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from dotenv import find_dotenv, load_dotenv |
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load_dotenv(find_dotenv()) |
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from langchain_openai import ChatOpenAI |
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from langchain_openai import OpenAIEmbeddings |
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GPT4_MODEL_NAME = "gpt-4-turbo-2024-04-09" |
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GPT35_MODEL_NAME = "gpt-3.5-turbo-1106" |
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gpt35_model = ChatOpenAI(model=GPT35_MODEL_NAME, temperature=0.0) |
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gpt4_model = ChatOpenAI(model=GPT4_MODEL_NAME, temperature=0.0) |
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embeddings = OpenAIEmbeddings(model="text-embedding-3-small") |
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DEFAULT_QUESTION1 = "What was the total value of 'Cash and cash equivalents' as of December 31, 2023?" |
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DEFAULT_QUESTION2 = "Who are 'Directors' (i.e., members of the Board of Directors) for Meta?" |
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ROOT_PATH = "." |
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VECTOR_STORE_PATH = f"{ROOT_PATH}/data/qdrant" |
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META_10K_FILE_PATH = f"{ROOT_PATH}/data/meta-10k-2023.pdf" |
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META_SEMANTIC_COLLECTION = "meta10k-semantic" |
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