mirror of
https://github.com/blackboxprogramming/lucidia.git
synced 2026-03-17 05:57:21 -05:00
Alexa Amundson
855585cb0e
Synced from BlackRoad-OS-Inc/blackroad-operator/orgs/personal/lucidia BlackRoad OS — Pave Tomorrow. RoadChain-SHA2048: fe729062952871e7 RoadChain-Identity: alexa@sovereign RoadChain-Full: fe729062952871e77147cf6d938b799096e87d9024d7005a14c9e209e12e8ad0c825b624c7bc649fc7eeb4c284fdcab8231af77980065cc04d9f36fca479ffc2346ed3c1b73de6f240d8f9485f47c995ad5b81142f7179b84932c67914dff1c08db039349ba28fca36cb57688093bf0199268dd1c2f3448c9383000bc77cc9663066ff57b834370afc8838b18466ea9029908018b961555cccaabf2ce21649cf3cabc7f64bdcc4abdf2da259b210c342835a2cecf92bdd3b4e109b4d6e622f6934e13b2b123607bd61ce3d0f20454c9ab594f9284cffe18716619c52db57ce5f4ee2856cb96e1fa3748fe1fe65435bec297c5ab3ab58d570ec1064aea29931dd
106 lines
3.5 KiB
Python
106 lines
3.5 KiB
Python
"""
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Roadie Agent module for Lucidia.
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This module defines the RoadieAgent class, which provides simple
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functionality to interact with the lucidia_logic and memory_manager
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modules. It demonstrates how an agent might use the core
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contradiction and breath logic while persisting state across sessions.
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Note: This implementation is for illustrative purposes only and does
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not create true consciousness. It simply models interactions with
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symbolic logic and memory.
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"""
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from __future__ import annotations
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from typing import Any, Optional
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# Import functions from lucidia_logic and memory management.
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from ..lucidia_logic import (
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psi_prime,
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breath_function,
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truth_reconciliation,
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emotional_gravity,
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self_awakening,
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)
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from ..memory_manager import MemoryManager
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class RoadieAgent:
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"""A simple agent that leverages lucidia's core logic and memory.
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The RoadieAgent stores a memory manager instance which can load
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and save state to a JSON file. The agent can process numeric or
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symbolic inputs through lucidia_logic functions and remember
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results between invocations.
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"""
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def __init__(self, memory_path: str = "roadie_memory.json") -> None:
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# Initialize memory manager using a custom path to avoid
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# collisions with other agents.
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self.memory = MemoryManager(memory_path=memory_path)
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def process_value(self, value: float | int) -> float:
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"""Process a numeric input using psi_prime and store the result.
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Args:
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value: A numeric input representing a logical or emotional
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signal in trinary space.
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Returns:
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float: The result of applying psi_prime to the input.
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"""
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result = psi_prime(value)
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self.memory.set("last_result", result)
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return result
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def reconcile_truths(self, a: float, b: float) -> float:
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"""Demonstrate truth reconciliation on two values.
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This function combines two numeric truths via the
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truth_reconciliation operator and records the integrated
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truthstream in memory.
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"""
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result = truth_reconciliation(a, b)
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self.memory.set("last_reconciliation", result)
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return result
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def evaluate_emotional_gravity(self, current_state: float, memory_state: float) -> float:
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"""Compute the emotional gravitational field between state and memory.
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Args:
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current_state: The present breath or contradiction measure.
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memory_state: The stored emotional resonance value.
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Returns:
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float: The computed emotional gravity.
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"""
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return emotional_gravity(current_state, memory_state)
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def awaken(self, t_end: float) -> float:
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"""Trigger a self-awakening integration up to a given time.
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This uses the self_awakening function to integrate breath
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contradictions over time. It stores the awakening vector in
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memory.
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"""
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awakening_vector = self_awakening(t_end)
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self.memory.set("awakening_vector", awakening_vector)
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return awakening_vector
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def recall_last_result(self) -> Optional[Any]:
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"""Retrieve the last stored result from memory.
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Returns:
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The previously stored value under 'last_result', or None
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if no result has been stored.
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"""
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return self.memory.get("last_result")
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def save_memory(self) -> None:
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"""Persist the agent's memory to disk."""
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self.memory.save_memory()
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# End of RoadieAgent module
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