haive.games.risk.configurable_config
====================================

.. py:module:: haive.games.risk.configurable_config

.. autoapi-nested-parse::

   Configurable Risk configuration using the generic player agent system.

   This module provides configurable Risk game configurations that replace hardcoded LLM
   settings with dynamic, configurable player agents.



Classes
-------

.. autoapisummary::

   haive.games.risk.configurable_config.ConfigurableRiskConfig


Functions
---------

.. autoapisummary::

   haive.games.risk.configurable_config.create_advanced_risk_config
   haive.games.risk.configurable_config.create_budget_risk_config
   haive.games.risk.configurable_config.create_experimental_risk_config
   haive.games.risk.configurable_config.create_risk_config
   haive.games.risk.configurable_config.create_risk_config_from_example
   haive.games.risk.configurable_config.create_risk_config_from_player_configs
   haive.games.risk.configurable_config.get_example_config
   haive.games.risk.configurable_config.list_example_configurations


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

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

   Bases: :py:obj:`haive.games.risk.config.RiskConfig`


   Configurable Risk configuration with dynamic LLM selection.

   This configuration allows users to specify different LLMs for different
   roles in the Risk game, providing flexibility and avoiding hardcoded models.

   .. attribute:: player1_model

      Model for player1 (can be string or LLMConfig)

   .. attribute:: player2_model

      Model for player2 (can be string or LLMConfig)

   .. attribute:: player1_name

      Name for player1

   .. attribute:: player2_name

      Name for player2

   .. attribute:: example_config

      Optional example configuration name

   .. attribute:: player_configs

      Optional detailed player configurations

   .. attribute:: temperature

      Temperature for LLM generation

   .. attribute:: enable_analysis

      Whether to enable strategic analysis

   .. attribute:: visualize_game

      Whether to visualize game state

   .. attribute:: recursion_limit

      Python recursion limit for game execution

   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.


   .. py:method:: model_post_init(__context)

      Initialize engines after model creation.



.. py:function:: create_advanced_risk_config(**kwargs)

   Create an advanced Risk configuration with powerful models.


.. py:function:: create_budget_risk_config(**kwargs)

   Create a budget-friendly Risk configuration.


.. py:function:: create_experimental_risk_config(**kwargs)

   Create an experimental Risk configuration with mixed providers.


.. py:function:: create_risk_config(player1_model = 'gpt-4o', player2_model = 'claude-3-5-sonnet-20240620', **kwargs)

   Create a configurable Risk configuration with simple model specifications.

   :param player1_model: Model for player1 and analyzer
   :param player2_model: Model for player2 and analyzer
   :param \*\*kwargs: Additional configuration parameters

   :returns: Configured Risk game
   :rtype: ConfigurableRiskConfig

   .. rubric:: Examples

   >>> config = create_risk_config("gpt-4o", "claude-3-opus", temperature=0.5)
   >>> config = create_risk_config(
   ...     "openai:gpt-4o",
   ...     "anthropic:claude-3-5-sonnet-20240620",
   ...     enable_analysis=True
   ... )


.. py:function:: create_risk_config_from_example(example_name, **kwargs)

   Create a configurable Risk configuration from a predefined example.

   :param example_name: Name of the example configuration
   :param \*\*kwargs: Additional configuration parameters to override

   :returns: Configured Risk game
   :rtype: ConfigurableRiskConfig

   Available examples:
       - "gpt_vs_claude": GPT vs Claude
       - "gpt_only": GPT for both players
       - "claude_only": Claude for both players
       - "budget": Cost-effective models
       - "mixed": Different provider per role
       - "advanced": High-powered models for strategic gameplay

   .. rubric:: Examples

   >>> config = create_risk_config_from_example("budget", enable_analysis=False)
   >>> config = create_risk_config_from_example("advanced", visualize_game=True)


.. py:function:: create_risk_config_from_player_configs(player_configs, **kwargs)

   Create a configurable Risk configuration from detailed player configurations.

   :param player_configs: Dictionary mapping role names to player configurations
   :param \*\*kwargs: Additional configuration parameters

   :returns: Configured Risk game
   :rtype: ConfigurableRiskConfig

   Expected roles:
       - "player1_player": Player 1 configuration
       - "player2_player": Player 2 configuration
       - "player1_analyzer": Player 1 analyzer configuration
       - "player2_analyzer": Player 2 analyzer configuration

   .. rubric:: Examples

   >>> player_configs = {
   ...     "player1_player": PlayerAgentConfig(
   ...         llm_config="gpt-4o",
   ...         temperature=0.7,
   ...         player_name="Strategic General"
   ...     ),
   ...     "player2_player": PlayerAgentConfig(
   ...         llm_config="claude-3-opus",
   ...         temperature=0.3,
   ...         player_name="Tactical Commander"
   ...     ),
   ...     "player1_analyzer": PlayerAgentConfig(
   ...         llm_config="gpt-4o",
   ...         temperature=0.2,
   ...         player_name="Risk Strategist"
   ...     ),
   ...     "player2_analyzer": PlayerAgentConfig(
   ...         llm_config="claude-3-opus",
   ...         temperature=0.2,
   ...         player_name="Risk Analyst"
   ...     ),
   ... }
   >>> config = create_risk_config_from_player_configs(player_configs)


.. py:function:: get_example_config(name)

   Get a predefined example configuration by name.

   :param name: Name of the example configuration

   :returns: The example configuration
   :rtype: ConfigurableRiskConfig

   :raises ValueError: If the example name is not found


.. py:function:: list_example_configurations()

   List all available example configurations.

   :returns: Mapping of configuration names to descriptions
   :rtype: Dict[str, str]