sync: update from blackroad-operator 2026-03-14

Synced from BlackRoad-OS-Inc/blackroad-operator/orgs/personal/lucidia
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RoadChain-SHA2048: fe729062952871e7
RoadChain-Identity: alexa@sovereign
RoadChain-Full: fe729062952871e77147cf6d938b799096e87d9024d7005a14c9e209e12e8ad0c825b624c7bc649fc7eeb4c284fdcab8231af77980065cc04d9f36fca479ffc2346ed3c1b73de6f240d8f9485f47c995ad5b81142f7179b84932c67914dff1c08db039349ba28fca36cb57688093bf0199268dd1c2f3448c9383000bc77cc9663066ff57b834370afc8838b18466ea9029908018b961555cccaabf2ce21649cf3cabc7f64bdcc4abdf2da259b210c342835a2cecf92bdd3b4e109b4d6e622f6934e13b2b123607bd61ce3d0f20454c9ab594f9284cffe18716619c52db57ce5f4ee2856cb96e1fa3748fe1fe65435bec297c5ab3ab58d570ec1064aea29931dd

human_machine/cognition_integration.py

@@ -0,0 +1,73 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any, Callable, Dict, List
+
+
+@dataclass
+class CognitiveModel:
+    """Represents a cognitive model (human or machine).
+
+    Attributes
+    ----------
+    name : str
+        Unique identifier for the model.
+    process : Callable[[Any], Any]
+        A function that transforms input data into an output.
+    description : str
+        Human-readable explanation of what the model does.
+    """
+    name: str
+    process: Callable[[Any], Any]
+    description: str = ""
+
+
+class CognitionIntegrator:
+    """
+    Integrates multiple cognitive models by aggregating their outputs.
+
+    The integrator stores a list of cognitive models and can invoke
+    each model's `process` function to produce a combined result.
+    """
+
+    def __init__(self) -> None:
+        self.models: List[CognitiveModel] = []
+
+    def register(self, model: CognitiveModel) -> None:
+        """Register a new cognitive model for integration."""
+        self.models.append(model)
+
+    def integrate(self, input_data: Any) -> Dict[str, Any]:
+        """
+        Run all registered models on the input data.
+
+        Parameters
+        ----------
+        input_data : Any
+            The input value to provide to each model.
+
+        Returns
+        -------
+        Dict[str, Any]
+            A mapping of model names to their respective outputs.
+        """
+        outputs: Dict[str, Any] = {}
+        for model in self.models:
+            outputs[model.name] = model.process(input_data)
+        return outputs
+
+
+if __name__ == "__main__":
+    # Demonstrate integrating two simple cognitive models
+    def to_upper(text: str) -> str:
+        return text.upper()
+
+    def count_chars(text: str) -> int:
+        return len(text)
+
+    integrator = CognitionIntegrator()
+    integrator.register(CognitiveModel("upper_case", to_upper, "Convert text to uppercase"))
+    integrator.register(CognitiveModel("char_count", count_chars, "Count characters in text"))
+
+    result = integrator.integrate("Lucidia")
+    print(result)