From 2571c000547da5782e5ccd0ce448adee2a221026 Mon Sep 17 00:00:00 2001
From: yiyixuxu <yixu310@gmail.com>
Date: Wed, 23 Apr 2025 19:43:34 +0200
Subject: [PATCH] move  componentspec, configspec, input output param to utils

---
 .../pipelines/modular_pipeline_utils.py       | 49 ++++++++++++++++++-
 1 file changed, 48 insertions(+), 1 deletion(-)

diff --git a/src/diffusers/pipelines/modular_pipeline_utils.py b/src/diffusers/pipelines/modular_pipeline_utils.py
index fb6b83c7ee..0fec1db91e 100644
--- a/src/diffusers/pipelines/modular_pipeline_utils.py
+++ b/src/diffusers/pipelines/modular_pipeline_utils.py
@@ -13,14 +13,61 @@
 # limitations under the License.
 
 import re
-from typing import Any, Dict, List, Union
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional, Tuple, Type, Union
 
 from ..utils.import_utils import is_torch_available
+from ..configuration_utils import FrozenDict
 
 if is_torch_available():
     import torch
 
 
+@dataclass
+class ComponentSpec:
+    """Specification for a pipeline component."""
+    name: str
+    # YiYi NOTE: is type_hint a good fild name? it is the actual class, will be used to create the default instance
+    type_hint: Type
+    description: Optional[str] = None
+    config: Optional[FrozenDict[str, Any]] = None  # you can specific default config to create a default component if it is a stateless class like scheduler, guider or image processor
+    repo: Optional[Union[str, List[str]]] = None
+    subfolder: Optional[str] = None
+    revision: Optional[str] = None
+    variant: Optional[str] = None
+
+@dataclass 
+class ConfigSpec:
+    """Specification for a pipeline configuration parameter."""
+    name: str
+    value: Any
+    description: Optional[str] = None
+    repo: Optional[Union[str, List[str]]] = None
+
+@dataclass
+class InputParam:
+    """Specification for an input parameter."""
+    name: str
+    type_hint: Any = None
+    default: Any = None
+    required: bool = False
+    description: str = ""
+
+    def __repr__(self):
+        return f"<{self.name}: {'required' if self.required else 'optional'}, default={self.default}>"
+
+
+@dataclass 
+class OutputParam:
+    """Specification for an output parameter."""
+    name: str
+    type_hint: Any = None
+    description: str = ""
+
+    def __repr__(self):
+        return f"<{self.name}: {self.type_hint.__name__ if hasattr(self.type_hint, '__name__') else str(self.type_hint)}>"
+
+
 def format_inputs_short(inputs):
     """
     Format input parameters into a string representation, with required params first followed by optional ones.