ChatMastermind/chatmastermind/configuration.py

167 lines
5.1 KiB
Python

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