"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-08 05:50:16.735544
"""

```python
from typing import List, Dict, Any


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 a piece of factual information.
        """
        self.knowledge.append(fact)

    def query(self, question: str) -> List[str]:
        """
        Queries the knowledge base with a question and returns relevant facts.

        :param question: A string representing the user's question.
        :return: A list of strings that are relevant to the question.
        """
        return [fact for fact in self.knowledge if question.lower() in fact.lower()]

    def __len__(self) -> int:
        return len(self.knowledge)


def create_reasoning_engine(kb: KnowledgeBase, question: str) -> str:
    """
    Generates a reasoning path based on the provided knowledge base and question.

    :param kb: An instance of the KnowledgeBase class.
    :param question: A string representing the user's question.
    :return: A string detailing the reasoning process or an answer to the question.
    """
    relevant_facts = kb.query(question)
    if not relevant_facts:
        return "No relevant facts found."
    
    # Simple reasoning by assuming only one fact is needed
    reasoning_path = f"Given that {relevant_facts[0]}, we can reason that: "
    answer = "The information provided does not directly answer the question, but it's related."

    if "temperature" in relevant_facts[0] and "weather" in question.lower():
        # Example of limited sophistication in reasoning
        answer = f"The weather is usually related to temperature. Based on {relevant_facts[0]}, we can infer that the current weather might be warm."
    
    return f"{reasoning_path}{answer}"


# Example usage
if __name__ == "__main__":
    kb = KnowledgeBase()
    kb.add_fact("The current temperature is 32 degrees Celsius.")
    kb.add_fact("It's raining in the city.")
    kb.add_fact("The humidity levels are at 60%.")

    question = "What is the weather like today?"
    reasoning_engine_output = create_reasoning_engine(kb, question)
    print(reasoning_engine_output)
```

This code defines a `KnowledgeBase` class to store facts and query them based on questions. The `create_reasoning_engine` function then uses this knowledge base to generate a simple reasoning path or an answer to the provided question. This is a basic example intended to demonstrate limited reasoning sophistication.