from dotenv import find_dotenv, load_dotenv
load_dotenv(find_dotenv())

from langchain_openai import ChatOpenAI
from langchain_openai import OpenAIEmbeddings

GPT4_MODEL_NAME = "gpt-4-turbo-2024-04-09"
GPT35_MODEL_NAME = "gpt-3.5-turbo-1106"

gpt35_model = ChatOpenAI(model=GPT35_MODEL_NAME, temperature=0.0)
gpt4_model  = ChatOpenAI(model=GPT4_MODEL_NAME, temperature=0.0)
embeddings  = OpenAIEmbeddings(model="text-embedding-3-small")

DEFAULT_QUESTION1 = "What was the total value of 'Cash and cash equivalents' as of December 31, 2023?"
DEFAULT_QUESTION2 = "Who are 'Directors' (i.e., members of the Board of Directors) for Meta?"

ROOT_PATH = "."
VECTOR_STORE_PATH = f"{ROOT_PATH}/data/qdrant"
META_10K_FILE_PATH = f"{ROOT_PATH}/data/meta-10k-2023.pdf"
META_SEMANTIC_COLLECTION = "meta10k-semantic"