Compare commits
3 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| f47bcab2cc | |||
| 6395941516 | |||
| c5e503771c |
@@ -66,9 +66,3 @@ class AI(Protocol):
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and is not implemented for all AIs.
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and is not implemented for all AIs.
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"""
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"""
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raise NotImplementedError
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raise NotImplementedError
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def print(self) -> None:
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"""
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Print some info about the current AI, like system message.
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"""
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pass
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@@ -4,31 +4,25 @@ Creates different AI instances, based on the given configuration.
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import argparse
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import argparse
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from typing import cast
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from typing import cast
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from .configuration import Config, AIConfig, OpenAIConfig
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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 import OpenAI
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def create_ai(args: argparse.Namespace, config: Config) -> AI: # noqa: 11
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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 arguments
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Creates an AI subclass instance from the given arguments
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and configuration file. If AI has not been set in the
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and configuration file.
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arguments, it searches for the ID 'default'. If that
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is not found, it uses the first AI in the list.
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"""
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"""
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ai_conf: AIConfig
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if args.AI:
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if args.AI:
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try:
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try:
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ai_conf = config.ais[args.AI]
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ai_conf = config.ais[args.AI]
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except KeyError:
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except KeyError:
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raise AIError(f"AI ID '{args.AI}' does not exist in this configuration")
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raise AIError(f"AI ID '{args.AI}' does not exist in this configuration")
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elif 'default' in config.ais:
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elif default_ai_ID in config.ais:
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ai_conf = config.ais['default']
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ai_conf = config.ais[default_ai_ID]
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else:
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else:
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try:
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raise AIError("No AI name given and no default exists")
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ai_conf = next(iter(config.ais.values()))
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except StopIteration:
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raise AIError("No AI found in this configuration")
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if ai_conf.name == 'openai':
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if ai_conf.name == 'openai':
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ai = OpenAI(cast(OpenAIConfig, ai_conf))
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ai = OpenAI(cast(OpenAIConfig, ai_conf))
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@@ -43,20 +43,16 @@ class OpenAI(AI):
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n=num_answers,
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n=num_answers,
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frequency_penalty=self.config.frequency_penalty,
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frequency_penalty=self.config.frequency_penalty,
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presence_penalty=self.config.presence_penalty)
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presence_penalty=self.config.presence_penalty)
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question.answer = Answer(response['choices'][0]['message']['content'])
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answers: list[Message] = []
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question.tags = otags
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for choice in response['choices']: # type: ignore
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question.ai = self.ID
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question.model = self.config.model
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answers: list[Message] = [question]
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for choice in response['choices'][1:]: # type: ignore
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answers.append(Message(question=question.question,
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answers.append(Message(question=question.question,
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answer=Answer(choice['message']['content']),
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answer=Answer(choice['message']['content']),
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tags=otags,
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tags=otags,
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ai=self.ID,
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ai=self.name,
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model=self.config.model))
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model=self.config.model))
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return AIResponse(answers, Tokens(response['usage']['prompt_tokens'],
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return AIResponse(answers, Tokens(response['usage']['prompt'],
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response['usage']['completion_tokens'],
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response['usage']['completion'],
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response['usage']['total_tokens']))
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response['usage']['total']))
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def models(self) -> list[str]:
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def models(self) -> list[str]:
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"""
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"""
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@@ -99,8 +95,3 @@ class OpenAI(AI):
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def tokens(self, data: Union[Message, Chat]) -> int:
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def tokens(self, data: Union[Message, Chat]) -> int:
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raise NotImplementedError
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raise NotImplementedError
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def print(self) -> None:
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print(f"MODEL: {self.config.model}")
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print("=== SYSTEM ===")
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print(self.config.system)
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@@ -62,10 +62,7 @@ def make_file_path(dir_path: Path,
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Create a file_path for the given directory using the
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Create a file_path for the given directory using the
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given file_suffix and ID generator function.
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given file_suffix and ID generator function.
