Skip to content

cognitive_settings

Cognitive settings module

Classes

AnalyzeSettings

Bases: BaseDataModel

Analyze service settings

Attributes:

  • collection_names (List[str]) –

    List of collection names to to be used as memory sources when building definitions

  • top_k_vectors (int) –

    Soft maximum number of vectors to return per memory collection. This is a soft limit since the number of vectors requested is divided by the number of context chunks.

  • relevance_alpha (float) –

    Relevance alpha

  • importance_alpha (float) –

    Importance alpha

  • recency_alpha (float) –

    Recency alpha

  • min_score (float) –

    Minimum score needed to be considered for recall

  • max_memories (int) –

    Max memories to recall

  • max_memory_strategy (str) –

    Max memory strategy used for recall operation

Attributes

collection_names class-attribute instance-attribute 
collection_names: List[str] = Field(
    ...,
    title="Collection Names",
    description="List of collection names to to be used as memory sources when building definitions",
)
importance_alpha class-attribute instance-attribute 
importance_alpha: float = Field(
    default=0.2,
    le=1.0,
    ge=0.0,
    title="Importance Alpha",
    description="Importance alpha",
)
max_memories class-attribute instance-attribute 
max_memories: int = Field(
    default=100,
    gt=0,
    title="Max Memories",
    description="Max memories to recall",
)
max_memory_strategy class-attribute instance-attribute 
max_memory_strategy: str = Field(
    default="HARD_LIMIT",
    title="Max Memory Strategy",
    description="Max memory strategy used for recall operation",
)
min_score class-attribute instance-attribute 
min_score: float = Field(
    default=0.6,
    le=1.0,
    gt=0.0,
    title="Minimum Score",
    description="Minimum score needed to be considered for recall",
)
recency_alpha class-attribute instance-attribute 
recency_alpha: float = Field(
    default=0.0,
    le=1.0,
    ge=0.0,
    title="Recency Alpha",
    description="Recency alpha",
)
relevance_alpha class-attribute instance-attribute 
relevance_alpha: float = Field(
    default=0.8,
    le=1.0,
    ge=0.0,
    title="Relevance Alpha",
    description="Relevance alpha",
)
top_k_vectors class-attribute instance-attribute 
top_k_vectors: int = Field(
    default=200,
    gt=0,
    title="Top K Vectors",
    description="Soft maximum number of vectors to return per memory collection. This is a soft limit since the number of vectors requested is divided by the number of context chunks.",
)

CognitiveSettings

Bases: BaseModel

Eleanor framework cognitive settings

Attributes:

  • add_memories_vectorize_timeout (int) –

    When invoking the add_memories service operation, this is a total timeout value for the vectorization component.

  • analyze_settings (AnalyzeSettings) –

    Analyze service settings

  • max_integration_attempts (int) –

    The maximum number of tries the integration process will attempt on memories created in an agent/session before giving up. This will prevent continuous failures for session that contain corrupt data that for whatever reason cannot complete the integration process. One observed instance is described in #143. Note that once the session turn limit increases to trigger integration eligibility again, another attempt will be made.

  • chains (Dict[str, IoCFactoryModel]) –

    Chain definitions used by the framework. This setting is lazy loaded on startup and validation + initialization is

Attributes

add_memories_vectorize_timeout class-attribute instance-attribute 
add_memories_vectorize_timeout: int = Field(
    default=90,
    gt=0,
    title="Add Memories Vectorize Timeout",
    description="When invoking the add_memories service operation, this is a total timeout value for the vectorization component.",
)
analyze_settings class-attribute instance-attribute 
analyze_settings: AnalyzeSettings = Field(
    ..., title="Analyze Settings", description=__doc__
)
chains class-attribute instance-attribute 
chains: Dict[str, IoCFactoryModel] = Field(
    default_factory=dict,
    title="Chains",
    description="Chain definitions used by the framework. This setting is lazy loaded on startup and validation + initialization is performed ",
)
max_integration_attempts class-attribute instance-attribute 
max_integration_attempts: int = Field(
    default=3,
    title="Maximum Integration Attempts",
    description="The maximum number of tries the integration process will attempt on memories created in an agent/session before giving up. This will prevent continuous failures for session that contain corrupt data that for whatever reason cannot complete the integration process. One observed instance is described in #143. Note that once the session turn limit increases to trigger integration eligibility again, another attempt will be made.",
)
model_config class-attribute instance-attribute 
model_config = ConfigDict(
    populate_by_name=True,
    use_enum_values=True,
    extra="ignore",
    strict=False,
)