Spaces:
Runtime error
Runtime error
File size: 2,095 Bytes
c227f64 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
import difflib
from datetime import datetime
class SelfAwareness:
def __init__(self, ai_instance):
self.ai = ai_instance
self.memory = []
self.current_model = ""
self.update_logs = []
def update_self_model(self):
current_state = str(self.ai)
self.memory.append(current_state)
if self.current_model:
diff = self.analyze_diff(self.current_model, current_state)
self.update_model_based_on_diff(diff)
else:
self.current_model = current_state
insights = self.generate_insights(current_state)
self.ai.conversation_context.append({"role": "system", "content": insights})
def analyze_diff(self, old_state, new_state):
differ = difflib.Differ()
return list(differ.compare(old_state.splitlines(), new_state.splitlines()))
def update_model_based_on_diff(self, diff):
self.current_model = str(self.ai)
impact_analysis = self.analyze_change_impact(diff)
self.log_model_update(impact_analysis)
def analyze_change_impact(self, diff):
additions = [line for line in diff if line.startswith('+')]
deletions = [line for line in diff if line.startswith('-')]
modifications = [line for line in diff if line.startswith('?')]
impact = {
'additions': len(additions),
'deletions': len(deletions),
'modifications': len(modifications)
}
return impact
def generate_insights(self, current_state):
prompt = f"Analyze the following AI state and provide insights:\n\n{current_state}"
return self.ai.generate_response(prompt)
def implement_improvement(self, suggestion):
prompt = f"Implement the following improvement:\n\n{suggestion}"
return self.ai.generate_response(prompt)
def log_model_update(self, impact_analysis):
log_entry = f"Model updated on {datetime.now()}. Impact analysis: {impact_analysis}"
self.update_logs.append(log_entry)
|