mirror of
https://github.com/blackboxprogramming/lucidia.git
synced 2026-03-17 04:57:15 -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: 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
74 lines
2.0 KiB
Python
74 lines
2.0 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any, Callable, Dict, List
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@dataclass
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class CognitiveModel:
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"""Represents a cognitive model (human or machine).
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Attributes
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----------
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name : str
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Unique identifier for the model.
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process : Callable[[Any], Any]
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A function that transforms input data into an output.
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description : str
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Human-readable explanation of what the model does.
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"""
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name: str
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process: Callable[[Any], Any]
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description: str = ""
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class CognitionIntegrator:
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"""
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Integrates multiple cognitive models by aggregating their outputs.
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The integrator stores a list of cognitive models and can invoke
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each model's `process` function to produce a combined result.
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"""
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def __init__(self) -> None:
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self.models: List[CognitiveModel] = []
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def register(self, model: CognitiveModel) -> None:
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"""Register a new cognitive model for integration."""
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self.models.append(model)
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def integrate(self, input_data: Any) -> Dict[str, Any]:
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"""
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Run all registered models on the input data.
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Parameters
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----------
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input_data : Any
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The input value to provide to each model.
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Returns
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-------
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Dict[str, Any]
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A mapping of model names to their respective outputs.
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"""
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outputs: Dict[str, Any] = {}
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for model in self.models:
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outputs[model.name] = model.process(input_data)
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return outputs
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if __name__ == "__main__":
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# Demonstrate integrating two simple cognitive models
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def to_upper(text: str) -> str:
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return text.upper()
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def count_chars(text: str) -> int:
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return len(text)
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integrator = CognitionIntegrator()
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integrator.register(CognitiveModel("upper_case", to_upper, "Convert text to uppercase"))
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integrator.register(CognitiveModel("char_count", count_chars, "Count characters in text"))
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result = integrator.integrate("Lucidia")
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print(result)
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