mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
111 lines
4.0 KiB
Python
111 lines
4.0 KiB
Python
from os.path import exists
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from typing import Literal, Optional
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import numpy as np
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from pydantic import Field, field_validator
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from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationConfig, InvocationContext
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from dynamicprompts.generators import RandomPromptGenerator, CombinatorialPromptGenerator
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class PromptOutput(BaseInvocationOutput):
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"""Base class for invocations that output a prompt"""
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# fmt: off
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type: Literal["prompt"] = "prompt"
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prompt: str = Field(default=None, description="The output prompt")
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# fmt: on
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class Config:
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json_schema_extra = {
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"required": [
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"type",
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"prompt",
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]
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}
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class PromptCollectionOutput(BaseInvocationOutput):
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"""Base class for invocations that output a collection of prompts"""
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# fmt: off
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type: Literal["prompt_collection_output"] = "prompt_collection_output"
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prompt_collection: list[str] = Field(description="The output prompt collection")
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count: int = Field(description="The size of the prompt collection")
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# fmt: on
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class Config:
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json_schema_extra = {"required": ["type", "prompt_collection", "count"]}
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class DynamicPromptInvocation(BaseInvocation):
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"""Parses a prompt using adieyal/dynamicprompts' random or combinatorial generator"""
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type: Literal["dynamic_prompt"] = "dynamic_prompt"
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prompt: str = Field(description="The prompt to parse with dynamicprompts")
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max_prompts: int = Field(default=1, description="The number of prompts to generate")
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combinatorial: bool = Field(default=False, description="Whether to use the combinatorial generator")
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class Config(InvocationConfig):
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json_schema_extra = {
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"ui": {"title": "Dynamic Prompt", "tags": ["prompt", "dynamic"]},
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}
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def invoke(self, context: InvocationContext) -> PromptCollectionOutput:
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if self.combinatorial:
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generator = CombinatorialPromptGenerator()
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prompts = generator.generate(self.prompt, max_prompts=self.max_prompts)
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else:
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generator = RandomPromptGenerator()
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prompts = generator.generate(self.prompt, num_images=self.max_prompts)
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return PromptCollectionOutput(prompt_collection=prompts, count=len(prompts))
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class PromptsFromFileInvocation(BaseInvocation):
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"""Loads prompts from a text file"""
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# fmt: off
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type: Literal['prompt_from_file'] = 'prompt_from_file'
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# Inputs
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file_path: str = Field(description="Path to prompt text file")
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pre_prompt: Optional[str] = Field(description="String to prepend to each prompt")
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post_prompt: Optional[str] = Field(description="String to append to each prompt")
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start_line: int = Field(default=1, ge=1, description="Line in the file to start start from")
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max_prompts: int = Field(default=1, ge=0, description="Max lines to read from file (0=all)")
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# fmt: on
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class Config(InvocationConfig):
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json_schema_extra = {
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"ui": {"title": "Prompts From File", "tags": ["prompt", "file"]},
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}
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@field_validator("file_path")
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def file_path_exists(cls, v):
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if not exists(v):
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raise ValueError(FileNotFoundError)
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return v
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def promptsFromFile(self, file_path: str, pre_prompt: str, post_prompt: str, start_line: int, max_prompts: int):
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prompts = []
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start_line -= 1
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end_line = start_line + max_prompts
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if max_prompts <= 0:
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end_line = np.iinfo(np.int32).max
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with open(file_path) as f:
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for i, line in enumerate(f):
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if i >= start_line and i < end_line:
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prompts.append((pre_prompt or "") + line.strip() + (post_prompt or ""))
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if i >= end_line:
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break
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return prompts
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def invoke(self, context: InvocationContext) -> PromptCollectionOutput:
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prompts = self.promptsFromFile(
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self.file_path, self.pre_prompt, self.post_prompt, self.start_line, self.max_prompts
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)
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return PromptCollectionOutput(prompt_collection=prompts, count=len(prompts))
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