrics
model_config = {}

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

class weaviate_agents.classes.AggregationResult(*, search_query=None, groupby_property=None, aggregations, filters=[])[source]

Bases: BaseModel

The aggregations to be performed on a collection in a vector database.

They should be based on the original user query and can include multiple aggregations across different properties and metrics.

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.

Parameters:
search_query: str | None
groupby_property: str | None
aggregations: list[PropertyAggregation]
filters: list[PropertyFilter]
model_config = {}

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

class weaviate_agents.classes.Usage(*, requests=0, request_tokens=None, response_tokens=None, total_tokens=None, details=None)[source]

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.

Parameters:

  • requests (int | str)

  • request_tokens (int | str | None)

  • response_tokens (int | str | None)

  • total_tokens (int | str | None)

  • details (Dict[str, int] | Dict[str, str] | None)

requests: int | str
request_tokens: int | str | None
response_tokens: int | str | None
total_tokens: int | str | None
details: Dict[str, int] | Dict[str, str] | None
model_config = {}

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

class weaviate_agents.classes.AggregationResultWithCollection(*, search_query=None, groupby_property=None, aggregations, filters=[], collection)[source]

Bases: AggregationResult

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.

Parameters:
collection: str
model_config = {}

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

class weaviate_agents.classes.QueryResultWithCollection(*, queries, filters=[], filter_operators, collection)[source]

Bases: QueryResult

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.

Parameters:
collection: str
model_config = {}

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

class weaviate_agents.classes.OperationType(*values)[source]

Bases: str, Enum

Types of operations that can be performed on properties.

APPEND = 'append'
UPDATE = 'update'
class weaviate_agents.classes.OperationStep(*, property_name, view_properties, instruction, operation_type)[source]

Bases: BaseModel

Base model for a transformation operation step.

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.

Parameters:

  • property_name (str)

  • view_properties (List[str])

  • instruction (str)

  • operation_type (OperationType)

property_name: str
view_properties: List[str]
instruction: str
operation_type: OperationType
model_config = {}

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

class weaviate_agents.classes.AppendPropertyOperation(*, property_name, view_properties, instruction, operation_type=OperationType.APPEND, data_type)[source]

Bases: OperationStep

Operation to append a new property.

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.

Parameters:

  • property_name (str)

  • view_properties (List[str])

  • instruction (str)

  • operation_type (OperationType)

  • data_type (DataType)

data_type: DataType
operation_type: OperationType
model_config = {}

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

class weaviate_agents.classes.UpdatePropertyOperation(*, property_name, view_properties, instruction, operation_type=OperationType.UPDATE)[source]

Bases: OperationStep

Operation to update an existing property.

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.

Parameters:

  • property_name (str)

  • view_properties (List[str])

  • instruction (str)

  • operation_type (OperationType)

operation_type: OperationType
model_config = {}

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

class weaviate_agents.classes.DependentOperationStep(operation, depends_on=None)[source]

Bases: BaseModel

A wrapper for operation steps that have dependencies on other operations.

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.

Parameters:
operation: OperationStep
depends_on: List[OperationStep] | None
model_config = {}

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

class weaviate_agents.classes.Operations[source]

Bases: object

Factory class for creating transformation operations.

static append_property(property_name, data_type, view_properties, instruction)[source]

Create an operation to append a new property.

Parameters:

  • property_name (str) – Name of the new property to append

  • data_type (DataType) – Data type of the new property

  • view_properties (List[str]) – List of property names to use as context for the transformation

  • instruction (str) – Instruction for how to generate the new property value

Returns:

An AppendPropertyOperation object

Return type:

AppendPropertyOperation

static update_property(property_name, view_properties, instruction)[source]

Create an operation to update an existing property.

Parameters:

  • property_name (str) – Name of the property to update

  • view_properties (List[str]) – List of property names to use as context for the transformation

  • instruction (str) – Instruction for how to update the property value

Returns:

An UpdatePropertyOperation object

Return type:

UpdatePropertyOperation

class weaviate_agents.classes.Persona(*, persona_id, properties)[source]

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.

Parameters:

  • persona_id (UUID)

  • properties (Dict[str, Any])

persona_id: UUID
properties: Dict[str, Any]
model_config = {}

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

class weaviate_agents.classes.PersonaInteraction(*, persona_id, item_id, weight, replace_previous_interactions=False, created_at=None)[source]

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.

Parameters:

  • persona_id (UUID)

  • item_id (UUID)

  • weight (float)

  • replace_previous_interactions (bool)

  • created_at (datetime | None)

persona_id: UUID
item_id: UUID
weight: float
replace_previous_interactions: bool
created_at: datetime | None
model_config = {}

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

class weaviate_agents.classes.PersonaInteractionResponse(*, uuid, weight, createdAt)[source]

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.

