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)