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37 lines
1.7 KiB
Python
37 lines
1.7 KiB
Python
from pathlib import Path
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from pydantic import BaseSettings
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class Settings(BaseSettings):
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LLM_NAME: str = "openai_chat"
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EMBEDDINGS_NAME: str = "openai_text-embedding-ada-002"
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CELERY_BROKER_URL: str = "redis://localhost:6379/0"
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CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"
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MONGO_URI: str = "mongodb://localhost:27017/docsgpt"
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MODEL_PATH: str = "./models/gpt4all-model.bin"
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TOKENS_MAX_HISTORY: int = 150
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SELF_HOSTED_MODEL: bool = False
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UPLOAD_FOLDER: str = "inputs"
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VECTOR_STORE: str = "elasticsearch" # "faiss" or "elasticsearch"
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API_URL: str = "http://localhost:7091" # backend url for celery worker
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API_KEY: str = None # LLM api key
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EMBEDDINGS_KEY: str = None # api key for embeddings (if using openai, just copy API_KEY
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OPENAI_API_BASE: str = None # azure openai api base url
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OPENAI_API_VERSION: str = None # azure openai api version
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AZURE_DEPLOYMENT_NAME: str = None # azure deployment name for answering
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AZURE_EMBEDDINGS_DEPLOYMENT_NAME: str = None # azure deployment name for embeddings
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# elasticsearch
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ELASTIC_CLOUD_ID: str = 'Docsgpt:ZXUtY2VudHJhbC0xLmF3cy5jbG91ZC5lcy5pbzo0NDMkYmNiZDYxZDE0ODE0NDNhMTkxNDU2YmI2MWViNzUxNTkkN2IwODMxZWYwMDI0NDFiOGJiNzgxZmQzYjI0MjIxYjA=' # cloud id for elasticsearch
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ELASTIC_USERNAME: str = 'elastic' # username for elasticsearch
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ELASTIC_PASSWORD: str = 'eSwoSbAhIWkXBsRdvhZxGPwc' # password for elasticsearch
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ELASTIC_URL: str = None # url for elasticsearch
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ELASTIC_INDEX: str = "docsgptbeta" # index name for elasticsearch
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path = Path(__file__).parent.parent.absolute()
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settings = Settings(_env_file=path.joinpath(".env"), _env_file_encoding="utf-8")
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