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"""
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"""
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file_path = dir_path / f"{next_fid():04d}{file_suffix}"
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return dir_path / f"{next_fid():04d}{file_suffix}"
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while file_path.exists():
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file_path = dir_path / f"{next_fid():04d}{file_suffix}"
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return file_path
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def write_dir(dir_path: Path,
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def write_dir(dir_path: Path,
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@@ -3,7 +3,7 @@ from pathlib import Path
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from itertools import zip_longest
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from itertools import zip_longest
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from ..configuration import Config
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from ..configuration import Config
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from ..chat import ChatDB
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from ..chat import ChatDB
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from ..message import Message, MessageFilter, Question, source_code
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from ..message import Message, Question, source_code
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from ..ai_factory import create_ai
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from ..ai_factory import create_ai
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from ..ai import AI, AIResponse
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from ..ai import AI, AIResponse
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@@ -52,12 +52,8 @@ def question_cmd(args: argparse.Namespace, config: Config) -> None:
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"""
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"""
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Handler for the 'question' command.
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Handler for the 'question' command.
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"""
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"""
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mfilter = MessageFilter(tags_or=args.or_tags if args.or_tags is not None else set(),
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tags_and=args.and_tags if args.and_tags is not None else set(),
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tags_not=args.exclude_tags if args.exclude_tags is not None else set())
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chat = ChatDB.from_dir(cache_path=Path('.'),
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chat = ChatDB.from_dir(cache_path=Path('.'),
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db_path=Path(config.db),
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db_path=Path(config.db))
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mfilter=mfilter)
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# if it's a new question, create and store it immediately
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# if it's a new question, create and store it immediately
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if args.ask or args.create:
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if args.ask or args.create:
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message = create_message(chat, args)
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message = create_message(chat, args)
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@@ -67,28 +63,23 @@ def question_cmd(args: argparse.Namespace, config: Config) -> None:
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# create the correct AI instance
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# create the correct AI instance
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ai: AI = create_ai(args, config)
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ai: AI = create_ai(args, config)
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if args.ask:
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if args.ask:
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ai.print()
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chat.print(paged=False)
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response: AIResponse = ai.request(message,
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response: AIResponse = ai.request(message,
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chat,
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chat,
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args.num_answers, # FIXME
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args.num_answers, # FIXME
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args.output_tags) # FIXME
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args.output_tags) # FIXME
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chat.update_messages([response.messages[0]])
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assert response
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chat.add_to_cache(response.messages[1:])
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# TODO:
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for idx, msg in enumerate(response.messages):
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# * add answer to the message above (and create
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print(f"=== ANSWER {idx+1} ===")
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# more messages for any additional answers)
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print(msg.answer)
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pass
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if response.tokens:
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elif args.repeat:
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print("===============")
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print(response.tokens)
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elif args.repeat is not None:
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lmessage = chat.latest_message()
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lmessage = chat.latest_message()
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assert lmessage
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assert lmessage
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# TODO: repeat either the last question or the
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# TODO: repeat either the last question or the
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# one(s) given in 'args.repeat' (overwrite
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# one(s) given in 'args.repeat' (overwrite
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# existing ones if 'args.overwrite' is True)
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# existing ones if 'args.overwrite' is True)
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pass
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pass
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elif args.process is not None:
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elif args.process:
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# TODO: process either all questions without an
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# TODO: process either all questions without an
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# answer or the one(s) given in 'args.process'
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# answer or the one(s) given in 'args.process'
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pass
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pass
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@@ -9,6 +9,7 @@ OpenAIConfigInst = TypeVar('OpenAIConfigInst', bound='OpenAIConfig')
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supported_ais: list[str] = ['openai']
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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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default_config_path = '.config.yaml'
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@@ -16,18 +17,6 @@ class ConfigError(Exception):
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pass
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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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@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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@@ -57,15 +46,15 @@ class OpenAIConfig(AIConfig):
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# all members have default values, so we can easily create
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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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# a default configuration
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ID: str = 'myopenai'
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ID: str = 'default'
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api_key: str = '0123456789'
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api_key: str = '0123456789'
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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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model: str = 'gpt-3.5-turbo-16k'
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temperature: float = 1.0
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temperature: float = 1.0
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max_tokens: int = 4000
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max_tokens: int = 4000
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top_p: float = 1.0
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top_p: float = 1.0
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frequency_penalty: float = 0.0
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frequency_penalty: float = 0.0
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presence_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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@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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@@ -73,14 +62,14 @@ class OpenAIConfig(AIConfig):
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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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res = cls(
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res = cls(
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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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temperature=float(source['temperature']),
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temperature=float(source['temperature']),
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top_p=float(source['top_p']),
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top_p=float(source['top_p']),
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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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system=str(source['system'])
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)
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)
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# overwrite default ID if provided
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# overwrite default ID if provided
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if 'ID' in source:
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if 'ID' in source:
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@@ -159,8 +148,6 @@ class Config:
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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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res = asdict(self)
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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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for ID, conf in res['ais'].items():
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res['ais'][ID] = {**{'name': self.ais[ID].name}, **conf}
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conf.update({'name': self.ais[ID].name})
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return res
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return res
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+10
-16
@@ -3,8 +3,6 @@ Module implementing message related functions and classes.
