"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-06 07:44:50.177356
"""

```python
from typing import List, Dict


class KnowledgeBase:
    def __init__(self):
        self.facts = []
        self.rules = []

    def add_fact(self, fact: str) -> None:
        """
        Adds a new fact to the knowledge base.
        
        :param fact: A string representing the fact
        """
        self.facts.append(fact)

    def add_rule(self, rule: str) -> None:
        """
        Adds a new rule to the knowledge base.
        
        :param rule: A string representing the rule in 'if ... then ...' format
        """
        self.rules.append(rule)


class ReasoningEngine:
    def __init__(self):
        self.knowledge_base = KnowledgeBase()
    
    def add_fact(self, fact: str) -> None:
        """Add a new fact to the knowledge base."""
        self.knowledge_base.add_fact(fact)
    
    def add_rule(self, rule: str) -> None:
        """Add a new rule to the knowledge base."""
        self.knowledge_base.add_rule(rule)
    
    def infer_conclusions(self) -> Dict[str, bool]:
        """
        Infers conclusions from the facts and rules in the knowledge base.
        
        :return: A dictionary with conclusion statements as keys and boolean values indicating validity
        """
        conclusions = {}
        for rule in self.knowledge_base.rules:
            if 'if' in rule:
                parts = rule.split(' then ')
                condition, conclusion = parts[0], parts[1]
                if all(part in self.knowledge_base.facts for part in condition.split(' and ')):
                    conclusions[conclusion] = True
        return conclusions


# Example usage:
reasoning_engine = ReasoningEngine()
reasoning_engine.add_fact("it is raining")
reasoning_engine.add_rule("if it is raining then bring an umbrella")
inferences = reasoning_engine.infer_conclusions()
print(inferences)  # {'bring an umbrella': True}
```

This code defines a simple reasoning engine that adds facts and rules to a knowledge base, and infers conclusions based on those. It's designed to handle basic "if-then" type logic, addressing limited reasoning sophistication within the given constraints.