Merge branch 'comfyanonymous:master' into master

comfy/ldm/chroma/model.py

@@ -179,7 +179,10 @@ class Chroma(nn.Module):
         pe = self.pe_embedder(ids)
 
         blocks_replace = patches_replace.get("dit", {})
+        transformer_options["total_blocks"] = len(self.double_blocks)
+        transformer_options["block_type"] = "double"
         for i, block in enumerate(self.double_blocks):
+            transformer_options["block_index"] = i
             if i not in self.skip_mmdit:
                 double_mod = (
                     self.get_modulations(mod_vectors, "double_img", idx=i),
@@ -222,7 +225,10 @@ class Chroma(nn.Module):
 
         img = torch.cat((txt, img), 1)
 
+        transformer_options["total_blocks"] = len(self.single_blocks)
+        transformer_options["block_type"] = "single"
         for i, block in enumerate(self.single_blocks):
+            transformer_options["block_index"] = i
             if i not in self.skip_dit:
                 single_mod = self.get_modulations(mod_vectors, "single", idx=i)
                 if ("single_block", i) in blocks_replace:

comfy/ldm/hunyuan_video/model.py

@@ -389,7 +389,10 @@ class HunyuanVideo(nn.Module):
             attn_mask = None
 
         blocks_replace = patches_replace.get("dit", {})
+        transformer_options["total_blocks"] = len(self.double_blocks)
+        transformer_options["block_type"] = "double"
         for i, block in enumerate(self.double_blocks):
+            transformer_options["block_index"] = i
             if ("double_block", i) in blocks_replace:
                 def block_wrap(args):
                     out = {}
@@ -411,7 +414,10 @@ class HunyuanVideo(nn.Module):
 
         img = torch.cat((img, txt), 1)
 
+        transformer_options["total_blocks"] = len(self.single_blocks)
+        transformer_options["block_type"] = "single"
         for i, block in enumerate(self.single_blocks):
+            transformer_options["block_index"] = i
             if ("single_block", i) in blocks_replace:
                 def block_wrap(args):
                     out = {}

comfy/ldm/qwen_image/model.py

@@ -439,7 +439,10 @@ class QwenImageTransformer2DModel(nn.Module):
         patches = transformer_options.get("patches", {})
         blocks_replace = patches_replace.get("dit", {})
 
+        transformer_options["total_blocks"] = len(self.transformer_blocks)
+        transformer_options["block_type"] = "double"
         for i, block in enumerate(self.transformer_blocks):
+            transformer_options["block_index"] = i
             if ("double_block", i) in blocks_replace:
                 def block_wrap(args):
                     out = {}

comfy_api/latest/_input/video_types.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 from abc import ABC, abstractmethod
+from fractions import Fraction
 from typing import Optional, Union, IO
 import io
 import av
@@ -72,6 +73,33 @@ class VideoInput(ABC):
         frame_count = components.images.shape[0]
         return float(frame_count / components.frame_rate)
 
+    def get_frame_count(self) -> int:
+        """
+        Returns the number of frames in the video.
+
+        Default implementation uses :meth:`get_components`, which may require
+        loading all frames into memory. File-based implementations should
+        override this method and use container/stream metadata instead.
+
+        Returns:
+            Total number of frames as an integer.
+        """
+        return int(self.get_components().images.shape[0])
+
+    def get_frame_rate(self) -> Fraction:
+        """
+        Returns the frame rate of the video.
+
+        Default implementation materializes the video into memory via
+        `get_components()`. Subclasses that can inspect the underlying
+        container (e.g. `VideoFromFile`) should override this with a more
+        efficient implementation.
+
+        Returns:
+            Frame rate as a Fraction.
+        """
+        return self.get_components().frame_rate
+
     def get_container_format(self) -> str:
         """
         Returns the container format of the video (e.g., 'mp4', 'mov', 'avi').

comfy_api/latest/_input_impl/video_types.py

@@ -121,6 +121,71 @@ class VideoFromFile(VideoInput):
 
         raise ValueError(f"Could not determine duration for file '{self.__file}'")
 