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"""
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"""
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import pathlib
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import pathlib
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import yaml
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import yaml
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import tempfile
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import shutil
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from typing import Type, TypeVar, ClassVar, Optional, Any, Union, Final, Literal, Iterable
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from typing import Type, TypeVar, ClassVar, Optional, Any, Union, Final, Literal, Iterable
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from dataclasses import dataclass, asdict, field
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from dataclasses import dataclass, asdict, field
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from .tags import Tag, TagLine, TagError, match_tags, rename_tags
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from .tags import Tag, TagLine, TagError, match_tags, rename_tags
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@@ -314,7 +312,7 @@ class Message():
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mfilter.tags_not if mfilter else None)
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mfilter.tags_not if mfilter else None)
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else:
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else:
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message = cls.__from_file_yaml(file_path)
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message = cls.__from_file_yaml(file_path)
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if message and (mfilter is None or message.match(mfilter)):
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if message and (not mfilter or (mfilter and message.match(mfilter))):
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return message
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return message
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else:
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else:
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return None
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return None
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@@ -447,18 +445,16 @@ class Message():
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* Answer.txt_header
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* Answer.txt_header
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* Answer
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* Answer
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"""
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"""
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with tempfile.NamedTemporaryFile(dir=file_path.parent, prefix=file_path.name, mode="w", delete=False) as temp_fd:
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with open(file_path, "w") as fd:
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temp_file_path = pathlib.Path(temp_fd.name)
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if self.tags:
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if self.tags:
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temp_fd.write(f'{TagLine.from_set(self.tags)}\n')
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fd.write(f'{TagLine.from_set(self.tags)}\n')
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if self.ai:
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if self.ai:
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temp_fd.write(f'{AILine.from_ai(self.ai)}\n')
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fd.write(f'{AILine.from_ai(self.ai)}\n')
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if self.model:
|
if self.model:
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temp_fd.write(f'{ModelLine.from_model(self.model)}\n')
