mirror of
https://github.com/NicolasBohn/NexQuant.git
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Xu Yang
48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
# TODO: use pydantic for other modules in Qlib
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# from pydantic_settings import BaseSettings
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import os
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from typing import Union
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from dotenv import load_dotenv
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# make sure that env variable is loaded while calling Config()
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load_dotenv(verbose=True, override=True)
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from pydantic_settings import BaseSettings
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class FincoSettings(BaseSettings):
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use_azure: bool = True
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max_retry: int = 10
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retry_wait_seconds: int = 1
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continuous_mode: bool = False
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dump_chat_cache: bool = False
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use_chat_cache: bool = False
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dump_embedding_cache: bool = False
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use_embedding_cache: bool = False
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prompt_cache_path: str = os.getcwd() + "/prompt_cache.db"
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session_cache_folder_location: str = os.getcwd() + "/session_cache_folder/"
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max_past_message_include: int = 10
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log_llm_chat_content: bool = True
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# Chat configs
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chat_openai_api_key: str = ""
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chat_azure_api_base: str = ""
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chat_azure_api_version: str = ""
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chat_model: str = ""
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chat_max_tokens: int = 3000
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chat_temperature: float = 0.5
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chat_stream: bool = True
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chat_seed: Union[int, None] = None
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chat_frequency_penalty: float = 0.0
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chat_presence_penalty: float = 0.0
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default_system_prompt: str = "You are an AI assistant who helps to answer user's questions about finance."
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# Embedding configs
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embedding_openai_api_key: str = ""
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embedding_azure_api_base: str = ""
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embedding_azure_api_version: str = ""
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embedding_model: str = ""
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