"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-07 04:24:32.091467
"""

```python
from typing import List, Dict

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

    def add_fact(self, fact: str) -> None:
        """Add a new fact to the knowledge base."""
        if fact not in self.knowledge:
            self.knowledge[fact] = []

    def get_facts(self) -> Dict[str, List]:
        """Return all facts present in the knowledge base."""
        return self.knowledge

    def infer_new_fact(self, facts: List[str]) -> str:
        """
        Infer a new fact based on existing ones.
        
        Args:
            facts (List[str]): A list of known facts to use for inference.

        Returns:
            str: The inferred fact or an empty string if no valid inference can be made.
        """
        # Simple rule-based system for demonstration purposes
        # Example rules: If it's raining and there are umbrellas, infer that people carry umbrellas
        umbrella_rule = ["raining", "umbrellas_available"]  # Placeholder facts

        inferred_fact = ""
        if set(umbrella_rule).issubset(set(facts)):
            inferred_fact = "people_carry_umbrellas"
        
        return inferred_fact


def create_reasoning_engine() -> KnowledgeBase:
    """
    Create a reasoning engine capable of inferring new knowledge based on existing facts.

    Returns:
        KnowledgeBase: A newly created reasoning engine.
    """
    engine = KnowledgeBase()
    # Adding some initial facts
    engine.add_fact("raining")
    engine.add_fact("umbrellas_available")

    return engine


# Example usage
if __name__ == "__main__":
    reasoning_engine = create_reasoning_engine()
    print(reasoning_engine.get_facts())  # Before inference

    inferred_fact = reasoning_engine.infer_new_fact(["raining", "umbrellas_available"])
    print(f"Inferred fact: {inferred_fact}")  # After inference
```