from pathlib import Path

from pydantic import BaseSettings


class Settings(BaseSettings):
    LLM_NAME: str = "openai_chat"
    EMBEDDINGS_NAME: str = "openai_text-embedding-ada-002"
    CELERY_BROKER_URL: str = "redis://localhost:6379/0"
    CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"
    MONGO_URI: str = "mongodb://localhost:27017/docsgpt"
    MODEL_PATH: str = "./models/gpt4all-model.bin"
    TOKENS_MAX_HISTORY: int = 150
    SELF_HOSTED_MODEL: bool = False
    UPLOAD_FOLDER: str = "inputs"
    VECTOR_STORE: str = "elasticsearch"  # "faiss" or "elasticsearch"

    API_URL: str = "http://localhost:7091"  # backend url for celery worker

    API_KEY: str = None  # LLM api key
    EMBEDDINGS_KEY: str = None  # api key for embeddings (if using openai, just copy API_KEY
    OPENAI_API_BASE: str = None  # azure openai api base url
    OPENAI_API_VERSION: str = None  # azure openai api version
    AZURE_DEPLOYMENT_NAME: str = None  # azure deployment name for answering
    AZURE_EMBEDDINGS_DEPLOYMENT_NAME: str = None  # azure deployment name for embeddings

    # elasticsearch
    ELASTIC_CLOUD_ID: str = 'Docsgpt:ZXUtY2VudHJhbC0xLmF3cy5jbG91ZC5lcy5pbzo0NDMkYmNiZDYxZDE0ODE0NDNhMTkxNDU2YmI2MWViNzUxNTkkN2IwODMxZWYwMDI0NDFiOGJiNzgxZmQzYjI0MjIxYjA=' # cloud id for elasticsearch
    ELASTIC_USERNAME: str = 'elastic' # username for elasticsearch
    ELASTIC_PASSWORD: str = 'eSwoSbAhIWkXBsRdvhZxGPwc' # password for elasticsearch
    ELASTIC_URL: str = None # url for elasticsearch
    ELASTIC_INDEX: str = "docsgptbeta" # index name for elasticsearch


path = Path(__file__).parent.parent.absolute()
settings = Settings(_env_file=path.joinpath(".env"), _env_file_encoding="utf-8")