167 lines
5.1 KiB
Python
167 lines
5.1 KiB
Python
import yaml
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from pathlib import Path
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from typing import Type, TypeVar, Any, Optional, ClassVar
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from dataclasses import dataclass, asdict, field
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ConfigInst = TypeVar('ConfigInst', bound='Config')
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AIConfigInst = TypeVar('AIConfigInst', bound='AIConfig')
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OpenAIConfigInst = TypeVar('OpenAIConfigInst', bound='OpenAIConfig')
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supported_ais: list[str] = ['openai']
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default_config_path = '.config.yaml'
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class ConfigError(Exception):
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pass
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def str_presenter(dumper: yaml.Dumper, data: str) -> yaml.ScalarNode:
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"""
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Changes the YAML dump style to multiline syntax for multiline strings.
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"""
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if len(data.splitlines()) > 1:
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return dumper.represent_scalar('tag:yaml.org,2002:str', data, style='|')
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return dumper.represent_scalar('tag:yaml.org,2002:str', data)
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yaml.add_representer(str, str_presenter)
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@dataclass
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class AIConfig:
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"""
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The base class of all AI configurations.
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"""
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# the name of the AI the config class represents
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# -> it's a class variable and thus not part of the
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# dataclass constructor
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name: ClassVar[str]
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# a user-defined ID for an AI configuration entry
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ID: str
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# the name must not be changed
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def __setattr__(self, name: str, value: Any) -> None:
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if name == 'name':
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raise AttributeError("'{name}' is not allowed to be changed")
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else:
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super().__setattr__(name, value)
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@dataclass
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class OpenAIConfig(AIConfig):
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"""
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The OpenAI section of the configuration file.
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"""
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name: ClassVar[str] = 'openai'
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# all members have default values, so we can easily create
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# a default configuration
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ID: str = 'myopenai'
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api_key: str = '0123456789'
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model: str = 'gpt-3.5-turbo-16k'
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temperature: float = 1.0
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max_tokens: int = 4000
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top_p: float = 1.0
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frequency_penalty: float = 0.0
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presence_penalty: float = 0.0
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system: str = 'You are an assistant'
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@classmethod
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def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
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"""
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Create OpenAIConfig from a dict.
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"""
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res = cls(
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api_key=str(source['api_key']),
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model=str(source['model']),
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max_tokens=int(source['max_tokens']),
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temperature=float(source['temperature']),
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top_p=float(source['top_p']),
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frequency_penalty=float(source['frequency_penalty']),
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presence_penalty=float(source['presence_penalty']),
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system=str(source['system'])
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)
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# overwrite default ID if provided
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if 'ID' in source:
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res.ID = source['ID']
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return res
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def ai_config_instance(name: str, conf_dict: Optional[dict[str, Any]] = None) -> AIConfig:
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"""
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Creates an AIConfig instance of the given name.
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"""
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if name.lower() == 'openai':
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if conf_dict is None:
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return OpenAIConfig()
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else:
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return OpenAIConfig.from_dict(conf_dict)
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else:
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raise ConfigError(f"Unknown AI '{name}'")
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def create_default_ai_configs() -> dict[str, AIConfig]:
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"""
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Create a dict containing default configurations for all supported AIs.
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"""
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return {ai_config_instance(name).ID: ai_config_instance(name) for name in supported_ais}
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@dataclass
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class Config:
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"""
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The configuration file structure.
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"""
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# all members have default values, so we can easily create
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# a default configuration
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db: str = './db/'
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ais: dict[str, AIConfig] = field(default_factory=create_default_ai_configs)
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@classmethod
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def from_dict(cls: Type[ConfigInst], source: dict[str, Any]) -> ConfigInst:
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"""
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Create Config from a dict (with the same format as the config file).
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"""
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# create the correct AI type instances
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ais: dict[str, AIConfig] = {}
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for ID, conf in source['ais'].items():
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# add the AI ID to the config (for easy internal access)
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conf['ID'] = ID
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ai_conf = ai_config_instance(conf['name'], conf)
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ais[ID] = ai_conf
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return cls(
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db=str(source['db']),
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ais=ais
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)
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@classmethod
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def create_default(self, file_path: Path) -> None:
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"""
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Creates a default Config in the given file.
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"""
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conf = Config()
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conf.to_file(file_path)
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@classmethod
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def from_file(cls: Type[ConfigInst], path: str) -> ConfigInst:
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with open(path, 'r') as f:
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source = yaml.load(f, Loader=yaml.FullLoader)
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return cls.from_dict(source)
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def to_file(self, file_path: Path) -> None:
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# remove the AI name from the config (for a cleaner format)
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data = self.as_dict()
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for conf in data['ais'].values():
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del (conf['ID'])
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with open(file_path, 'w') as f:
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yaml.dump(data, f, sort_keys=False)
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def as_dict(self) -> dict[str, Any]:
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res = asdict(self)
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# add the AI name manually (as first element)
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# (not done by 'asdict' because it's a class variable)
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for ID, conf in res['ais'].items():
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res['ais'][ID] = {**{'name': self.ais[ID].name}, **conf}
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return res
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