configuration et al: implemented new Config format
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@ -33,18 +33,23 @@ class AI(Protocol):
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The base class for AI clients.
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The base class for AI clients.
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"""
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"""
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ID: str
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name: str
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name: str
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config: AIConfig
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config: AIConfig
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def request(self,
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def request(self,
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question: Message,
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question: Message,
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context: Chat,
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chat: Chat,
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num_answers: int = 1,
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num_answers: int = 1,
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otags: Optional[set[Tag]] = None) -> AIResponse:
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otags: Optional[set[Tag]] = None) -> AIResponse:
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"""
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"""
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Make an AI request, asking the given question with the given
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Make an AI request. Parameters:
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context (i. e. chat history). The nr. of requested answers
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* question: the question to ask
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corresponds to the nr. of messages in the 'AIResponse'.
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* chat: the chat history to be added as context
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* num_answers: nr. of requested answers (corresponds
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to the nr. of messages in the 'AIResponse')
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* otags: the output tags, i. e. the tags that all
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returned messages should contain
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"""
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"""
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raise NotImplementedError
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raise NotImplementedError
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@ -3,18 +3,32 @@ Creates different AI instances, based on the given configuration.
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"""
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"""
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import argparse
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import argparse
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from .configuration import Config
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from typing import cast
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from .configuration import Config, OpenAIConfig, default_ai_ID
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from .ai import AI, AIError
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from .ai import AI, AIError
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from .ais.openai import OpenAI
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from .ais.openai_cmm import OpenAI
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def create_ai(args: argparse.Namespace, config: Config) -> AI:
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def create_ai(args: argparse.Namespace, config: Config) -> AI:
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"""
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"""
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Creates an AI subclass instance from the given args and configuration.
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Creates an AI subclass instance from the given arguments
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and configuration file.
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"""
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"""
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if args.ai == 'openai':
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if args.ai:
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# FIXME: create actual 'OpenAIConfig' and set values from 'args'
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ai_conf = config.ais[args.ai]
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# FIXME: use actual name from config
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elif default_ai_ID in config.ais:
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return OpenAI("openai", config.openai)
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ai_conf = config.ais[default_ai_ID]
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else:
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raise AIError("No AI name given and no default exists")
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if ai_conf.name == 'openai':
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ai = OpenAI(cast(OpenAIConfig, ai_conf))
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if args.max_tokens:
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ai.config.max_tokens = args.max_tokens
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if args.config.temperature:
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ai.config.temperature = args.temperature
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if args.model:
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ai.config.model = args.model
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return ai
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else:
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else:
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raise AIError(f"AI '{args.ai}' is not supported")
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raise AIError(f"AI '{args.ai}' is not supported")
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@ -17,9 +17,11 @@ class OpenAI(AI):
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The OpenAI AI client.
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The OpenAI AI client.
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"""
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"""
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def __init__(self, name: str, config: OpenAIConfig) -> None:
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def __init__(self, config: OpenAIConfig) -> None:
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self.name = name
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self.ID = config.ID
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self.name = config.name
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self.config = config
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self.config = config
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openai.api_key = config.api_key
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def request(self,
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def request(self,
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question: Message,
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question: Message,
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@ -31,8 +33,7 @@ class OpenAI(AI):
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chat history. The nr. of requested answers corresponds to the
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chat history. The nr. of requested answers corresponds to the
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nr. of messages in the 'AIResponse'.
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nr. of messages in the 'AIResponse'.
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"""
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"""
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# FIXME: use real 'system' message (store in OpenAIConfig)
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oai_chat = self.openai_chat(chat, self.config.system, question)
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oai_chat = self.openai_chat(chat, "system", question)
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response = openai.ChatCompletion.create(
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response = openai.ChatCompletion.create(
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model=self.config.model,
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model=self.config.model,
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messages=oai_chat,
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messages=oai_chat,
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@ -1,17 +1,40 @@
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import yaml
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import yaml
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from typing import Type, TypeVar, Any
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from pathlib import Path
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from dataclasses import dataclass, asdict
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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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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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OpenAIConfigInst = TypeVar('OpenAIConfigInst', bound='OpenAIConfig')
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supported_ais: list[str] = ['openai']
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default_ai_ID: str = 'default'
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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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@dataclass
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@dataclass
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class AIConfig:
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class AIConfig:
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"""
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"""
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The base class of all AI configurations.
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The base class of all AI configurations.
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"""
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"""
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name: str
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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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@dataclass
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@ -19,21 +42,27 @@ class OpenAIConfig(AIConfig):
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"""
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"""
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The OpenAI section of the configuration file.
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The OpenAI section of the configuration file.
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"""
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"""
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api_key: str
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name: ClassVar[str] = 'openai'
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model: str
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temperature: float
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# all members have default values, so we can easily create
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max_tokens: int
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# a default configuration
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top_p: float
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ID: str = 'default'
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frequency_penalty: float
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api_key: str = '0123456789'
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presence_penalty: float
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system: str = 'You are an assistant'
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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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@classmethod
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@classmethod
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def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
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def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
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"""
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"""
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Create OpenAIConfig from a dict.
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Create OpenAIConfig from a dict.
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"""
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"""
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return cls(
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res = cls(
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name='OpenAI',
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system=str(source['system']),
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api_key=str(source['api_key']),
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api_key=str(source['api_key']),
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model=str(source['model']),
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model=str(source['model']),
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max_tokens=int(source['max_tokens']),
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max_tokens=int(source['max_tokens']),
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@ -42,6 +71,30 @@ class OpenAIConfig(AIConfig):
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frequency_penalty=float(source['frequency_penalty']),
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frequency_penalty=float(source['frequency_penalty']),
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presence_penalty=float(source['presence_penalty'])
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presence_penalty=float(source['presence_penalty'])
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)
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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"AI '{name}' is not supported")
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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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@dataclass
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@ -49,30 +102,52 @@ class Config:
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"""
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"""
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The configuration file structure.
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The configuration file structure.
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"""
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"""
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system: str
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# all members have default values, so we can easily create
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db: str
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# a default configuration
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openai: OpenAIConfig
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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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@classmethod
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def from_dict(cls: Type[ConfigInst], source: dict[str, Any]) -> ConfigInst:
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def from_dict(cls: Type[ConfigInst], source: dict[str, Any]) -> ConfigInst:
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"""
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"""
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Create Config from a dict.
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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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"""
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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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return cls(
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system=str(source['system']),
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db=str(source['db']),
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db=str(source['db']),
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openai=OpenAIConfig.from_dict(source['openai'])
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ais=ais
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)
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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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@classmethod
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def from_file(cls: Type[ConfigInst], path: str) -> ConfigInst:
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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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with open(path, 'r') as f:
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source = yaml.load(f, Loader=yaml.FullLoader)
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source = yaml.load(f, Loader=yaml.FullLoader)
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return cls.from_dict(source)
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return cls.from_dict(source)
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def to_file(self, path: str) -> None:
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def to_file(self, file_path: Path) -> None:
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with open(path, 'w') as f:
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# remove the AI name from the config (for a cleaner format)
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yaml.dump(asdict(self), f, sort_keys=False)
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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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def as_dict(self) -> dict[str, Any]:
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return asdict(self)
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res = asdict(self)
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for ID, conf in res['ais'].items():
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conf.update({'name': self.ais[ID].name})
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return res
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