"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-07 04:18:14.679163
"""

```python
from typing import List, Tuple


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

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

    def get_relevant_facts(self, query: str) -> List[str]:
        """
        Retrieve relevant facts from the knowledge base based on a given query.

        :param query: The query used for searching relevant facts.
        :return: A list of facts that are related to the query.
        """
        return [fact for fact in self.knowledge if query.lower() in fact.lower()]

    def infer_new_facts(self, rule: Tuple[str, str]) -> None:
        """
        Infer new facts based on a given inference rule.

        :param rule: A tuple containing two strings - the first is a known fact,
                     and the second is the inferred fact.
        """
        for known_fact in self.knowledge:
            if rule[0] == known_fact:
                self.add_fact(rule[1])


def reasoning_engine(kb: KnowledgeBase, query: str) -> List[str]:
    """
    Enhance knowledge base with new facts based on a given query.

    :param kb: The knowledge base instance to work with.
    :param query: The user's query to find relevant and infer new facts.
    :return: A list of new facts inferred or found related to the query.
    """

    print(f"Querying for: {query}")
    
    # Retrieve existing relevant facts
    relevant_facts = kb.get_relevant_facts(query)

    if relevant_facts:
        print("Relevant facts found:")
        for fact in relevant_facts:
            print(f"\t{fact}")

    else:
        print("No relevant facts found. Looking for inference rules...")

        # Define some simple inference rules
        inference_rules = [("A", "B"), ("C", "D")]

        # Try to infer new facts based on the query and rules
        for known_fact in kb.knowledge:
            if any(query in rule_part for rule_part in (known_fact, *inference_rules)):
                inferred_fact = [rule[1] for rule in inference_rules if known_fact == rule[0]]
                if inferred_fact:
                    kb.add_fact(inferred_fact[0])
                    relevant_facts.append(inferred_fact[0])
                    print(f"Inferring new fact: {inferred_fact[0]}")

    return relevant_facts


# Example usage
if __name__ == "__main__":
    # Initialize the knowledge base
    kb = KnowledgeBase()
    
    # Add some initial facts to the KB
    kb.add_fact("A is true")
    kb.add_fact("B implies C")
    
    # Call reasoning_engine with a query
    new_facts = reasoning_engine(kb, "C")

    print("\nNew facts inferred:")
    for fact in new_facts:
        print(f"\t{fact}")
```

This code defines a basic knowledge base and a `reasoning_engine` function that can retrieve relevant facts from the knowledge base based on a query. If no relevant facts are found, it attempts to infer new facts using predefined inference rules. The example usage demonstrates how to use this capability with some initial facts added to the knowledge base.