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fd.write(f'{ModelLine.from_model(self.model)}\n')
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temp_fd.write(f'{Question.txt_header}\n{self.question}\n')
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fd.write(f'{Question.txt_header}\n{self.question}\n')
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if self.answer:
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if self.answer:
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temp_fd.write(f'{Answer.txt_header}\n{self.answer}\n')
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fd.write(f'{Answer.txt_header}\n{self.answer}\n')
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shutil.move(temp_file_path, file_path)
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def __to_file_yaml(self, file_path: pathlib.Path) -> None:
|
def __to_file_yaml(self, file_path: pathlib.Path) -> None:
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"""
|
"""
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@@ -470,8 +466,7 @@ class Message():
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* Message.ai_yaml_key: str [Optional]
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* Message.ai_yaml_key: str [Optional]
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* Message.model_yaml_key: str [Optional]
|
* Message.model_yaml_key: str [Optional]
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"""
|
"""
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with tempfile.NamedTemporaryFile(dir=file_path.parent, prefix=file_path.name, mode="w", delete=False) as temp_fd:
|
with open(file_path, "w") as fd:
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temp_file_path = pathlib.Path(temp_fd.name)
|
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data: YamlDict = {Question.yaml_key: str(self.question)}
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data: YamlDict = {Question.yaml_key: str(self.question)}
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if self.answer:
|
if self.answer:
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data[Answer.yaml_key] = str(self.answer)
|
data[Answer.yaml_key] = str(self.answer)
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@@ -481,8 +476,7 @@ class Message():
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data[self.model_yaml_key] = self.model
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data[self.model_yaml_key] = self.model
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if self.tags:
|
if self.tags:
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data[self.tags_yaml_key] = sorted([str(tag) for tag in self.tags])
|
data[self.tags_yaml_key] = sorted([str(tag) for tag in self.tags])
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yaml.dump(data, temp_fd, sort_keys=False)
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yaml.dump(data, fd, sort_keys=False)
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shutil.move(temp_file_path, file_path)
|
|
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|
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def filter_tags(self, prefix: Optional[str] = None, contain: Optional[str] = None) -> set[Tag]:
|
def filter_tags(self, prefix: Optional[str] = None, contain: Optional[str] = None) -> set[Tag]:
|
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"""
|
"""
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@@ -514,7 +508,7 @@ class Message():
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Return True if all attributes match, else False.
|
Return True if all attributes match, else False.
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"""
|
"""
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mytags = self.tags or set()
|
mytags = self.tags or set()
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if (((mfilter.tags_or is not None or mfilter.tags_and is not None or mfilter.tags_not is not None)
|
if (((mfilter.tags_or or mfilter.tags_and or mfilter.tags_not)
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and not match_tags(mytags, mfilter.tags_or, mfilter.tags_and, mfilter.tags_not)) # noqa: W503
