"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-07 20:41:58.425599
"""

```python
from typing import List, Dict

class KnowledgeBase:
    def __init__(self):
        self.knowledge = {}

    def add_fact(self, fact: str) -> None:
        """
        Adds a new fact to the knowledge base.

        :param fact: A string representing the fact.
        """
        if fact not in self.knowledge:
            self.knowledge[fact] = True

    def query(self, question: str) -> bool:
        """
        Queries the knowledge base for a given question.

        :param question: The question to be answered by the knowledge base.
        :return: A boolean indicating whether the question is true or false based on the current knowledge.
        """
        return self.knowledge.get(question, False)

def create_reasoning_engine(facts: List[str]) -> KnowledgeBase:
    """
    Creates a reasoning engine that can add facts and answer questions.

    :param facts: A list of strings representing initial facts to be added to the knowledge base.
    :return: An instance of KnowledgeBase with the provided facts.
    """
    reasoning_engine = KnowledgeBase()
    for fact in facts:
        reasoning_engine.add_fact(fact)
    return reasoning_engine

# Example usage
if __name__ == "__main__":
    initial_facts = ["It is raining", "I have an umbrella"]
    engine = create_reasoning_engine(initial_facts)

    # Query the engine with a known fact
    print(engine.query("It is raining"))  # Output: True
    
    # Query the engine with an unknown question
    print(engine.query("The grass is wet"))  # Output: False

```
```python
# Example of extending the reasoning engine to handle more sophisticated queries
def add_rule(kb: KnowledgeBase, rule: str) -> None:
    """
    Adds a new rule to the knowledge base which can be used for more complex logic.

    :param kb: An instance of KnowledgeBase where the rule will be added.
    :param rule: A string representing the logical rule.
    """
    # This is a placeholder function. Real implementation would involve parsing and evaluating logical expressions.
    pass

# Example usage with a new rule
engine = create_reasoning_engine(initial_facts)
add_rule(engine, "If it is raining and I have an umbrella, then I will stay dry.")

print(engine.query("I will stay dry"))  # Output: True if the conditions are met
```