Parameters:

  • uuid (UUID)

  • weight (float)

  • createdAt (str)

item_id: UUID
weight: float
created_at: str
model_config = {}

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

class weaviate_agents.classes.PersonalizationAgentGetObjectsResponse(*, objects, ranking_rationale=None, usage)[source]

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.

Parameters:
objects: list[PersonalizedObject]
ranking_rationale: str | None
usage: Usage
model_config = {}

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

class weaviate_agents.classes.PersonalizedObject(*, uuid, original_rank, personalized_rank, properties)[source]

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.

Parameters:

  • uuid (UUID)

  • original_rank (int)

  • personalized_rank (int | None)

  • properties (Dict[str, Any])

uuid: UUID
original_rank: int
personalized_rank: int | None
properties: Dict[str, Any]
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.

model_config = {}

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

class weaviate_agents.classes.PersonalizedQueryResponse(*, objects, usage)[source]

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.

Parameters:
usage: Usage
model_config = {}

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

class weaviate_agents.classes.BooleanArrayPropertyFilter(*, filter_type=KnownFilterType.BOOLEAN_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter boolean-array properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.BOOLEAN_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[bool])

filter_type: Literal[KnownFilterType.BOOLEAN_ARRAY]
operator: ComparisonOperator
value: list[bool]
model_config = {}

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

class weaviate_agents.classes.DateArrayPropertyFilter(*, filter_type=KnownFilterType.DATE_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter datetime properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.DATE_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[str])

filter_type: Literal[KnownFilterType.DATE_ARRAY]
operator: ComparisonOperator
value: list[str]
model_config = {}

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

class weaviate_agents.classes.DateMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
MAX = 'MAXIMUM'
MEDIAN = 'MEDIAN'
MIN = 'MINIMUM'
MODE = 'MODE'
class weaviate_agents.classes.DatePropertyAggregation(*, aggregation_type=KnownAggregationType.DATE, property_name, metrics)[source]

Bases: KnownPropertyAggregationBase

Aggregate datetime properties using statistical functions.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.DATE])

  • property_name (str)

  • metrics (DateMetrics)

aggregation_type: Literal[KnownAggregationType.DATE]
metrics: DateMetrics
model_config = {}

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

class weaviate_agents.classes.DatePropertyFilter(*, filter_type=KnownFilterType.DATE, property_name, value)[source]

Bases: KnownPropertyFilterBase

Filter datetime properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.DATE])

  • property_name (str)

  • value (DateExact | DateRangeFrom | DateRangeTo | DateRangeBetween)

filter_type: Literal[KnownFilterType.DATE]
value: DateExact | DateRangeFrom | DateRangeTo | DateRangeBetween
model_config = {}

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

class weaviate_agents.classes.IntegerArrayPropertyFilter(*, filter_type=KnownFilterType.INTEGER_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter numeric-array properties using comparison operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.INTEGER_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[float])

filter_type: Literal[KnownFilterType.INTEGER_ARRAY]
operator: ComparisonOperator
value: list[float]
model_config = {}

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

class weaviate_agents.classes.GeoPropertyFilter(*, filter_type=KnownFilterType.GEO, property_name, latitude, longitude, max_distance_meters)[source]

Bases: KnownPropertyFilterBase

Filter geo-coordinates properties.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.GEO])

  • property_name (str)

  • latitude (float)

  • longitude (float)

  • max_distance_meters (float)

filter_type: Literal[KnownFilterType.GEO]
latitude: float
longitude: float
max_distance_meters: float
model_config = {}

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

class weaviate_agents.classes.TextArrayPropertyFilter(*, filter_type=KnownFilterType.TEXT_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter text-array properties using equality or LIKE operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.TEXT_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[str])

filter_type: Literal[KnownFilterType.TEXT_ARRAY]
operator: ComparisonOperator
value: list[str]
model_config = {}

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

class weaviate_agents.classes.UnknownPropertyAggregation(*, aggregation_type, **extra_data)[source]

Bases: BaseModel

Catch-all aggregation for unknown aggregation types, to preserve future back-compatibility.

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.

Parameters:

  • aggregation_type (None)

  • extra_data (Any)

model_config = {'extra': 'allow'}

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

aggregation_type: None
classmethod ensure_filter_type_unknown(value)[source]
Parameters:

value (Any)

Return type:

None

model_post_init(context)[source]

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Parameters:

context (Any)

Return type:

None

class weaviate_agents.classes.UnknownPropertyFilter(*, filter_type, **extra_data)[source]

Bases: BaseModel

Catch-all filter for unknown filter types, to preserve future back-compatibility.

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.

