CortexFlowManager
================

The CortexFlowManager is the main entry point for the CortexFlow library. It manages the multi-tier memory system and provides methods for adding messages, generating responses, and managing knowledge.

.. autoclass:: cortexflow.CortexFlowManager
   :members:
   :undoc-members:
   :show-inheritance:

Core Methods
----------

.. automethod:: cortexflow.CortexFlowManager.__init__
.. automethod:: cortexflow.CortexFlowManager.add_message
.. automethod:: cortexflow.CortexFlowManager.generate_response
.. automethod:: cortexflow.CortexFlowManager.remember_knowledge
.. automethod:: cortexflow.CortexFlowManager.close

Example Usage
-----------

.. code-block:: python

    from cortexflow import CortexFlowManager, CortexFlowConfig, MemoryConfig, LLMConfig

    # Create a configuration using nested config
    config = CortexFlowConfig(
        memory=MemoryConfig(
            active_token_limit=2000,
            working_token_limit=4000,
            archive_token_limit=6000,
        ),
        llm=LLMConfig(default_model="llama3"),
    )

    # Initialize the manager
    manager = CortexFlowManager(config)

    # Add messages
    manager.add_message("system", "You are a helpful assistant.")
    manager.add_message("user", "What's the capital of France?")

    # Generate a response
    response = manager.generate_response()
    print(f"Assistant: {response}")

    # Close the manager when done
    manager.close()