+    def get_frame_count(self) -> int:
+        """
+        Returns the number of frames in the video without materializing them as
+        torch tensors.
+        """
+        if isinstance(self.__file, io.BytesIO):
+            self.__file.seek(0)
+
+        with av.open(self.__file, mode="r") as container:
+            video_stream = self._get_first_video_stream(container)
+            # 1. Prefer the frames field if available
+            if video_stream.frames and video_stream.frames > 0:
+                return int(video_stream.frames)
+
+            # 2. Try to estimate from duration and average_rate using only metadata
+            if container.duration is not None and video_stream.average_rate:
+                duration_seconds = float(container.duration / av.time_base)
+                estimated_frames = int(round(duration_seconds * float(video_stream.average_rate)))
+                if estimated_frames > 0:
+                    return estimated_frames
+
+            if (
+                getattr(video_stream, "duration", None) is not None
+                and getattr(video_stream, "time_base", None) is not None
+                and video_stream.average_rate
+            ):
+                duration_seconds = float(video_stream.duration * video_stream.time_base)
+                estimated_frames = int(round(duration_seconds * float(video_stream.average_rate)))
+                if estimated_frames > 0:
+                    return estimated_frames
+
+            # 3. Last resort: decode frames and count them (streaming)
+            frame_count = 0
+            container.seek(0)
+            for packet in container.demux(video_stream):
+                for _ in packet.decode():
+                    frame_count += 1
+
+            if frame_count == 0:
+                raise ValueError(f"Could not determine frame count for file '{self.__file}'")
+            return frame_count
+
+    def get_frame_rate(self) -> Fraction:
+        """
+        Returns the average frame rate of the video using container metadata
+        without decoding all frames.
+        """
+        if isinstance(self.__file, io.BytesIO):
+            self.__file.seek(0)
+
+        with av.open(self.__file, mode="r") as container:
+            video_stream = self._get_first_video_stream(container)
+            # Preferred: use PyAV's average_rate (usually already a Fraction-like)
+            if video_stream.average_rate:
+                return Fraction(video_stream.average_rate)
+
+            # Fallback: estimate from frames + duration if available
+            if video_stream.frames and container.duration:
+                duration_seconds = float(container.duration / av.time_base)
+                if duration_seconds > 0:
+                    return Fraction(video_stream.frames / duration_seconds).limit_denominator()
+
+            # Last resort: match get_components_internal default
+            return Fraction(1)
+
     def get_container_format(self) -> str:
         """
         Returns the container format of the video (e.g., 'mp4', 'mov', 'avi').
@@ -238,6 +303,13 @@ class VideoFromFile(VideoInput):
                         packet.stream = stream_map[packet.stream]
                         output_container.mux(packet)
 
+    def _get_first_video_stream(self, container: InputContainer):
+        video_stream = next((s for s in container.streams if s.type == "video"), None)
+        if video_stream is None:
+            raise ValueError(f"No video stream found in file '{self.__file}'")
+        return video_stream
+
+
 class VideoFromComponents(VideoInput):
     """
     Class representing video input from tensors.

comfy_api_nodes/apis/gemini_api.py

@@ -113,9 +113,9 @@ class GeminiGenerationConfig(BaseModel):
     maxOutputTokens: int | None = Field(None, ge=16, le=8192)
     seed: int | None = Field(None)
     stopSequences: list[str] | None = Field(None)
-    temperature: float | None = Field(1, ge=0.0, le=2.0)
-    topK: int | None = Field(40, ge=1)
-    topP: float | None = Field(0.95, ge=0.0, le=1.0)
+    temperature: float | None = Field(None, ge=0.0, le=2.0)
+    topK: int | None = Field(None, ge=1)
+    topP: float | None = Field(None, ge=0.0, le=1.0)
 
 
 class GeminiImageConfig(BaseModel):

