haive.agents.memory.core.classifier
===================================

.. py:module:: haive.agents.memory.core.classifier

.. autoapi-nested-parse::

   Memory classification system using LLM-based analysis.

   This module provides intelligent classification of memories into types,
   importance scoring, and metadata extraction using language models.



Classes
-------

.. autoapisummary::

   haive.agents.memory.core.classifier.MemoryClassifier
   haive.agents.memory.core.classifier.MemoryClassifierConfig


Module Contents
---------------

.. py:class:: MemoryClassifier(config = None)

   LLM-based memory classifier for automatic memory type detection and metadata extraction.

   This classifier analyzes memory content to:
   - Determine memory types (semantic, episodic, procedural, etc.)
   - Calculate importance scores
   - Extract entities, topics, and sentiment
   - Provide classification reasoning

   Initialize memory classifier with configuration.


   .. py:method:: batch_classify(contents, contexts = None)

      Classify multiple memories in batch for efficiency.

      :param contents: List of memory contents to classify
      :param contexts: Optional list of contexts for each memory

      :returns: List of MemoryClassificationResult for each content



   .. py:method:: classify_memory(content, user_context = None, conversation_context = None)

      Classify a single memory content into types and extract metadata.

      :param content: Memory content to classify
      :param user_context: Optional user context for classification
      :param conversation_context: Optional conversation context

      :returns: MemoryClassificationResult with types, importance, and metadata



   .. py:method:: classify_query_intent(query)

      Analyze user query to determine memory retrieval intent.

      :param query: User query to analyze

      :returns: MemoryQueryIntent with retrieval strategy and parameters



   .. py:method:: create_memory_entry(content, user_context = None, conversation_context = None, namespace = None)

      Create a complete memory entry with automatic classification.

      :param content: Memory content
      :param user_context: Optional user context
      :param conversation_context: Optional conversation context
      :param namespace: Optional memory namespace

      :returns: MemoryEntry with full classification and metadata



.. py:class:: MemoryClassifierConfig(/, **data)

   Bases: :py:obj:`pydantic.BaseModel`


   Configuration for memory classification system.

   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.