from libs import MODEL_PATH, get_embedding_model
from services import load_model
from langchain_google_genai import ChatGoogleGenerativeAI
from dotenv import load_dotenv
from services import RAGService

load_dotenv()

# model = ChatGoogleGenerativeAI(
#     model="gemini-2.5-flash-lite"
# )
    # embedding_model=get_embedding_model(),
# model2 = load_model()
rag_service = RAGService(
    model=None,
    collection_name="demo",
    persist_directory="./demo",
    embedding_model=None,
    k = 5
)