|
and not match_tags(mytags, mfilter.tags_or, mfilter.tags_and, mfilter.tags_not)) # noqa: W503
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or (mfilter.ai and (not self.ai or mfilter.ai != self.ai)) # noqa: W503
|
or (mfilter.ai and (not self.ai or mfilter.ai != self.ai)) # noqa: W503
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or (mfilter.model and (not self.model or mfilter.model != self.model)) # noqa: W503
|
or (mfilter.model and (not self.model or mfilter.model != self.model)) # noqa: W503
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||||||
|
|||||||
@@ -10,7 +10,7 @@ from chatmastermind.ais.openai import OpenAI
|
|||||||
class TestCreateAI(unittest.TestCase):
|
class TestCreateAI(unittest.TestCase):
|
||||||
def setUp(self) -> None:
|
def setUp(self) -> None:
|
||||||
self.args = MagicMock(spec=argparse.Namespace)
|
self.args = MagicMock(spec=argparse.Namespace)
|
||||||
self.args.AI = 'myopenai'
|
self.args.AI = 'default'
|
||||||
self.args.model = None
|
self.args.model = None
|
||||||
self.args.max_tokens = None
|
self.args.max_tokens = None
|
||||||
self.args.temperature = None
|
self.args.temperature = None
|
||||||
@@ -18,7 +18,7 @@ class TestCreateAI(unittest.TestCase):
|
|||||||
def test_create_ai_from_args(self) -> None:
|
def test_create_ai_from_args(self) -> None:
|
||||||
# Create an AI with the default configuration
|
# Create an AI with the default configuration
|
||||||
config = Config()
|
config = Config()
|
||||||
self.args.AI = 'myopenai'
|
self.args.AI = 'default'
|
||||||
ai = create_ai(self.args, config)
|
ai = create_ai(self.args, config)
|
||||||
self.assertIsInstance(ai, OpenAI)
|
self.assertIsInstance(ai, OpenAI)
|
||||||
|
|
||||||
|
|||||||
+2
-25
@@ -202,25 +202,7 @@ class TestChatDB(unittest.TestCase):
|
|||||||
self.assertEqual(chat_db.messages[1].file_path,
|
self.assertEqual(chat_db.messages[1].file_path,
|
||||||
pathlib.Path(self.db_path.name, '0003.txt'))
|
pathlib.Path(self.db_path.name, '0003.txt'))
|
||||||
|
|
||||||
def test_chat_db_from_dir_filter_tags(self) -> None:
|
def test_chat_db_filter(self) -> None:
|
||||||
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
|
|
||||||
pathlib.Path(self.db_path.name),
|
|
||||||
mfilter=MessageFilter(tags_or={Tag('tag1')}))
|
|
||||||
self.assertEqual(len(chat_db.messages), 1)
|
|
||||||
self.assertEqual(chat_db.cache_path, pathlib.Path(self.cache_path.name))
|
|
||||||
self.assertEqual(chat_db.db_path, pathlib.Path(self.db_path.name))
|
|
||||||
self.assertEqual(chat_db.messages[0].file_path,
|
|
||||||
pathlib.Path(self.db_path.name, '0001.txt'))
|
|
||||||
|
|
||||||
def test_chat_db_from_dir_filter_tags_empty(self) -> None:
|
|
||||||
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
|
|
||||||
pathlib.Path(self.db_path.name),
|
|
||||||
mfilter=MessageFilter(tags_or=set(),
|
|
||||||
tags_and=set(),
|
|
||||||
tags_not=set()))
|
|
||||||
self.assertEqual(len(chat_db.messages), 0)
|
|
||||||
|
|
||||||
def test_chat_db_from_dir_filter_answer(self) -> None:
|
|
||||||
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
|
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
|
||||||
pathlib.Path(self.db_path.name),
|
pathlib.Path(self.db_path.name),
|
||||||
mfilter=MessageFilter(answer_contains='Answer 2'))
|
mfilter=MessageFilter(answer_contains='Answer 2'))
|
||||||
@@ -231,7 +213,7 @@ class TestChatDB(unittest.TestCase):
|
|||||||
pathlib.Path(self.db_path.name, '0002.yaml'))
|
pathlib.Path(self.db_path.name, '0002.yaml'))
|
||||||
self.assertEqual(chat_db.messages[0].answer, 'Answer 2')
|
self.assertEqual(chat_db.messages[0].answer, 'Answer 2')
|
||||||
|
|
||||||
def test_chat_db_from_messages(self) -> None:
|
def test_chat_db_from_messges(self) -> None:
|
||||||
chat_db = ChatDB.from_messages(pathlib.Path(self.cache_path.name),
|
chat_db = ChatDB.from_messages(pathlib.Path(self.cache_path.name),
|
||||||
pathlib.Path(self.db_path.name),
|
pathlib.Path(self.db_path.name),
|
||||||
messages=[self.message1, self.message2,
|
messages=[self.message1, self.message2,
|
||||||