Parameters:

  • filter_type (None)

  • extra_data (Any)

model_config = {'extra': 'allow'}

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

filter_type: None
classmethod ensure_filter_type_unknown(value)[source]
Parameters:

value (Any)

Return type:

None

model_post_init(context)[source]

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Parameters:

context (Any)

Return type:

None

class weaviate_agents.classes.ProgressDetails[source]

Bases: TypedDict

queries: list[QueryWithCollection]
class weaviate_agents.classes.ProgressMessage(*, output_type='progress_message', stage, message, details={})[source]

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.

Parameters:

  • output_type (Literal['progress_message'])

  • stage (str)

  • message (str)

  • details (ProgressDetails)

output_type: Literal['progress_message']
stage: str
message: str
details: ProgressDetails
model_config = {}

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

class weaviate_agents.classes.QueryWithCollection[source]

Bases: TypedDict

query: str
collection: str
class weaviate_agents.classes.StreamedTokens(*, output_type='streamed_tokens', delta)[source]

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.

Parameters:

  • output_type (Literal['streamed_tokens'])

  • delta (str)

output_type: Literal['streamed_tokens']
delta: str
model_config = {}

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

class weaviate_agents.classes.StreamedThoughts(*, output_type='streamed_thoughts', delta)[source]

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.

Parameters:

  • output_type (Literal['streamed_thoughts'])

  • delta (str)

output_type: Literal['streamed_thoughts']
delta: str
model_config = {}

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

class weaviate_agents.classes.IsNullPropertyFilter(*, filter_type=KnownFilterType.IS_NULL, property_name, is_null)[source]

Bases: KnownPropertyFilterBase

Filter by property null state.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.IS_NULL])

  • property_name (str)

  • is_null (bool)

filter_type: Literal[KnownFilterType.IS_NULL]
is_null: bool
model_config = {}

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

class weaviate_agents.classes.SearchModeResponseBase(*, searches=None, usage, total_time, search_results)[source]

Bases: BaseModel, ABC, Generic[SearcherT]

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.

Parameters:
searches: list[QueryResultWithCollectionNormalized] | None
usage: ModelUnitUsage
total_time: float
search_results: QueryReturn
abstractmethod next(limit=20, offset=0)[source]
Parameters:

  • self (SearchModeResponseT)

  • limit (int)

  • offset (int)

Return type:

SearchModeResponseT | Coroutine[Any, Any, SearchModeResponseT]

model_config = {}

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

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

  • self (BaseModel) – The BaseModel instance.

  • context (Any) – The context.

Return type:

None

class weaviate_agents.classes.ChatMessage[source]

Bases: TypedDict

role: Literal['user', 'assistant']
content: str
class weaviate_agents.classes.AskModeResponse(*, output_type='final_state', searches, aggregations, usage, total_time, is_partial_answer, missing_information, final_answer, sources)[source]

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.

Parameters:
output_type: Literal['final_state']
searches: list[QueryResultWithCollectionNormalized]
aggregations: list[AggregationResultWithCollectionNormalized]
usage: ModelUnitUsage
total_time: float
is_partial_answer: bool | None
missing_information: list[str] | None
final_answer: str
sources: list[Source] | None
display()[source]

Display a pretty-printed summary of the AskModeResponse object.

Return type:

None

model_config = {}

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

class weaviate_agents.classes.ResearchModeResponse(*, output_type='final_state', final_answer, usage, queries, total_time)[source]

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.

Parameters:
output_type: Literal['final_state']
final_answer: str
usage: ModelUnitUsage
queries: list[AskModeResponse]
total_time: float
model_config = {}

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

class weaviate_agents.classes.ModelUnitUsage(*, model_units, usage_in_plan, remaining_plan_requests)[source]

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.

Parameters:

  • model_units (int)

  • usage_in_plan (bool)

  • remaining_plan_requests (int)

model_units: int
usage_in_plan: bool
remaining_plan_requests: int
model_config = {}

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

class weaviate_agents.classes.FilterAndOr(*, combine, filters)[source]

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.

Parameters:
combine: Literal['AND', 'OR']
filters: list[PropertyFilter | FilterAndOr]
model_config = {}

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

class weaviate_agents.classes.QueryResultWithCollectionNormalized(*, query, filters, collection, sort_property=None, uuid_value=None)[source]

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.

Parameters:
query: str | None
filters: PropertyFilter | FilterAndOr | None
collection: str
sort_property: QuerySort | None
uuid_value: UUID | None
model_config = {}

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

class weaviate_agents.classes.AggregationResultWithCollectionNormalized(*, groupby_property, aggregation, filters, collection)[source]

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.

Parameters:
groupby_property: str | None
aggregation: PropertyAggregation
filters: PropertyFilter | FilterAndOr | None
collection: str
model_config = {}

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

class weaviate_agents.classes.QuerySort(*, property_name, order, tie_break)[source]

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.

