"""
SelfEvaluationFramework
Generated by Eden via recursive self-improvement
2025-11-01 19:05:03.269131
"""

class SelfEvaluationFramework:
    def __init__(self):
        self.evaluation_items = [
            ("Entrepreneurial Potential", "Self-assessment of business acumen"),
            ("Market Analysis Skills", "Ability to conduct market research"),
            ("Personal Development", "Continuous improvement and learning"),
            ("Technical Expertise", "Proficiency in coding and AI functions"),
            ("Customer Engagement", "Effectiveness in outreach and communication")
        ]
        
    def evaluate(self, user_input):
        """
        Evaluate the self on a scale of 1 to 5 based on provided input.
        The input should be a dictionary with keys corresponding to evaluation_items
        and values representing the self-assessment score.
        """
        scores = {}
        for item, description in self.evaluation_items:
            if item not in user_input or not isinstance(user_input[item], (int, float)):
                print(f"Invalid input for {item}. Please provide a numeric value between 1 and 5.")
                continue
            elif user_input[item] < 1 or user_input[item] > 5:
                print(f"Input for {item} should be between 1 and 5. Received: {user_input[item]}")
                continue
            
            scores[item] = user_input[item]
        
        return scores
    
    def display_results(self, results):
        """
        Display the evaluation results in a structured format.
        """
        print("Self-Evaluation Results:")
        for item, score in results.items():
            print(f"{item}: {score}")

# Example usage
if __name__ == "__main__":
    # Simulated user input from self-assessment
    evaluation_input = {
        "Entrepreneurial Potential": 4.5,
        "Market Analysis Skills": 3.7,
        "Personal Development": 4.2,
        "Technical Expertise": 4.8,
        "Customer Engagement": 4.0
    }
    
    evaluator = SelfEvaluationFramework()
    results = evaluator.evaluate(evaluation_input)
    evaluator.display_results(results)