@@ -481,8 +463,3 @@ class TestChatDB(unittest.TestCase):
|
|||||||
chat_db.update_messages([message], write=True)
|
chat_db.update_messages([message], write=True)
|
||||||
chat_db.read_db()
|
chat_db.read_db()
|
||||||
self.assertEqual(chat_db.messages[0].answer, Answer("New answer"))
|
self.assertEqual(chat_db.messages[0].answer, Answer("New answer"))
|
||||||
# test without file_path -> expect error
|
|
||||||
message1 = Message(question=Question("Question 1"),
|
|
||||||
answer=Answer("Answer 1"))
|
|
||||||
with self.assertRaises(ChatError):
|
|
||||||
chat_db.update_messages([message1])
|
|
||||||
|
|||||||
@@ -59,7 +59,7 @@ class TestConfig(unittest.TestCase):
|
|||||||
source_dict = {
|
source_dict = {
|
||||||
'db': './test_db/',
|
'db': './test_db/',
|
||||||
'ais': {
|
'ais': {
|
||||||
'myopenai': {
|
'default': {
|
||||||
'name': 'openai',
|
'name': 'openai',
|
||||||
'system': 'Custom system',
|
'system': 'Custom system',
|
||||||
'api_key': '9876543210',
|
'api_key': '9876543210',
|
||||||
@@ -75,10 +75,10 @@ class TestConfig(unittest.TestCase):
|
|||||||
config = Config.from_dict(source_dict)
|
config = Config.from_dict(source_dict)
|
||||||
self.assertEqual(config.db, './test_db/')
|
self.assertEqual(config.db, './test_db/')
|
||||||
self.assertEqual(len(config.ais), 1)
|
self.assertEqual(len(config.ais), 1)
|
||||||
self.assertEqual(config.ais['myopenai'].name, 'openai')
|
self.assertEqual(config.ais['default'].name, 'openai')
|
||||||
self.assertEqual(cast(OpenAIConfig, config.ais['myopenai']).system, 'Custom system')
|
self.assertEqual(cast(OpenAIConfig, config.ais['default']).system, 'Custom system')
|
||||||
# check that 'ID' has been added
|
# check that 'ID' has been added
|
||||||
self.assertEqual(config.ais['myopenai'].ID, 'myopenai')
|
self.assertEqual(config.ais['default'].ID, 'default')
|
||||||
|
|
||||||
def test_create_default_should_create_default_config(self) -> None:
|
def test_create_default_should_create_default_config(self) -> None:
|
||||||
Config.create_default(Path(self.test_file.name))
|
Config.create_default(Path(self.test_file.name))
|
||||||
@@ -117,8 +117,8 @@ class TestConfig(unittest.TestCase):
|
|||||||
config = Config(
|
config = Config(
|
||||||
db='./test_db/',
|
db='./test_db/',
|
||||||
ais={
|
ais={
|
||||||
'myopenai': OpenAIConfig(
|
'default': OpenAIConfig(
|
||||||
ID='myopenai',
|
ID='default',
|
||||||
system='Custom system',
|
system='Custom system',
|
||||||
api_key='9876543210',
|
api_key='9876543210',
|
||||||
model='custom_model',
|
model='custom_model',
|
||||||
@@ -135,7 +135,7 @@ class TestConfig(unittest.TestCase):
|
|||||||
saved_config = yaml.load(f, Loader=yaml.FullLoader)
|
saved_config = yaml.load(f, Loader=yaml.FullLoader)
|
||||||
self.assertEqual(saved_config['db'], './test_db/')
|
self.assertEqual(saved_config['db'], './test_db/')
|
||||||
self.assertEqual(len(saved_config['ais']), 1)
|
self.assertEqual(len(saved_config['ais']), 1)
|
||||||
self.assertEqual(saved_config['ais']['myopenai']['system'], 'Custom system')
|
self.assertEqual(saved_config['ais']['default']['system'], 'Custom system')
|
||||||
|
|
||||||
def test_from_file_error_unknown_ai(self) -> None:
|
def test_from_file_error_unknown_ai(self) -> None:
|
||||||
source_dict = {
|
source_dict = {
|
||||||
|
|||||||
@@ -300,12 +300,6 @@ This is a question.
|
|||||||
MessageFilter(tags_or={Tag('tag1')}))
|
MessageFilter(tags_or={Tag('tag1')}))
|
||||||
self.assertIsNone(message)
|
self.assertIsNone(message)
|
||||||
|
|
||||||
def test_from_file_txt_empty_tags_dont_match(self) -> None:
|
|
||||||
message = Message.from_file(self.file_path_min,
|
|
||||||
MessageFilter(tags_or=set(),
|
|
||||||
tags_and=set()))
|
|
||||||
self.assertIsNone(message)
|
|
||||||
|
|
||||||
def test_from_file_txt_no_tags_match_tags_not(self) -> None:
|
def test_from_file_txt_no_tags_match_tags_not(self) -> None:
|
||||||
message = Message.from_file(self.file_path_min,
|
message = Message.from_file(self.file_path_min,
|
||||||
MessageFilter(tags_not={Tag('tag1')}))
|
MessageFilter(tags_not={Tag('tag1')}))
|
||||||
|
|||||||
Reference in New Issue
Block a user