424 lines
16 KiB
Python
424 lines
16 KiB
Python
"""
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Module implementing message related functions and classes.
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"""
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import pathlib
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import yaml
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from typing import Type, TypeVar, ClassVar, Optional, Any, Union, Final, Literal
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from dataclasses import dataclass, asdict
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from .tags import Tag, TagLine, TagError, match_tags
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QuestionInst = TypeVar('QuestionInst', bound='Question')
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AnswerInst = TypeVar('AnswerInst', bound='Answer')
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MessageInst = TypeVar('MessageInst', bound='Message')
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AILineInst = TypeVar('AILineInst', bound='AILine')
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ModelLineInst = TypeVar('ModelLineInst', bound='ModelLine')
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YamlDict = dict[str, Union[QuestionInst, AnswerInst, set[Tag]]]
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class MessageError(Exception):
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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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def source_code(text: str, include_delims: bool = False) -> list[str]:
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"""
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Extract all source code sections from the given text, i. e. all lines
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surrounded by lines tarting with '```'. If 'include_delims' is True,
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the surrounding lines are included, otherwise they are omitted. The
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result list contains every source code section as a single string.
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The order in the list represents the order of the sections in the text.
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"""
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code_sections: list[str] = []
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code_lines: list[str] = []
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in_code_block = False
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for line in text.split('\n'):
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if line.strip().startswith('```'):
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if include_delims:
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code_lines.append(line)
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if in_code_block:
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code_sections.append('\n'.join(code_lines) + '\n')
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code_lines.clear()
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in_code_block = not in_code_block
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elif in_code_block:
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code_lines.append(line)
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return code_sections
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@dataclass(kw_only=True)
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class MessageFilter:
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"""
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Various filters for a Message.
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"""
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tags_or: Optional[set[Tag]] = None
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tags_and: Optional[set[Tag]] = None
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tags_not: Optional[set[Tag]] = None
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ai: Optional[str] = None
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model: Optional[str] = None
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question_contains: Optional[str] = None
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answer_contains: Optional[str] = None
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answer_state: Optional[Literal['available', 'missing']] = None
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ai_state: Optional[Literal['available', 'missing']] = None
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model_state: Optional[Literal['available', 'missing']] = None
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class AILine(str):
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"""
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A line that represents the AI name in a '.txt' file..
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"""
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prefix: Final[str] = 'AI:'
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def __new__(cls: Type[AILineInst], string: str) -> AILineInst:
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if not string.startswith(cls.prefix):
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raise TagError(f"AILine '{string}' is missing prefix '{cls.prefix}'")
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instance = super().__new__(cls, string)
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return instance
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def ai(self) -> str:
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return self[len(self.prefix):].strip()
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@classmethod
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def from_ai(cls: Type[AILineInst], ai: str) -> AILineInst:
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return cls(' '.join([cls.prefix, ai]))
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class ModelLine(str):
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"""
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A line that represents the model name in a '.txt' file..
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"""
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prefix: Final[str] = 'MODEL:'
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def __new__(cls: Type[ModelLineInst], string: str) -> ModelLineInst:
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if not string.startswith(cls.prefix):
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raise TagError(f"ModelLine '{string}' is missing prefix '{cls.prefix}'")
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instance = super().__new__(cls, string)
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return instance
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def model(self) -> str:
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return self[len(self.prefix):].strip()
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@classmethod
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def from_model(cls: Type[ModelLineInst], model: str) -> ModelLineInst:
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return cls(' '.join([cls.prefix, model]))
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class Question(str):
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"""
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A single question with a defined header.
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"""
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txt_header: ClassVar[str] = '=== QUESTION ==='
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yaml_key: ClassVar[str] = 'question'
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def __new__(cls: Type[QuestionInst], string: str) -> QuestionInst:
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"""
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Make sure the question string does not contain the header.
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"""
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if cls.txt_header in string:
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raise MessageError(f"Question '{string}' contains the header '{cls.txt_header}'")
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instance = super().__new__(cls, string)
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return instance
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@classmethod
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def from_list(cls: Type[QuestionInst], strings: list[str]) -> QuestionInst:
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"""
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Build Question from a list of strings. Make sure strings do not contain the header.
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"""
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if any(cls.txt_header in string for string in strings):
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raise MessageError(f"Question contains the header '{cls.txt_header}'")
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instance = super().__new__(cls, '\n'.join(strings).strip())
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return instance
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def source_code(self, include_delims: bool = False) -> list[str]:
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"""
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Extract and return all source code sections.
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"""
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return source_code(self, include_delims)
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class Answer(str):
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"""
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A single answer with a defined header.
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"""
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txt_header: ClassVar[str] = '=== ANSWER ==='
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yaml_key: ClassVar[str] = 'answer'
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def __new__(cls: Type[AnswerInst], string: str) -> AnswerInst:
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"""
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Make sure the answer string does not contain the header.