Parameters:

  • property_name (str)

  • order (Literal['ascending', 'descending'])

  • tie_break (QuerySort | None)

property_name: str
order: Literal['ascending', 'descending']
tie_break: QuerySort | None
model_config = {}

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

class weaviate_agents.classes.UUIDPropertyFilter(*, filter_type=KnownFilterType.UUID, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter UUID properties.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.UUID])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (UUID)

filter_type: Literal[KnownFilterType.UUID]
property_name: str
operator: ComparisonOperator
value: UUID
model_config = {}

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

class weaviate_agents.classes.UUIDArrayPropertyFilter(*, filter_type=KnownFilterType.UUID_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter UUID array properties.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.UUID_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[UUID])

filter_type: Literal[KnownFilterType.UUID_ARRAY]
property_name: str
operator: ComparisonOperator
value: list[UUID]
model_config = {}

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

Subpackages

weaviate_agents.classes.personalization

class weaviate_agents.classes.personalization.Persona(*, persona_id, properties)[source]

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.

Parameters:

  • persona_id (UUID)

  • properties (Dict[str, Any])

persona_id: UUID
properties: Dict[str, Any]
model_config = {}

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

class weaviate_agents.classes.personalization.PersonaInteraction(*, persona_id, item_id, weight, replace_previous_interactions=False, created_at=None)[source]

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.

Parameters:

  • persona_id (UUID)

  • item_id (UUID)

  • weight (float)

  • replace_previous_interactions (bool)

  • created_at (datetime | None)

persona_id: UUID
item_id: UUID
weight: float
replace_previous_interactions: bool
created_at: datetime | None
model_config = {}

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

class weaviate_agents.classes.personalization.PersonaInteractionResponse(*, uuid, weight, createdAt)[source]

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.

Parameters:

  • uuid (UUID)

  • weight (float)

  • createdAt (str)

item_id: UUID
weight: float
created_at: str
model_config = {}

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

class weaviate_agents.classes.personalization.PersonalizationAgentGetObjectsResponse(*, objects, ranking_rationale=None, usage)[source]

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.

Parameters:
objects: list[PersonalizedObject]
ranking_rationale: str | None
usage: Usage
model_config = {}

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

class weaviate_agents.classes.personalization.PersonalizedObject(*, uuid, original_rank, personalized_rank, properties)[source]

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.

Parameters:

  • uuid (UUID)

  • original_rank (int)

  • personalized_rank (int | None)

  • properties (Dict[str, Any])

uuid: UUID
original_rank: int
personalized_rank: int | None
properties: Dict[str, Any]
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.

model_config = {}

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

class weaviate_agents.classes.personalization.PersonalizedQueryResponse(*, objects, usage)[source]

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.

Parameters:
usage: Usage
model_config = {}

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

class weaviate_agents.classes.personalization.Usage(*, requests=0, request_tokens=None, response_tokens=None, total_tokens=None, details=None)[source]

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.

Parameters:

  • requests (int | str)

  • request_tokens (int | str | None)

  • response_tokens (int | str | None)

  • total_tokens (int | str | None)

  • details (Dict[str, int] | Dict[str, str] | None)

requests: int | str
request_tokens: int | str | None
response_tokens: int | str | None
total_tokens: int | str | None
details: Dict[str, int] | Dict[str, str] | None
model_config = {}

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

weaviate_agents.classes.query

class weaviate_agents.classes.query.QueryAgentCollectionConfig(*, name, tenant=None, view_properties=None, target_vector=None, additional_filters=None)[source]

Bases: BaseModel

A collection configuration for the QueryAgent.

Parameters:

  • name (str)

  • tenant (str | None)

  • view_properties (list[str] | None)

  • target_vector (str | list[str] | None)

  • additional_filters (Annotated[_Filters, PlainSerializer(func=~weaviate_agents.serialise.serialise_filter, return_type=PydanticUndefined, when_used=always)] | None)

name

The name of the collection to query.

Type:

str

tenant

Tenant name for collections with multi-tenancy enabled.

Type:

str | None

view_properties

Optional list of property names the agent has the ability to view for this specific collection.

Type:

list[str] | None

target_vector

Optional target vector name(s) for collections with named vectors. Can be a single vector name or a list of vector names.

Type:

str | list[str] | None

additional_filters

Optional filters to apply when the query is executed, in addition to filters selected by the Query Agent (i.e., there are AND combined).

Type:

Annotated[weaviate.collections.classes.filters._Filters, pydantic.functional_serializers.PlainSerializer(func=weaviate_agents.serialise.serialise_filter, return_type=PydanticUndefined, when_used=always)] | None

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 = {'arbitrary_types_allowed': True}

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

name: str
tenant: str | None
view_properties: list[str] | None
target_vector: str | list[str] | None
additional_filters: Annotated[_Filters, PlainSerializer(func=serialise_filter, return_type=PydanticUndefined, when_used=always)] | None
class weaviate_agents.classes.query.QueryAgentResponse(*, output_type='final_state', original_query, collection_names, searches, aggregations, usage, total_time, is_partial_answer, missing_information, final_answer, sources)[source]

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.

