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tidy(config): move config docstring builder to its script
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@ -7,7 +7,7 @@ import os
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import re
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from functools import lru_cache
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from pathlib import Path
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from typing import Any, Literal, Optional, get_args, get_type_hints
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from typing import Any, Literal, Optional
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import yaml
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from pydantic import BaseModel, Field, PrivateAttr, field_validator
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@ -321,38 +321,6 @@ class InvokeAIAppConfig(BaseSettings):
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return root
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def generate_config_docstrings() -> str:
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"""Helper function for mkdocs. Generates a docstring for the InvokeAIAppConfig class.
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You shouldn't run this manually. Instead, run `scripts/update-config-docstring.py` to update the docstring.
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A makefile target is also available: `make update-config-docstring`.
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See that script for more information about why this is necessary.
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"""
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docstring = ' """Invoke\'s global app configuration.\n\n'
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docstring += " Typically, you won't need to interact with this class directly. Instead, use the `get_config` function from `invokeai.app.services.config` to get a singleton config object.\n\n"
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docstring += " Attributes:\n"
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field_descriptions: list[str] = []
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type_hints = get_type_hints(InvokeAIAppConfig)
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for k, v in InvokeAIAppConfig.model_fields.items():
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if v.exclude:
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continue
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field_type = type_hints.get(k)
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extra = ""
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if getattr(field_type, "__origin__", None) is Literal:
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# Get options for literals - the docs generator can't pull these out
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options = [f"`{str(x)}`" for x in get_args(field_type)]
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extra = f"<br>Valid values: {', '.join(options)}"
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field_descriptions.append(f" {k}: {v.description}{extra}")
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docstring += "\n".join(field_descriptions)
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docstring += '\n """'
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return docstring
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def migrate_v3_config_dict(config_dict: dict[str, Any]) -> InvokeAIAppConfig:
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"""Migrate a v3 config dictionary to a current config object.
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@ -1,4 +1,39 @@
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import os
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from typing import Literal, get_args, get_type_hints
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from invokeai.app.services.config.config_default import InvokeAIAppConfig
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def generate_config_docstrings() -> str:
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"""Helper function for mkdocs. Generates a docstring for the InvokeAIAppConfig class.
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You shouldn't run this manually. Instead, run `scripts/update-config-docstring.py` to update the docstring.
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A makefile target is also available: `make update-config-docstring`.
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See that script for more information about why this is necessary.
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"""
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docstring = ' """Invoke\'s global app configuration.\n\n'
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docstring += " Typically, you won't need to interact with this class directly. Instead, use the `get_config` function from `invokeai.app.services.config` to get a singleton config object.\n\n"
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docstring += " Attributes:\n"
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field_descriptions: list[str] = []
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type_hints = get_type_hints(InvokeAIAppConfig)
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for k, v in InvokeAIAppConfig.model_fields.items():
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if v.exclude:
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continue
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field_type = type_hints.get(k)
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extra = ""
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if getattr(field_type, "__origin__", None) is Literal:
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# Get options for literals - the docs generator can't pull these out
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options = [f"`{str(x)}`" for x in get_args(field_type)]
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extra = f"<br>Valid values: {', '.join(options)}"
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field_descriptions.append(f" {k}: {v.description}{extra}")
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docstring += "\n".join(field_descriptions)
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docstring += '\n """'
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return docstring
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# The pydantic app config can be documented automatically using mkdocs, but this requires that the docstring
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# for the class is kept up to date. We use a pydantic model for the app config. Each config setting is a field
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@ -14,7 +49,6 @@ def main():
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# Change working directory to the repo root
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os.chdir(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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from invokeai.app.services.config.config_default import generate_config_docstrings
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docstring = generate_config_docstrings()
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@ -1,4 +1,5 @@
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from invokeai.app.services.config.config_default import InvokeAIAppConfig, generate_config_docstrings
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from invokeai.app.services.config.config_default import InvokeAIAppConfig
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from scripts.update_config_docstring import generate_config_docstrings
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def test_app_config_docstrings_are_current():
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