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### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> extend mypy coverage for prompt_templates, template_engine and some other smaller folders. still todo: connectors, memory and planner folders. ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄
308 lines
8.4 KiB
Python
308 lines
8.4 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""A Text splitter.
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Split text in chunks, attempting to leave meaning intact.
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For plain text, split looking at new lines first, then periods, and so on.
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For markdown, split looking at punctuation first, and so on.
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"""
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import os
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import re
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from collections.abc import Callable
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NEWLINE = os.linesep
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TEXT_SPLIT_OPTIONS: list[list[str] | None] = [
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["\n", "\r"],
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["."],
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["?", "!"],
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[";"],
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[":"],
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[","],
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[")", "]", "}"],
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[" "],
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["-"],
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None,
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]
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MD_SPLIT_OPTIONS: list[list[str] | None] = [
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["."],
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["?", "!"],
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[";"],
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[":"],
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[","],
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[")", "]", "}"],
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[" "],
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["-"],
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["\n", "\r"],
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None,
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]
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def _token_counter(text: str) -> int:
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"""Count the number of tokens in a string.
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TODO: chunking methods should be configurable to allow for different
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tokenization strategies depending on the model to be called.
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For now, we use an extremely rough estimate.
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"""
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return len(text) // 4
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def split_plaintext_lines(text: str, max_token_per_line: int, token_counter: Callable = _token_counter) -> list[str]:
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"""Split plain text into lines.
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it will split on new lines first, and then on punctuation.
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"""
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return _split_text_lines(
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text=text,
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max_token_per_line=max_token_per_line,
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trim=True,
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token_counter=token_counter,
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)
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def split_markdown_lines(text: str, max_token_per_line: int, token_counter: Callable = _token_counter) -> list[str]:
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"""Split markdown into lines.
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It will split on punctuation first, and then on space and new lines.
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"""
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return _split_markdown_lines(
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text=text,
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max_token_per_line=max_token_per_line,
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trim=True,
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token_counter=token_counter,
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)
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def split_plaintext_paragraph(text: list[str], max_tokens: int, token_counter: Callable = _token_counter) -> list[str]:
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"""Split plain text into paragraphs."""
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split_lines = []
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for line in text:
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split_lines.extend(
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_split_text_lines(
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text=line,
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max_token_per_line=max_tokens,
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trim=True,
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token_counter=token_counter,
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)
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)
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return _split_text_paragraph(text=split_lines, max_tokens=max_tokens, token_counter=token_counter)
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def split_markdown_paragraph(text: list[str], max_tokens: int, token_counter: Callable = _token_counter) -> list[str]:
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"""Split markdown into paragraphs."""
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split_lines = []
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for line in text:
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split_lines.extend(
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_split_markdown_lines(
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text=line,
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max_token_per_line=max_tokens,
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trim=False,
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token_counter=token_counter,
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)
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)
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return _split_text_paragraph(text=split_lines, max_tokens=max_tokens, token_counter=token_counter)
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def _split_text_paragraph(text: list[str], max_tokens: int, token_counter: Callable = _token_counter) -> list[str]:
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"""Split text into paragraphs."""
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if not text:
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return []
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paragraphs: list[str] = []
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current_paragraph: list[str] = []
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for line in text:
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num_tokens_line = token_counter(line)
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num_tokens_paragraph = token_counter("".join(current_paragraph))
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if num_tokens_paragraph + num_tokens_line + 1 >= max_tokens and len(current_paragraph) > 0:
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paragraphs.append("".join(current_paragraph).strip())
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current_paragraph = []
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current_paragraph.append(f"{line}{NEWLINE}")
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if len(current_paragraph) > 0:
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paragraphs.append("".join(current_paragraph).strip())
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current_paragraph = []
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# Distribute text more evenly in the last paragraphs
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# when the last paragraph is too short.