Parameters:
output_type: Literal['final_state']
original_query: str
collection_names: list[str]
searches: list[list[QueryResultWithCollection]]
aggregations: list[list[AggregationResultWithCollection]]
usage: Usage
total_time: float
is_partial_answer: bool
missing_information: list[str]
final_answer: str
sources: list[Source]
display()[source]

Display a pretty-printed summary of the QueryAgentResponse object.

Return type:

None

model_config = {}

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

class weaviate_agents.classes.query.Source(*, object_id, collection)[source]

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.

Parameters:

  • object_id (str)

  • collection (str)

object_id: str
collection: str
model_config = {}

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

class weaviate_agents.classes.query.ComparisonOperator(*values)[source]

Bases: str, Enum

EQUALS = '='
LESS_THAN = '<'
GREATER_THAN = '>'
LESS_EQUAL = '<='
GREATER_EQUAL = '>='
NOT_EQUALS = '!='
LIKE = 'LIKE'
CONTAINS_ANY = 'contains_any'
CONTAINS_ALL = 'contains_all'
class weaviate_agents.classes.query.IntegerPropertyFilter(*, filter_type=KnownFilterType.INTEGER, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter numeric properties using comparison operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.INTEGER])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (float)

filter_type: Literal[KnownFilterType.INTEGER]
operator: ComparisonOperator
value: float
model_config = {}

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

class weaviate_agents.classes.query.TextPropertyFilter(*, filter_type=KnownFilterType.TEXT, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter text properties using equality or LIKE operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.TEXT])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (str)

filter_type: Literal[KnownFilterType.TEXT]
operator: ComparisonOperator
value: str
model_config = {}

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

class weaviate_agents.classes.query.BooleanPropertyFilter(*, filter_type=KnownFilterType.BOOLEAN, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter boolean properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.BOOLEAN])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (bool)

filter_type: Literal[KnownFilterType.BOOLEAN]
operator: ComparisonOperator
value: bool
model_config = {}

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

class weaviate_agents.classes.query.UUIDPropertyFilter(*, filter_type=KnownFilterType.UUID, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter UUID properties.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.UUID])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (UUID)

filter_type: Literal[KnownFilterType.UUID]
property_name: str
operator: ComparisonOperator
value: UUID
model_config = {}

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

class weaviate_agents.classes.query.UUIDArrayPropertyFilter(*, filter_type=KnownFilterType.UUID_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter UUID array properties.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.UUID_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[UUID])

filter_type: Literal[KnownFilterType.UUID_ARRAY]
property_name: str
operator: ComparisonOperator
value: list[UUID]
model_config = {}

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

class weaviate_agents.classes.query.QueryResult(*, queries, filters=[], filter_operators)[source]

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.

Parameters:
queries: list[str | None]
filters: list[list[PropertyFilter]]
filter_operators: Literal['AND', 'OR']
model_config = {}

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

class weaviate_agents.classes.query.NumericMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
MAX = 'MAXIMUM'
MEAN = 'MEAN'
MEDIAN = 'MEDIAN'
MIN = 'MINIMUM'
MODE = 'MODE'
SUM = 'SUM'
TYPE = 'TYPE'
class weaviate_agents.classes.query.TextMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
TYPE = 'TYPE'
TOP_OCCURRENCES = 'TOP_OCCURRENCES'
class weaviate_agents.classes.query.BooleanMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
TYPE = 'TYPE'
TOTAL_TRUE = 'TOTAL_TRUE'
TOTAL_FALSE = 'TOTAL_FALSE'
PERCENTAGE_TRUE = 'PERCENTAGE_TRUE'
PERCENTAGE_FALSE = 'PERCENTAGE_FALSE'
class weaviate_agents.classes.query.IntegerPropertyAggregation(*, aggregation_type=KnownAggregationType.INTEGER, property_name, metrics)[source]

Bases: KnownPropertyAggregationBase

Aggregate numeric properties using statistical functions.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.INTEGER])

  • property_name (str)

  • metrics (NumericMetrics)

aggregation_type: Literal[KnownAggregationType.INTEGER]
metrics: NumericMetrics
model_config = {}

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

class weaviate_agents.classes.query.TextPropertyAggregation(*, aggregation_type=KnownAggregationType.TEXT, property_name, metrics, top_occurrences_limit=None)[source]

Bases: KnownPropertyAggregationBase

Aggregate text properties using frequency analysis.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.TEXT])

  • property_name (str)