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"""
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if cls.txt_header in string:
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raise MessageError(f"Answer '{string}' contains the header '{cls.txt_header}'")
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instance = super().__new__(cls, string)
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return instance
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@classmethod
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def from_list(cls: Type[AnswerInst], strings: list[str]) -> AnswerInst:
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"""
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Build Question from a list of strings. Make sure strings do not contain the header.
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"""
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if any(cls.txt_header in string for string in strings):
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raise MessageError(f"Question contains the header '{cls.txt_header}'")
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instance = super().__new__(cls, '\n'.join(strings).strip())
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return instance
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def source_code(self, include_delims: bool = False) -> list[str]:
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"""
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Extract and return all source code sections.
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"""
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return source_code(self, include_delims)
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@dataclass
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class Message():
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"""
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Single message. Consists of a question and optionally an answer, a set of tags
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and a file path.
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"""
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question: Question
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answer: Optional[Answer] = None
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tags: Optional[set[Tag]] = None
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ai: Optional[str] = None
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model: Optional[str] = None
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file_path: Optional[pathlib.Path] = None
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# class variables
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file_suffixes: ClassVar[list[str]] = ['.txt', '.yaml']
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tags_yaml_key: ClassVar[str] = 'tags'
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file_yaml_key: ClassVar[str] = 'file_path'
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ai_yaml_key: ClassVar[str] = 'ai'
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model_yaml_key: ClassVar[str] = 'model'
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@classmethod
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def from_dict(cls: Type[MessageInst], data: dict[str, Any]) -> MessageInst:
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"""
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Create a Message from the given dict.
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"""
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return cls(question=data[Question.yaml_key],
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answer=data.get(Answer.yaml_key, None),
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tags=set(data.get(cls.tags_yaml_key, [])),
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ai=data.get(cls.ai_yaml_key, None),
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model=data.get(cls.model_yaml_key, None),
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file_path=data.get(cls.file_yaml_key, None))
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@classmethod
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def tags_from_file(cls: Type[MessageInst], file_path: pathlib.Path) -> set[Tag]:
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"""
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Return only the tags from the given Message file.
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"""
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if not file_path.exists():
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raise MessageError(f"Message file '{file_path}' does not exist")
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if file_path.suffix not in cls.file_suffixes:
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raise MessageError(f"File type '{file_path.suffix}' is not supported")
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if file_path.suffix == '.txt':
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with open(file_path, "r") as fd:
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tags = TagLine(fd.readline()).tags()
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else: # '.yaml'
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with open(file_path, "r") as fd:
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data = yaml.load(fd, Loader=yaml.FullLoader)
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tags = set(sorted(data[cls.tags_yaml_key]))
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return tags
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@classmethod
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def from_file(cls: Type[MessageInst], file_path: pathlib.Path,
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mfilter: Optional[MessageFilter] = None) -> Optional[MessageInst]:
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"""
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Create a Message from the given file. Returns 'None' if the message does
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not fulfill the filter requirements. For TXT files, the tags are matched
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before building the whole message. The other filters are applied afterwards.
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"""
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if not file_path.exists():
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raise MessageError(f"Message file '{file_path}' does not exist")
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if file_path.suffix not in cls.file_suffixes:
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raise MessageError(f"File type '{file_path.suffix}' is not supported")
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if file_path.suffix == '.txt':
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message = cls.__from_file_txt(file_path,
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mfilter.tags_or if mfilter else None,
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mfilter.tags_and if mfilter else None,
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mfilter.tags_not if mfilter else None)
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else:
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message = cls.__from_file_yaml(file_path)
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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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else:
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return None
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@classmethod
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def __from_file_txt(cls: Type[MessageInst], file_path: pathlib.Path, # noqa: 11
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tags_or: Optional[set[Tag]] = None,
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tags_and: Optional[set[Tag]] = None,
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tags_not: Optional[set[Tag]] = None) -> Optional[MessageInst]:
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"""
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Create a Message from the given TXT file. Expects the following file structures:
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For '.txt':
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* TagLine [Optional]
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* AI [Optional]
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* Model [Optional]
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* Question.txt_header
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* Question
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* Answer.txt_header [Optional]
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* Answer [Optional]
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Returns 'None' if the message does not fulfill the tag requirements.
