configuration: implemented new Config format

This commit is contained in:
juk0de 2023-09-06 22:52:03 +02:00
parent 893917e455
commit b2401d57ae
2 changed files with 82 additions and 22 deletions

View File

@ -17,8 +17,9 @@ class OpenAI(AI):
The OpenAI AI client.
"""
def __init__(self, name: str, config: OpenAIConfig) -> None:
self.name = name
def __init__(self, config: OpenAIConfig) -> None:
self.ai_type = config.ai_type
self.name = config.name
self.config = config
def request(self,
@ -31,8 +32,7 @@ class OpenAI(AI):
chat history. The nr. of requested answers corresponds to the
nr. of messages in the 'AIResponse'.
"""
# FIXME: use real 'system' message (store in OpenAIConfig)
oai_chat = self.openai_chat(chat, "system", question)
oai_chat = self.openai_chat(chat, self.config.system, question)
response = openai.ChatCompletion.create(
model=self.config.model,
messages=oai_chat,

View File

@ -1,16 +1,26 @@
import yaml
from typing import Type, TypeVar, Any
from dataclasses import dataclass, asdict
from pathlib import Path
from typing import Type, TypeVar, Any, Optional
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']
class ConfigError(Exception):
pass
@dataclass
class AIConfig:
"""
The base class of all AI configurations.
"""
ai_type: str
name: str
@ -19,13 +29,18 @@ 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
# all members have default values, so we can easily create
# a default configuration
ai_type: str = 'openai'
name: str = 'openai_1'
system: str = 'You are an assistant'
api_key: str = '0123456789'
model: str = 'gpt-3.5'
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:
@ -33,7 +48,9 @@ class OpenAIConfig(AIConfig):
Create OpenAIConfig from a dict.
"""
return cls(
name='OpenAI',
ai_type='openai',
name=str(source['name']),
system=str(source['system']),
api_key=str(source['api_key']),
model=str(source['model']),
max_tokens=int(source['max_tokens']),
@ -43,36 +60,79 @@ class OpenAIConfig(AIConfig):
presence_penalty=float(source['presence_penalty'])
)
def as_dict(self) -> dict[str, Any]:
return asdict(self)
def ai_type_instance(ai_type: str, conf_dict: Optional[dict[str, Any]] = None) -> AIConfig:
"""
Creates an AIConfig instance of the given type.
"""
if ai_type.lower() == 'openai':
if conf_dict is None:
return OpenAIConfig()
else:
return OpenAIConfig.from_dict(conf_dict)
else:
raise ConfigError(f"AI type '{ai_type}' is not supported")
def create_default_ai_configs() -> dict[str, AIConfig]:
"""
Create a dict containing default configurations for all supported AIs.
"""
return {ai_type_instance(ai_type).name: ai_type_instance(ai_type) for ai_type in supported_ais}
@dataclass
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 the correct AI type instances
ais: dict[str, AIConfig] = {}
for name, conf in source['ais'].items():
ai_conf = ai_type_instance(conf['type'], conf)
ais[name] = 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)
# add the AI name to the config (for easy internal access)
for name, conf in source['ais'].items():
conf['name'] = name
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 ai_name, ai_conf in data['ais'].items():
del (ai_conf['name'])
with open(file_path, 'w') as f:
yaml.dump(data, f, sort_keys=False)
def as_dict(self) -> dict[str, Any]:
return asdict(self)