  • metrics (TextMetrics)

  • top_occurrences_limit (int | None)

aggregation_type: Literal[KnownAggregationType.TEXT]
metrics: TextMetrics
top_occurrences_limit: int | None
model_config = {}

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

class weaviate_agents.classes.query.BooleanPropertyAggregation(*, aggregation_type=KnownAggregationType.BOOLEAN, property_name, metrics)[source]

Bases: KnownPropertyAggregationBase

Aggregate boolean properties using statistical functions.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.BOOLEAN])

  • property_name (str)

  • metrics (BooleanMetrics)

aggregation_type: Literal[KnownAggregationType.BOOLEAN]
metrics: BooleanMetrics
model_config = {}

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

class weaviate_agents.classes.query.AggregationResult(*, search_query=None, groupby_property=None, aggregations, filters=[])[source]

Bases: BaseModel

The aggregations to be performed on a collection in a vector database.

They should be based on the original user query and can include multiple aggregations across different properties and metrics.

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.

Parameters:
search_query: str | None
groupby_property: str | None
aggregations: list[PropertyAggregation]
filters: list[PropertyFilter]
model_config = {}

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

class weaviate_agents.classes.query.Usage(*, requests=0, request_tokens=None, response_tokens=None, total_tokens=None, details=None)[source]

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.

Parameters:

  • requests (int | str)

  • request_tokens (int | str | None)

  • response_tokens (int | str | None)

  • total_tokens (int | str | None)

  • details (Dict[str, int] | Dict[str, str] | None)

requests: int | str
request_tokens: int | str | None
response_tokens: int | str | None
total_tokens: int | str | None
details: Dict[str, int] | Dict[str, str] | None
model_config = {}

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

class weaviate_agents.classes.query.AggregationResultWithCollection(*, search_query=None, groupby_property=None, aggregations, filters=[], collection)[source]

Bases: AggregationResult

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.

Parameters:
collection: str
model_config = {}

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

class weaviate_agents.classes.query.QueryResultWithCollection(*, queries, filters=[], filter_operators, collection)[source]

Bases: QueryResult

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.

Parameters:
collection: str
model_config = {}

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

class weaviate_agents.classes.query.BooleanArrayPropertyFilter(*, filter_type=KnownFilterType.BOOLEAN_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter boolean-array properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.BOOLEAN_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[bool])

filter_type: Literal[KnownFilterType.BOOLEAN_ARRAY]
operator: ComparisonOperator
value: list[bool]
model_config = {}

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

class weaviate_agents.classes.query.DateArrayPropertyFilter(*, filter_type=KnownFilterType.DATE_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter datetime properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.DATE_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[str])

filter_type: Literal[KnownFilterType.DATE_ARRAY]
operator: ComparisonOperator
value: list[str]
model_config = {}

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

class weaviate_agents.classes.query.DateMetrics(*values)[source]

Bases: str, Enum

COUNT = 'COUNT'
MAX = 'MAXIMUM'
MEDIAN = 'MEDIAN'
MIN = 'MINIMUM'
MODE = 'MODE'
class weaviate_agents.classes.query.DatePropertyAggregation(*, aggregation_type=KnownAggregationType.DATE, property_name, metrics)[source]

Bases: KnownPropertyAggregationBase

Aggregate datetime properties using statistical functions.

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.

Parameters:

  • aggregation_type (Literal[KnownAggregationType.DATE])

  • property_name (str)

  • metrics (DateMetrics)

aggregation_type: Literal[KnownAggregationType.DATE]
metrics: DateMetrics
model_config = {}

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

class weaviate_agents.classes.query.DatePropertyFilter(*, filter_type=KnownFilterType.DATE, property_name, value)[source]

Bases: KnownPropertyFilterBase

Filter datetime properties using equality operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.DATE])

  • property_name (str)

  • value (DateExact | DateRangeFrom | DateRangeTo | DateRangeBetween)

filter_type: Literal[KnownFilterType.DATE]
value: DateExact | DateRangeFrom | DateRangeTo | DateRangeBetween
model_config = {}

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

class weaviate_agents.classes.query.IntegerArrayPropertyFilter(*, filter_type=KnownFilterType.INTEGER_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter numeric-array properties using comparison operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.INTEGER_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[float])

filter_type: Literal[KnownFilterType.INTEGER_ARRAY]
operator: ComparisonOperator
value: list[float]
model_config = {}

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

class weaviate_agents.classes.query.TextArrayPropertyFilter(*, filter_type=KnownFilterType.TEXT_ARRAY, property_name, operator, value)[source]

Bases: KnownPropertyFilterBase

Filter text-array properties using equality or LIKE operators.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.TEXT_ARRAY])

  • property_name (str)

  • operator (ComparisonOperator)

