"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-08 15:49:53.469558
"""

```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 to be added.
        """
        if fact not in self.knowledge:
            self.knowledge[fact] = []

    def retrieve_facts(self, keyword: str) -> List[str]:
        """
        Retrieves all facts that contain the given keyword.

        :param keyword: The keyword to search for within the knowledge base.
        :return: A list of matching facts.
        """
        return [fact for fact in self.knowledge if keyword in fact]


class ReasoningEngine:
    def __init__(self, kb: KnowledgeBase):
        self.kb = kb

    def infer_new_fact(self, known_facts: List[str], new_data: str) -> str:
        """
        Infers a new fact based on existing knowledge and new data.

        :param known_facts: A list of strings representing the currently known facts.
        :param new_data: A string containing additional data that may allow inference.
        :return: A newly inferred fact as a string, or an empty string if no inference is possible.
        """
        # Example simplistic logic for inferring new facts
        for fact in known_facts:
            if "temperature" in fact and "humidity" in new_data:
                return f"The temperature may affect the humidity level."
        
        return ""

    def update_reasoning(self) -> None:
        """
        Updates the engine's reasoning by adding relevant new facts.
        """
        related_facts = self.kb.retrieve_facts("weather")
        for fact in related_facts:
            if "forecast" in fact and "temperature" not in fact:
                self.kb.add_fact(f"Temperature forecast is {fact.split()[-1]} degrees.")


# Example usage
if __name__ == "__main__":
    kb = KnowledgeBase()
    kb.add_fact("High temperature today")
    kb.add_fact("Humidity levels are expected to rise")

    reasoning_engine = ReasoningEngine(kb)
    inference_result = reasoning_engine.infer_new_fact(
        known_facts=["High temperature today"],
        new_data="There is a 60% chance of rain"
    )
    
    print(inference_result)  # Output: The temperature may affect the humidity level.

    reasoning_engine.update_reasoning()
```