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if len(paragraphs) > 1:
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last_para = paragraphs[-1]
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sec_last_para = paragraphs[-2]
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if token_counter(last_para) < max_tokens / 4:
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last_para_tokens = last_para.split(" ")
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sec_last_para_tokens = sec_last_para.split(" ")
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last_para_token_count = len(last_para_tokens)
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sec_last_para_token_count = len(sec_last_para_tokens)
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if last_para_token_count + sec_last_para_token_count <= max_tokens:
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sec_last_para = " ".join(sec_last_para_tokens) + NEWLINE
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last_para = " ".join(last_para_tokens)
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new_sec_last_para = sec_last_para + last_para
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paragraphs[-2] = new_sec_last_para.strip()
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paragraphs.pop()
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return paragraphs
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def _split_markdown_lines(
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text: str,
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max_token_per_line: int,
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trim: bool,
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token_counter: Callable = _token_counter,
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) -> list[str]:
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"""Split markdown into lines."""
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return _split_str_lines(
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text=text,
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max_tokens=max_token_per_line,
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separators=MD_SPLIT_OPTIONS,
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trim=trim,
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token_counter=token_counter,
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)
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def _split_text_lines(
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text: str,
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max_token_per_line: int,
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trim: bool,
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token_counter: Callable = _token_counter,
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) -> list[str]:
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"""Split text into lines."""
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return _split_str_lines(
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text=text,
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max_tokens=max_token_per_line,
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separators=TEXT_SPLIT_OPTIONS,
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trim=trim,
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token_counter=token_counter,
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)
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def _split_str_lines(
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text: str,
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max_tokens: int,
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separators: list[list[str] | None],
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trim: bool,
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token_counter: Callable = _token_counter,
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) -> list[str]:
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"""Split text into lines."""
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if not text:
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return []
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text = text.replace("\r\n", "\n")
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lines: list[str] = []
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was_split = False
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for split_option in separators:
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if not lines:
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lines, was_split = _split_str(
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text=text,
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max_tokens=max_tokens,
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separators=split_option,
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trim=trim,
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token_counter=token_counter,
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)
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else:
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lines, was_split = _split_list(
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text=lines,
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max_tokens=max_tokens,
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separators=split_option,
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trim=trim,
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token_counter=token_counter,
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)
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if was_split:
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break # pragma: no cover
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return lines
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def _split_str(
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text: str,
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max_tokens: int,
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separators: list[str] | None,
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trim: bool,
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token_counter: Callable = _token_counter,
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) -> tuple[list[str], bool]:
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"""Split text into lines."""
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input_was_split = False
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if not text:
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return [], input_was_split # pragma: no cover
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if trim:
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text = text.strip()
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text_as_is = [text]
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if token_counter(text) <= max_tokens:
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return text_as_is, input_was_split
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half = len(text) // 2
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cutpoint = -1
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if not separators:
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cutpoint = half
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elif set(separators) & set(text) and len(text) > 2:
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regex_separators = re.compile("|".join(re.escape(s) for s in separators))
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min_dist = half
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for match in re.finditer(regex_separators, text):
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end = match.end()
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dist = abs(half - end)
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if dist < min_dist:
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min_dist = dist
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cutpoint = end
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elif end > half:
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# distance is increasing, so we can stop searching
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break
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else:
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return text_as_is, input_was_split
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if 0 < cutpoint < len(text):
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lines = []
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for text_part in [text[:cutpoint], text[cutpoint:]]:
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split, has_split = _split_str(
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text=text_part,
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max_tokens=max_tokens,
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separators=separators,
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trim=trim,
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token_counter=token_counter,
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)
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lines.extend(split)
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input_was_split = input_was_split or has_split
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else:
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return text_as_is, input_was_split
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return lines, input_was_split
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def _split_list(
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text: list[str],
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max_tokens: int,
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separators: list[str] | None,
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trim: bool,
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token_counter: Callable = _token_counter,
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) -> tuple[list[str], bool]:
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"""Split list of string into lines."""
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if not text:
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return [], False # pragma: no cover
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lines = []
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input_was_split = False
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for line in text:
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split_str, was_split = _split_str(
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text=line,
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max_tokens=max_tokens,
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separators=separators,
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trim=trim,
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token_counter=token_counter,
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)
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lines.extend(split_str)
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input_was_split = input_was_split or was_split
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return lines, input_was_split
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