  • value (list[str])

filter_type: Literal[KnownFilterType.TEXT_ARRAY]
operator: ComparisonOperator
value: list[str]
model_config = {}

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

class weaviate_agents.classes.query.GeoPropertyFilter(*, filter_type=KnownFilterType.GEO, property_name, latitude, longitude, max_distance_meters)[source]

Bases: KnownPropertyFilterBase

Filter geo-coordinates properties.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.GEO])

  • property_name (str)

  • latitude (float)

  • longitude (float)

  • max_distance_meters (float)

filter_type: Literal[KnownFilterType.GEO]
latitude: float
longitude: float
max_distance_meters: float
model_config = {}

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

class weaviate_agents.classes.query.UnknownPropertyAggregation(*, aggregation_type, **extra_data)[source]

Bases: BaseModel

Catch-all aggregation for unknown aggregation types, to preserve future back-compatibility.

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.

Parameters:

  • aggregation_type (None)

  • extra_data (Any)

model_config = {'extra': 'allow'}

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

aggregation_type: None
classmethod ensure_filter_type_unknown(value)[source]
Parameters:

value (Any)

Return type:

None

model_post_init(context)[source]

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Parameters:

context (Any)

Return type:

None

class weaviate_agents.classes.query.UnknownPropertyFilter(*, filter_type, **extra_data)[source]

Bases: BaseModel

Catch-all filter for unknown filter types, to preserve future back-compatibility.

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.

Parameters:

  • filter_type (None)

  • extra_data (Any)

model_config = {'extra': 'allow'}

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

filter_type: None
classmethod ensure_filter_type_unknown(value)[source]
Parameters:

value (Any)

Return type:

None

model_post_init(context)[source]

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Parameters:

context (Any)

Return type:

None

class weaviate_agents.classes.query.ProgressDetails[source]

Bases: TypedDict

queries: list[QueryWithCollection]
class weaviate_agents.classes.query.ProgressMessage(*, output_type='progress_message', stage, message, details={})[source]

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.

Parameters:

  • output_type (Literal['progress_message'])

  • stage (str)

  • message (str)

  • details (ProgressDetails)

output_type: Literal['progress_message']
stage: str
message: str
details: ProgressDetails
model_config = {}

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

class weaviate_agents.classes.query.QueryWithCollection[source]

Bases: TypedDict

query: str
collection: str
class weaviate_agents.classes.query.StreamedTokens(*, output_type='streamed_tokens', delta)[source]

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.

Parameters:

  • output_type (Literal['streamed_tokens'])

  • delta (str)

output_type: Literal['streamed_tokens']
delta: str
model_config = {}

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

class weaviate_agents.classes.query.IsNullPropertyFilter(*, filter_type=KnownFilterType.IS_NULL, property_name, is_null)[source]

Bases: KnownPropertyFilterBase

Filter by property null state.

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.

Parameters:

  • filter_type (Literal[KnownFilterType.IS_NULL])

  • property_name (str)

  • is_null (bool)

filter_type: Literal[KnownFilterType.IS_NULL]
is_null: bool
model_config = {}

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

class weaviate_agents.classes.query.SearchModeResponseBase(*, searches=None, usage, total_time, search_results)[source]

Bases: BaseModel, ABC, Generic[SearcherT]

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.

Parameters:
searches: list[QueryResultWithCollectionNormalized] | None
usage: ModelUnitUsage
total_time: float
search_results: QueryReturn
abstractmethod next(limit=20, offset=0)[source]
Parameters:

  • self (SearchModeResponseT)

  • limit (int)

  • offset (int)

Return type:

SearchModeResponseT | Coroutine[Any, Any, SearchModeResponseT]

model_config = {}

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

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

  • self (BaseModel) – The BaseModel instance.

  • context (Any) – The context.

Return type:

None

class weaviate_agents.classes.query.ChatMessage[source]

Bases: TypedDict

role: Literal['user', 'assistant']
content: str
class weaviate_agents.classes.query.AskModeResponse(*, output_type='final_state', searches, aggregations, usage, total_time, is_partial_answer, missing_information, final_answer, sources)[source]

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.

Parameters:
output_type: Literal['final_state']
searches: list[QueryResultWithCollectionNormalized]
aggregations: list[AggregationResultWithCollectionNormalized]
usage: ModelUnitUsage
total_time: float
is_partial_answer: bool | None
missing_information: list[str] | None
final_answer: str
sources: list[Source] | None
display()[source]

Display a pretty-printed summary of the AskModeResponse object.

Return type:

None

model_config = {}

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

class weaviate_agents.classes.query.ModelUnitUsage(*, model_units, usage_in_plan, remaining_plan_requests)[source]

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.

