memoryscope.core.worker.backend.get_observation_worker

class memoryscope.core.worker.backend.get_observation_worker.GetObservationWorker(embedding_model: str = '', generation_model: str = '', rank_model: str = '', **kwargs)

Bases: MemoryBaseWorker

A specialized worker class to generate the observations from the original chat histories.

FILE_PATH: str = '/home/runner/work/MemoryScope/MemoryScope/memoryscope/core/worker/backend/get_observation_worker.py'

OBS_STORE_KEY: str = 'new_obs_nodes'

add_observation(message: Message, time_infer: str, obs_content: str, keywords: str)

Builds a MemoryNode containing the observation details.

Parameters:

• message (Message) – The source message from which the observation is derived.

• time_infer (str) – The inferred time if available.

• obs_content (str) – The content of the observation.

• keywords (str) – Keywords associated with the observation.

Returns:

The constructed MemoryNode containing the observation.

Return type:

MemoryNode

filter_messages() → List[Message]

Filters the chat messages to only include those which not contain time-related keywords.

Returns:

A list of filtered messages that mention time.

Return type:

List[Message]

build_message(filter_messages: List[Message]) → List[Message]

Constructs a formatted message for observation based on input messages, incorporating system prompts, few-shot examples, and user queries.

Parameters:

filter_messages (List[Message]) – A list of messages filtered for observation processing.

Returns:

A list containing the constructed message ready for observation.

Return type:

List[Message]

name: str

workflow_context: Dict[str, Any]

memoryscope_context: MemoryscopeContext

raise_exception: bool

is_multi_thread: bool

thread_pool: ThreadPoolExecutor

enable_parallel: bool

kwargs: dict

continue_run: bool

async_task_list: list

thread_task_list: list

logger: Logger