mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
7e5ba2795e
Update all invocations to use the new context. The changes are all fairly simple, but there are a lot of them. Supporting minor changes: - Patch bump for all nodes that use the context - Update invocation processor to provide new context - Minor change to `EventServiceBase` to accept a node's ID instead of the dict version of a node - Minor change to `ModelManagerService` to support the new wrapped context - Fanagling of imports to avoid circular dependencies
103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
from os.path import exists
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from typing import Optional, Union
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import numpy as np
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from dynamicprompts.generators import CombinatorialPromptGenerator, RandomPromptGenerator
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from pydantic import field_validator
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from invokeai.app.invocations.primitives import StringCollectionOutput
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from .baseinvocation import BaseInvocation, invocation
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from .fields import InputField, UIComponent
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@invocation(
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"dynamic_prompt",
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title="Dynamic Prompt",
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tags=["prompt", "collection"],
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category="prompt",
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version="1.0.0",
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use_cache=False,
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)
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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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prompt: str = InputField(
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description="The prompt to parse with dynamicprompts",
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ui_component=UIComponent.Textarea,
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)
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max_prompts: int = InputField(default=1, description="The number of prompts to generate")
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combinatorial: bool = InputField(default=False, description="Whether to use the combinatorial generator")
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def invoke(self, context) -> StringCollectionOutput:
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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 StringCollectionOutput(collection=prompts)
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@invocation(
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"prompt_from_file",
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title="Prompts from File",
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tags=["prompt", "file"],
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category="prompt",
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version="1.0.1",
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)
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class PromptsFromFileInvocation(BaseInvocation):
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"""Loads prompts from a text file"""
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file_path: str = InputField(description="Path to prompt text file")
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pre_prompt: Optional[str] = InputField(
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default=None,
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description="String to prepend to each prompt",
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ui_component=UIComponent.Textarea,
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)
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post_prompt: Optional[str] = InputField(
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default=None,
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description="String to append to each prompt",
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ui_component=UIComponent.Textarea,
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)
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start_line: int = InputField(default=1, ge=1, description="Line in the file to start start from")
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max_prompts: int = InputField(default=1, ge=0, description="Max lines to read from file (0=all)")
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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(
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self,
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file_path: str,
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pre_prompt: Union[str, None],
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post_prompt: Union[str, None],
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start_line: int,
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max_prompts: int,
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):
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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, encoding="utf-8") 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) -> StringCollectionOutput:
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prompts = self.promptsFromFile(
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self.file_path,
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self.pre_prompt,
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self.post_prompt,
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self.start_line,
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self.max_prompts,
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)
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return StringCollectionOutput(collection=prompts)
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