Update AI_core.py
Browse files- AI_core.py +5 -6
AI_core.py
CHANGED
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@@ -2,8 +2,7 @@ import os
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import json
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from typing import Optional
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from components.ethics import EthicalAIGovernance
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from sentiment_analysis import EnhancedSentimentAnalyzer
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from elements import Element # You may have multiple Element types
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from self_improving_ai import SelfImprovingAI
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@@ -19,7 +18,7 @@ from quantum_spiderweb import QuantumSpiderweb
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class AICore:
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def __init__(self, config_path: str = "Codetteconfig.json"):
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self.config = self.
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self.memory = CognitionCocooner()
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self.ethics = EthicalAIGovernance()
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self.sentiment = EnhancedSentimentAnalyzer()
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@@ -33,13 +32,13 @@ class AICore:
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self.self_improving = SelfImprovingAI()
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self.elements = [] # To be filled with Element() instances
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def
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if os.path.exists(path):
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with open(path, 'r') as f:
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return json.load(f)
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return {}
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def
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# Placeholder example objective function
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def objective_fn(vec):
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return sum(x**2 for x in vec)
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@@ -63,7 +62,7 @@ class AICore:
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if __name__ == "__main__":
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codette =
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sample = "What does it mean to be sentient?"
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response = codette.process_input(sample)
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print(response)
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import json
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from typing import Optional
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from components.ethics import EthicalAIGovernance
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from sentiment_analysis import EnhancedSentimentAnalyzer
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from elements import Element # You may have multiple Element types
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from self_improving_ai import SelfImprovingAI
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class AICore:
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def __init__(self, config_path: str = "Codetteconfig.json"):
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self.config = self.load_config(config_path)
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self.memory = CognitionCocooner()
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self.ethics = EthicalAIGovernance()
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self.sentiment = EnhancedSentimentAnalyzer()
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self.self_improving = SelfImprovingAI()
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self.elements = [] # To be filled with Element() instances
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def load_config(self, path: str) -> dict:
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if os.path.exists(path):
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with open(path, 'r') as f:
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return json.load(f)
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return {}
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def optimizer(self):
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# Placeholder example objective function
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def objective_fn(vec):
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return sum(x**2 for x in vec)
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if __name__ == "__main__":
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codette = AI_Core()
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sample = "What does it mean to be sentient?"
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response = codette.process_input(sample)
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print(response)
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