configuration et al: implemented new Config format

This commit is contained in:
2023-09-06 22:52:03 +02:00
parent b1a23394fc
commit eaa399bcb9
4 changed files with 134 additions and 36 deletions
+97 -22
View File
@@ -1,17 +1,40 @@
import yaml
from typing import Type, TypeVar, Any
from dataclasses import dataclass, asdict
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_ai_ID: str = 'default'
default_config_path = '.config.yaml'
class ConfigError(Exception):
pass
@dataclass
class AIConfig:
"""
The base class of all AI configurations.
"""
name: str
# 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
@@ -19,21 +42,27 @@ class OpenAIConfig(AIConfig):
"""
The OpenAI section of the configuration file.
"""
api_key: str
model: str
temperature: float
max_tokens: int
top_p: float
frequency_penalty: float
presence_penalty: float
name: ClassVar[str] = 'openai'
# all members have default values, so we can easily create
# a default configuration
ID: str = 'default'
api_key: str = '0123456789'
system: str = 'You are an assistant'
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
@classmethod
def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
"""
Create OpenAIConfig from a dict.
"""
return cls(
name='OpenAI',
res = cls(
system=str(source['system']),
api_key=str(source['api_key']),
model=str(source['model']),
max_tokens=int(source['max_tokens']),
@@ -42,6 +71,30 @@ class OpenAIConfig(AIConfig):
frequency_penalty=float(source['frequency_penalty']),
presence_penalty=float(source['presence_penalty'])
)
# 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"AI '{name}' is not supported")
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
@@ -49,30 +102,52 @@ class Config:
"""
The configuration file structure.
"""
system: str
db: str
openai: OpenAIConfig
# 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.
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(
system=str(source['system']),
db=str(source['db']),
openai=OpenAIConfig.from_dict(source['openai'])
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, path: str) -> None:
with open(path, 'w') as f:
yaml.dump(asdict(self), f, sort_keys=False)
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]:
return asdict(self)
res = asdict(self)
for ID, conf in res['ais'].items():
conf.update({'name': self.ais[ID].name})
return res