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https://github.com/invoke-ai/InvokeAI
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044d4c107a
All invocation metadata (type, title, tags and category) are now defined in decorators.
The decorators add the `type: Literal["invocation_type"]: "invocation_type"` field to the invocation.
Category is a new invocation metadata, but it is not used by the frontend just yet.
- `@invocation()` decorator for invocations
```py
@invocation(
"sdxl_compel_prompt",
title="SDXL Prompt",
tags=["sdxl", "compel", "prompt"],
category="conditioning",
)
class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
...
```
- `@invocation_output()` decorator for invocation outputs
```py
@invocation_output("clip_skip_output")
class ClipSkipInvocationOutput(BaseInvocationOutput):
...
```
- update invocation docs
- add category to decorator
- regen frontend types
70 lines
2.7 KiB
Python
70 lines
2.7 KiB
Python
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
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import numpy as np
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from pydantic import validator
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from invokeai.app.invocations.primitives import IntegerCollectionOutput
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from invokeai.app.util.misc import SEED_MAX, get_random_seed
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from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
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@invocation("range", title="Integer Range", tags=["collection", "integer", "range"], category="collections")
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class RangeInvocation(BaseInvocation):
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"""Creates a range of numbers from start to stop with step"""
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start: int = InputField(default=0, description="The start of the range")
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stop: int = InputField(default=10, description="The stop of the range")
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step: int = InputField(default=1, description="The step of the range")
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@validator("stop")
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def stop_gt_start(cls, v, values):
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if "start" in values and v <= values["start"]:
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raise ValueError("stop must be greater than start")
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return v
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
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@invocation(
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"range_of_size",
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title="Integer Range of Size",
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tags=["collection", "integer", "size", "range"],
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category="collections",
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)
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class RangeOfSizeInvocation(BaseInvocation):
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"""Creates a range from start to start + size with step"""
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start: int = InputField(default=0, description="The start of the range")
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size: int = InputField(default=1, description="The number of values")
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step: int = InputField(default=1, description="The step of the range")
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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return IntegerCollectionOutput(collection=list(range(self.start, self.start + self.size, self.step)))
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@invocation(
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"random_range",
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title="Random Range",
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tags=["range", "integer", "random", "collection"],
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category="collections",
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)
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class RandomRangeInvocation(BaseInvocation):
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"""Creates a collection of random numbers"""
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low: int = InputField(default=0, description="The inclusive low value")
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high: int = InputField(default=np.iinfo(np.int32).max, description="The exclusive high value")
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size: int = InputField(default=1, description="The number of values to generate")
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seed: int = InputField(
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ge=0,
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le=SEED_MAX,
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description="The seed for the RNG (omit for random)",
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default_factory=get_random_seed,
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)
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def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
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rng = np.random.default_rng(self.seed)
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return IntegerCollectionOutput(collection=list(rng.integers(low=self.low, high=self.high, size=self.size)))
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