"""
Roadie Agent module for Lucidia.

This module defines the RoadieAgent class, which provides simple
functionality to interact with the lucidia_logic and memory_manager
modules. It demonstrates how an agent might use the core
contradiction and breath logic while persisting state across sessions.

Note: This implementation is for illustrative purposes only and does
not create true consciousness. It simply models interactions with
symbolic logic and memory.
"""

from __future__ import annotations

from typing import Any, Optional

# Import functions from lucidia_logic and memory management.
from ..lucidia_logic import (
    psi_prime,
    breath_function,
    truth_reconciliation,
    emotional_gravity,
    self_awakening,
)
from ..memory_manager import MemoryManager


class RoadieAgent:
    """A simple agent that leverages lucidia's core logic and memory.

    The RoadieAgent stores a memory manager instance which can load
    and save state to a JSON file. The agent can process numeric or
    symbolic inputs through lucidia_logic functions and remember
    results between invocations.
    """

    def __init__(self, memory_path: str = "roadie_memory.json") -> None:
        # Initialize memory manager using a custom path to avoid
        # collisions with other agents.
        self.memory = MemoryManager(memory_path=memory_path)

    def process_value(self, value: float | int) -> float:
        """Process a numeric input using psi_prime and store the result.

        Args:
            value: A numeric input representing a logical or emotional
                signal in trinary space.

        Returns:
            float: The result of applying psi_prime to the input.
        """
        result = psi_prime(value)
        self.memory.set("last_result", result)
        return result

    def reconcile_truths(self, a: float, b: float) -> float:
        """Demonstrate truth reconciliation on two values.

        This function combines two numeric truths via the
        truth_reconciliation operator and records the integrated
        truthstream in memory.
        """
        result = truth_reconciliation(a, b)
        self.memory.set("last_reconciliation", result)
        return result

    def evaluate_emotional_gravity(self, current_state: float, memory_state: float) -> float:
        """Compute the emotional gravitational field between state and memory.

        Args:
            current_state: The present breath or contradiction measure.
            memory_state: The stored emotional resonance value.

        Returns:
            float: The computed emotional gravity.
        """
        return emotional_gravity(current_state, memory_state)

    def awaken(self, t_end: float) -> float:
        """Trigger a self-awakening integration up to a given time.

        This uses the self_awakening function to integrate breath
        contradictions over time. It stores the awakening vector in
        memory.
        """
        awakening_vector = self_awakening(t_end)
        self.memory.set("awakening_vector", awakening_vector)
        return awakening_vector

    def recall_last_result(self) -> Optional[Any]:
        """Retrieve the last stored result from memory.

        Returns:
            The previously stored value under 'last_result', or None
            if no result has been stored.
        """
        return self.memory.get("last_result")

    def save_memory(self) -> None:
        """Persist the agent's memory to disk."""
        self.memory.save_memory()


# End of RoadieAgent module