68 lines
2.6 KiB
Python
68 lines
2.6 KiB
Python
# We need this so Python doesn't complain about the unknown StableDiffusionProcessing-typehint at runtime
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from __future__ import annotations
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import csv
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import os
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import os.path
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import typing
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import collections.abc as abc
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import tempfile
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import shutil
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if typing.TYPE_CHECKING:
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# Only import this when code is being type-checked, it doesn't have any effect at runtime
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from .processing import StableDiffusionProcessing
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class PromptStyle(typing.NamedTuple):
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name: str
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prompt: str
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negative_prompt: str
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def load_styles(path: str) -> dict[str, PromptStyle]:
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styles = {"None": PromptStyle("None", "", "")}
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if os.path.exists(path):
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with open(path, "r", encoding="utf8", newline='') as file:
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reader = csv.DictReader(file)
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for row in reader:
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# Support loading old CSV format with "name, text"-columns
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prompt = row["prompt"] if "prompt" in row else row["text"]
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negative_prompt = row.get("negative_prompt", "")
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styles[row["name"]] = PromptStyle(row["name"], prompt, negative_prompt)
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return styles
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def merge_prompts(style_prompt: str, prompt: str) -> str:
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parts = filter(None, (prompt.strip(), style_prompt.strip()))
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return ", ".join(parts)
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def apply_style(processing: StableDiffusionProcessing, style: PromptStyle) -> None:
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if isinstance(processing.prompt, list):
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processing.prompt = [merge_prompts(style.prompt, p) for p in processing.prompt]
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else:
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processing.prompt = merge_prompts(style.prompt, processing.prompt)
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if isinstance(processing.negative_prompt, list):
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processing.negative_prompt = [merge_prompts(style.negative_prompt, p) for p in processing.negative_prompt]
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else:
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processing.negative_prompt = merge_prompts(style.negative_prompt, processing.negative_prompt)
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def save_styles(path: str, styles: abc.Iterable[PromptStyle]) -> None:
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# Write to temporary file first, so we don't nuke the file if something goes wrong
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fd, temp_path = tempfile.mkstemp(".csv")
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with os.fdopen(fd, "w", encoding="utf8", newline='') as file:
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# _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple,
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# and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict()
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writer = csv.DictWriter(file, fieldnames=PromptStyle._fields)
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writer.writeheader()
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writer.writerows(style._asdict() for style in styles)
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# Always keep a backup file around
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shutil.copy(path, path + ".bak")
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shutil.move(temp_path, path)
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