caching.py

import streamlit as st
from pathlib import Path
from typing import Optional
from optimized_store import OptimizedVectorStore
from shared_models import SharedModels
from langchain_google_genai import GoogleGenerativeAI
import os

@st.cache_resource
def load_cached_vectorstore(file_path: Path) -> OptimizedVectorStore:
    """Cached Laden des Vector Stores"""
    return OptimizedVectorStore(file_path)

@st.cache_resource
def load_shared_models():
    """Cached Laden der Shared Models"""
    return SharedModels()

@st.cache_resource
def load_llm(api_key: Optional[str] = None):
    """Cached Laden des LLM"""
    try:
        api_key = api_key or os.getenv("GOOGLE_API_KEY")
        if not api_key:
            raise ValueError("Google API Key nicht gefunden")
                
        return GoogleGenerativeAI(
            model="gemini-pro",
            temperature=0.4,
            top_p=0.95,
            max_output_tokens=700
        )
    except Exception as e:
        raise Exception(f"LLM-Initialisierungsfehler: {str(e)}")