Parameters:

  • model_units (int)

  • usage_in_plan (bool)

  • remaining_plan_requests (int)

model_units: int
usage_in_plan: bool
remaining_plan_requests: int
model_config = {}

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

class weaviate_agents.classes.query.FilterAndOr(*, combine, filters)[source]

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.

Parameters:
combine: Literal['AND', 'OR']
filters: list[PropertyFilter | FilterAndOr]
model_config = {}

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

class weaviate_agents.classes.query.QueryResultWithCollectionNormalized(*, query, filters, collection, sort_property=None, uuid_value=None)[source]

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.

Parameters:
query: str | None
filters: PropertyFilter | FilterAndOr | None
collection: str
sort_property: QuerySort | None
uuid_value: UUID | None
model_config = {}

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

class weaviate_agents.classes.query.AggregationResultWithCollectionNormalized(*, groupby_property, aggregation, filters, collection)[source]

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.

Parameters:
groupby_property: str | None
aggregation: PropertyAggregation
filters: PropertyFilter | FilterAndOr | None
collection: str
model_config = {}

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

class weaviate_agents.classes.query.QuerySort(*, property_name, order, tie_break)[source]

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.

Parameters:

  • property_name (str)

  • order (Literal['ascending', 'descending'])

  • tie_break (QuerySort | None)

property_name: str
order: Literal['ascending', 'descending']
tie_break: QuerySort | None
model_config = {}

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

class weaviate_agents.classes.query.ResearchModeResponse(*, output_type='final_state', final_answer, usage, queries, total_time)[source]

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.

Parameters:
output_type: Literal['final_state']
final_answer: str
usage: ModelUnitUsage
queries: list[AskModeResponse]
total_time: float
model_config = {}

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

class weaviate_agents.classes.query.StreamedThoughts(*, output_type='streamed_thoughts', delta)[source]

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.

Parameters:

  • output_type (Literal['streamed_thoughts'])

  • delta (str)

output_type: Literal['streamed_thoughts']
delta: str
model_config = {}

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

weaviate_agents.classes.transformation

class weaviate_agents.classes.transformation.OperationType(*values)[source]

Bases: str, Enum

Types of operations that can be performed on properties.

APPEND = 'append'
UPDATE = 'update'
class weaviate_agents.classes.transformation.OperationStep(*, property_name, view_properties, instruction, operation_type)[source]

Bases: BaseModel

Base model for a transformation operation step.

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.

Parameters:

  • property_name (str)

  • view_properties (List[str])

  • instruction (str)

  • operation_type (OperationType)

property_name: str
view_properties: List[str]
instruction: str
operation_type: OperationType
model_config = {}

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

class weaviate_agents.classes.transformation.AppendPropertyOperation(*, property_name, view_properties, instruction, operation_type=OperationType.APPEND, data_type)[source]

Bases: OperationStep

Operation to append a new property.

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.

Parameters:

  • property_name (str)

  • view_properties (List[str])

  • instruction (str)

  • operation_type (OperationType)

  • data_type (DataType)

data_type: DataType
operation_type: OperationType
model_config = {}

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

class weaviate_agents.classes.transformation.UpdatePropertyOperation(*, property_name, view_properties, instruction, operation_type=OperationType.UPDATE)[source]

Bases: OperationStep

Operation to update an existing property.

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.

Parameters:

  • property_name (str)

  • view_properties (List[str])

  • instruction (str)

  • operation_type (OperationType)

operation_type: OperationType
model_config = {}

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

class weaviate_agents.classes.transformation.DependentOperationStep(operation, depends_on=None)[source]

Bases: BaseModel

A wrapper for operation steps that have dependencies on other operations.

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.

Parameters:
operation: OperationStep
depends_on: List[OperationStep] | None
model_config = {}

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

class weaviate_agents.classes.transformation.TransformationResponse(*, workflow_id)[source]

Bases: BaseModel

Response from a transformation operation.

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.

Parameters:

workflow_id (str)

workflow_id: str
model_config = {}

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

class weaviate_agents.classes.transformation.Operations[source]

Bases: object

Factory class for creating transformation operations.

static append_property(property_name, data_type, view_properties, instruction)[source]

Create an operation to append a new property.

Parameters:

  • property_name (str) – Name of the new property to append

  • data_type (DataType) – Data type of the new property

  • view_properties (List[str]) – List of property names to use as context for the transformation

  • instruction (str) – Instruction for how to generate the new property value

Returns:

An AppendPropertyOperation object

Return type:

AppendPropertyOperation

static update_property(property_name, view_properties, instruction)[source]

Create an operation to update an existing property.

Parameters:

  • property_name (str) – Name of the property to update

  • view_properties (List[str]) – List of property names to use as context for the transformation

  • instruction (str) – Instruction for how to update the property value

Returns:

An UpdatePropertyOperation object

Return type:

UpdatePropertyOperation