comfy_api_nodes/nodes_gemini.py

@@ -104,14 +104,14 @@ def get_parts_by_type(response: GeminiGenerateContentResponse, part_type: Litera
         List of response parts matching the requested type.
     """
     if response.candidates is None:
-        if response.promptFeedback.blockReason:
+        if response.promptFeedback and response.promptFeedback.blockReason:
             feedback = response.promptFeedback
             raise ValueError(
                 f"Gemini API blocked the request. Reason: {feedback.blockReason} ({feedback.blockReasonMessage})"
             )
-        raise NotImplementedError(
-            "Gemini returned no response candidates. "
-            "Please report to ComfyUI repository with the example of workflow to reproduce this."
+        raise ValueError(
+            "Gemini API returned no response candidates. If you are using the `IMAGE` modality, "
+            "try changing it to `IMAGE+TEXT` to view the model's reasoning and understand why image generation failed."
         )
     parts = []
     for part in response.candidates[0].content.parts:
@@ -182,11 +182,12 @@ def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | N
     else:
         return None
     final_price = response.usageMetadata.promptTokenCount * input_tokens_price
-    for i in response.usageMetadata.candidatesTokensDetails:
-        if i.modality == Modality.IMAGE:
-            final_price += output_image_tokens_price * i.tokenCount  # for Nano Banana models
-        else:
-            final_price += output_text_tokens_price * i.tokenCount
+    if response.usageMetadata.candidatesTokensDetails:
+        for i in response.usageMetadata.candidatesTokensDetails:
+            if i.modality == Modality.IMAGE:
+                final_price += output_image_tokens_price * i.tokenCount  # for Nano Banana models
+            else:
+                final_price += output_text_tokens_price * i.tokenCount
     if response.usageMetadata.thoughtsTokenCount:
         final_price += output_text_tokens_price * response.usageMetadata.thoughtsTokenCount
     return final_price / 1_000_000.0
@@ -645,7 +646,7 @@ class GeminiImage2(IO.ComfyNode):
                     options=["auto", "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"],
                     default="auto",
                     tooltip="If set to 'auto', matches your input image's aspect ratio; "
-                    "if no image is provided, generates a 1:1 square.",
+                    "if no image is provided, a 16:9 square is usually generated.",
                 ),
                 IO.Combo.Input(
                     "resolution",

comfy_api_nodes/nodes_topaz.py

@@ -5,8 +5,7 @@ import aiohttp
 import torch
 from typing_extensions import override
 
-from comfy_api.input.video_types import VideoInput
-from comfy_api.latest import IO, ComfyExtension
+from comfy_api.latest import IO, ComfyExtension, Input
 from comfy_api_nodes.apis import topaz_api
 from comfy_api_nodes.util import (
     ApiEndpoint,
@@ -282,7 +281,7 @@ class TopazVideoEnhance(IO.ComfyNode):
     @classmethod
     async def execute(
         cls,
-        video: VideoInput,
+        video: Input.Video,
         upscaler_enabled: bool,
         upscaler_model: str,
         upscaler_resolution: str,
@@ -297,12 +296,10 @@ class TopazVideoEnhance(IO.ComfyNode):
     ) -> IO.NodeOutput:
         if upscaler_enabled is False and interpolation_enabled is False:
             raise ValueError("There is nothing to do: both upscaling and interpolation are disabled.")
-        src_width, src_height = video.get_dimensions()
-        video_components = video.get_components()
-        src_frame_rate = int(video_components.frame_rate)
-        duration_sec = video.get_duration()
-        estimated_frames = int(duration_sec * src_frame_rate)
         validate_container_format_is_mp4(video)
+        src_width, src_height = video.get_dimensions()
+        src_frame_rate = int(video.get_frame_rate())
+        duration_sec = video.get_duration()
         src_video_stream = video.get_stream_source()
         target_width = src_width
         target_height = src_height
@@ -338,7 +335,7 @@ class TopazVideoEnhance(IO.ComfyNode):
                     container="mp4",
                     size=get_fs_object_size(src_video_stream),
                     duration=int(duration_sec),
-                    frameCount=estimated_frames,
+                    frameCount=video.get_frame_count(),
                     frameRate=src_frame_rate,
                     resolution=topaz_api.Resolution(width=src_width, height=src_height),
                 ),