[API Nodes]: fixes and refactor (#11104)

* chore(api-nodes): applied ruff's pyupgrade(python3.10) to api-nodes client's to folder

* chore(api-nodes): add validate_video_frame_count function from LTX PR

* chore(api-nodes): replace deprecated V1 imports

* fix(api-nodes): the types returned by the "poll_op" function are now correct.

comfy_api_nodes/util/validation_utils.py

@@ -1,9 +1,7 @@
 import logging
-from typing import Optional
 
 import torch
 
-from comfy_api.input.video_types import VideoInput
 from comfy_api.latest import Input
 
 
@@ -18,10 +16,10 @@ def get_image_dimensions(image: torch.Tensor) -> tuple[int, int]:
 
 def validate_image_dimensions(
     image: torch.Tensor,
-    min_width: Optional[int] = None,
-    max_width: Optional[int] = None,
-    min_height: Optional[int] = None,
-    max_height: Optional[int] = None,
+    min_width: int | None = None,
+    max_width: int | None = None,
+    min_height: int | None = None,
+    max_height: int | None = None,
 ):
     height, width = get_image_dimensions(image)
 
@@ -37,8 +35,8 @@ def validate_image_dimensions(
 
 def validate_image_aspect_ratio(
     image: torch.Tensor,
-    min_ratio: Optional[tuple[float, float]] = None,  # e.g. (1, 4)
-    max_ratio: Optional[tuple[float, float]] = None,  # e.g. (4, 1)
+    min_ratio: tuple[float, float] | None = None,  # e.g. (1, 4)
+    max_ratio: tuple[float, float] | None = None,  # e.g. (4, 1)
     *,
     strict: bool = True,  # True -> (min, max); False -> [min, max]
 ) -> float:
@@ -54,8 +52,8 @@ def validate_image_aspect_ratio(
 def validate_images_aspect_ratio_closeness(
     first_image: torch.Tensor,
     second_image: torch.Tensor,
-    min_rel: float,   # e.g. 0.8
-    max_rel: float,   # e.g. 1.25
+    min_rel: float,  # e.g. 0.8
+    max_rel: float,  # e.g. 1.25
     *,
     strict: bool = False,  # True -> (min, max); False -> [min, max]
 ) -> float:
@@ -84,8 +82,8 @@ def validate_images_aspect_ratio_closeness(
 
 def validate_aspect_ratio_string(
     aspect_ratio: str,
-    min_ratio: Optional[tuple[float, float]] = None,  # e.g. (1, 4)
-    max_ratio: Optional[tuple[float, float]] = None,  # e.g. (4, 1)
+    min_ratio: tuple[float, float] | None = None,  # e.g. (1, 4)
+    max_ratio: tuple[float, float] | None = None,  # e.g. (4, 1)
     *,
     strict: bool = False,  # True -> (min, max); False -> [min, max]
 ) -> float:
@@ -97,10 +95,10 @@ def validate_aspect_ratio_string(
 
 def validate_video_dimensions(
     video: Input.Video,
-    min_width: Optional[int] = None,
-    max_width: Optional[int] = None,
-    min_height: Optional[int] = None,
-    max_height: Optional[int] = None,
+    min_width: int | None = None,
+    max_width: int | None = None,
+    min_height: int | None = None,
+    max_height: int | None = None,
 ):
     try:
         width, height = video.get_dimensions()
@@ -120,8 +118,8 @@ def validate_video_dimensions(
 
 def validate_video_duration(
     video: Input.Video,
-    min_duration: Optional[float] = None,
-    max_duration: Optional[float] = None,
+    min_duration: float | None = None,
+    max_duration: float | None = None,
 ):
     try:
         duration = video.get_duration()
@@ -136,6 +134,23 @@ def validate_video_duration(
         raise ValueError(f"Video duration must be at most {max_duration}s, got {duration}s")
 
 
+def validate_video_frame_count(
+    video: Input.Video,
+    min_frame_count: int | None = None,
+    max_frame_count: int | None = None,
+):
+    try:
+        frame_count = video.get_frame_count()
+    except Exception as e:
+        logging.error("Error getting frame count of video: %s", e)
+        return
+
+    if min_frame_count is not None and min_frame_count > frame_count:
+        raise ValueError(f"Video frame count must be at least {min_frame_count}, got {frame_count}")
+    if max_frame_count is not None and frame_count > max_frame_count:
+        raise ValueError(f"Video frame count must be at most {max_frame_count}, got {frame_count}")
+
+
 def get_number_of_images(images):
     if isinstance(images, torch.Tensor):
         return images.shape[0] if images.ndim >= 4 else 1
@@ -144,8 +159,8 @@ def get_number_of_images(images):
 
 def validate_audio_duration(
     audio: Input.Audio,
-    min_duration: Optional[float] = None,
-    max_duration: Optional[float] = None,
+    min_duration: float | None = None,
+    max_duration: float | None = None,
 ) -> None:
     sr = int(audio["sample_rate"])
     dur = int(audio["waveform"].shape[-1]) / sr
@@ -177,7 +192,7 @@ def validate_string(
         )
 
 
-def validate_container_format_is_mp4(video: VideoInput) -> None:
+def validate_container_format_is_mp4(video: Input.Video) -> None:
     """Validates video container format is MP4."""
     container_format = video.get_container_format()
     if container_format not in ["mp4", "mov,mp4,m4a,3gp,3g2,mj2"]:
@@ -194,8 +209,8 @@ def _ratio_from_tuple(r: tuple[float, float]) -> float:
 def _assert_ratio_bounds(
     ar: float,
     *,
-    min_ratio: Optional[tuple[float, float]] = None,
-    max_ratio: Optional[tuple[float, float]] = None,
+    min_ratio: tuple[float, float] | None = None,
+    max_ratio: tuple[float, float] | None = None,
     strict: bool = True,
 ) -> None:
     """Validate a numeric aspect ratio against optional min/max ratio bounds."""