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"""
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tags: set[Tag] = set()
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question: Question
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answer: Optional[Answer] = None
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ai: Optional[str] = None
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model: Optional[str] = None
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with open(file_path, "r") as fd:
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# TagLine (Optional)
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try:
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pos = fd.tell()
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tags = TagLine(fd.readline()).tags()
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except TagError:
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fd.seek(pos)
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if tags_or or tags_and or tags_not:
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# match with an empty set if the file has no tags
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if not match_tags(tags, tags_or, tags_and, tags_not):
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return None
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# AILine (Optional)
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try:
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pos = fd.tell()
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ai = AILine(fd.readline()).ai()
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except TagError:
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fd.seek(pos)
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# ModelLine (Optional)
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try:
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pos = fd.tell()
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model = ModelLine(fd.readline()).model()
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except TagError:
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fd.seek(pos)
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# Question and Answer
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text = fd.read().strip().split('\n')
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question_idx = text.index(Question.txt_header) + 1
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try:
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answer_idx = text.index(Answer.txt_header)
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question = Question.from_list(text[question_idx:answer_idx])
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answer = Answer.from_list(text[answer_idx + 1:])
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except ValueError:
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question = Question.from_list(text[question_idx:])
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return cls(question, answer, tags, ai, model, file_path)
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@classmethod
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def __from_file_yaml(cls: Type[MessageInst], file_path: pathlib.Path) -> MessageInst:
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"""
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Create a Message from the given YAML file. Expects the following file structures:
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* Question.yaml_key: single or multiline string
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* Answer.yaml_key: single or multiline string [Optional]
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* Message.tags_yaml_key: list of strings [Optional]
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* Message.ai_yaml_key: str [Optional]
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* Message.model_yaml_key: str [Optional]
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"""
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with open(file_path, "r") as fd:
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data = yaml.load(fd, Loader=yaml.FullLoader)
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data[cls.file_yaml_key] = file_path
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return cls.from_dict(data)
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def to_file(self, file_path: Optional[pathlib.Path]=None) -> None: # noqa: 11
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"""
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Write a Message to the given file. Type is determined based on the suffix.
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Currently supported suffixes: ['.txt', '.yaml']
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"""
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if file_path:
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self.file_path = file_path
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if not self.file_path:
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raise MessageError("Got no valid path to write message")
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if self.file_path.suffix not in self.file_suffixes:
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raise MessageError(f"File type '{self.file_path.suffix}' is not supported")
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# TXT
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if self.file_path.suffix == '.txt':
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return self.__to_file_txt(self.file_path)
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elif self.file_path.suffix == '.yaml':
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return self.__to_file_yaml(self.file_path)
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def __to_file_txt(self, file_path: pathlib.Path) -> None:
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"""
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Write a Message to the given file in TXT format.
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Creates the following file structures:
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* TagLine
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* AI [Optional]
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* Model [Optional]
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* Question.txt_header
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* Question
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* Answer.txt_header
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* Answer
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"""
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with open(file_path, "w") as fd:
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if self.tags:
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fd.write(f'{TagLine.from_set(self.tags)}\n')
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if self.ai:
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fd.write(f'{AILine.from_ai(self.ai)}\n')
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if self.model:
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fd.write(f'{ModelLine.from_model(self.model)}\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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fd.write(f'{Answer.txt_header}\n{self.answer}\n')
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def __to_file_yaml(self, file_path: pathlib.Path) -> None:
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"""
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Write a Message to the given file in YAML format.
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Creates the following file structures:
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* Question.yaml_key: single or multiline string
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* Answer.yaml_key: single or multiline string
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* Message.tags_yaml_key: list of strings
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* Message.ai_yaml_key: str [Optional]
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* Message.model_yaml_key: str [Optional]
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"""
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with open(file_path, "w") as fd:
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data: YamlDict = {Question.yaml_key: str(self.question)}
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if self.answer:
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data[Answer.yaml_key] = str(self.answer)
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if self.ai:
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data[self.ai_yaml_key] = self.ai
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if self.model:
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data[self.model_yaml_key] = self.model
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if self.tags:
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data[self.tags_yaml_key] = sorted([str(tag) for tag in self.tags])
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yaml.dump(data, fd, sort_keys=False)
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def match(self, mfilter: MessageFilter) -> bool: # noqa: 13
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"""
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Matches the current Message to the given filter atttributes.
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Return True if all attributes match, else False.
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"""
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mytags = self.tags or set()
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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
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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
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or (mfilter.question_contains and mfilter.question_contains not in self.question) # noqa: W503
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or (mfilter.answer_contains and (not self.answer or mfilter.answer_contains not in self.answer)) # noqa: W503
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or (mfilter.answer_state == 'available' and not self.answer) # noqa: W503
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or (mfilter.ai_state == 'available' and not self.ai) # noqa: W503
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or (mfilter.model_state == 'available' and not self.model) # noqa: W503
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or (mfilter.answer_state == 'missing' and self.answer) # noqa: W503
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or (mfilter.ai_state == 'missing' and self.ai) # noqa: W503
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or (mfilter.model_state == 'missing' and self.model)): # noqa: W503
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return False
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return True
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def msg_id(self) -> str:
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"""
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Returns an ID that is unique throughout all messages in the same (DB) directory.
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Currently this is the file name. The ID is also used for sorting messages.
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"""
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if self.file_path:
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return self.file_path.name
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else:
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raise MessageError("Can't create file ID without a file path")
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def as_dict(self) -> dict[str, Any]:
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return asdict(self)
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