| 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 = "./meta2023" | |
| 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" | |