Merge remote-tracking branch 'origin/master' into yuhao/fix-loginterceptor-flush-oserror-update

comfy/model_base.py

@@ -1691,6 +1691,13 @@ class HiDreamO1(BaseModel):
         if text_input_ids is None or noise is None:
             return out
 
+        # handle area conds
+        area = kwargs.get("area", None)
+        if area is not None:
+            crop_h = min(noise.shape[-2] - area[2], area[0])
+            crop_w = min(noise.shape[-1] - area[3], area[1])
+            noise = torch.empty((noise.shape[0], 3, crop_h, crop_w), dtype=noise.dtype, device=noise.device)
+
         conds = build_extra_conds(
             text_input_ids, noise,
             ref_images=kwargs.get("reference_latents", None),

comfy/ops.py

@@ -1376,6 +1376,7 @@ def pick_operations(weight_dtype, compute_dtype, load_device=None, disable_fast_
         if not fp8_compute:
             disabled.add("float8_e4m3fn")
             disabled.add("float8_e5m2")
+        logging.info("Native ops: {} {}".format(", ".join(QUANT_ALGOS.keys() - disabled), ", emulated ops: {}".format(", ".join(disabled)) if len(disabled) > 0 else ""))
         return mixed_precision_ops(model_config.quant_config, compute_dtype, disabled=disabled)
 
     if (

comfy/text_encoders/qwen35.py

@@ -760,7 +760,7 @@ class Qwen35ImageTokenizer(sd1_clip.SD1Tokenizer):
     def tokenize_with_weights(self, text, return_word_ids=False, llama_template=None, images=[], prevent_empty_text=False, thinking=False, **kwargs):
         image = kwargs.get("image", None)
         if image is not None and len(images) == 0:
-            images = [image]
+            images = [image[i:i + 1] for i in range(image.shape[0])]
 
         skip_template = False
         if text.startswith('<|im_start|>'):
@@ -771,13 +771,16 @@ class Qwen35ImageTokenizer(sd1_clip.SD1Tokenizer):
         if skip_template:
             llama_text = text
         else:
-            if llama_template is None:
-                if len(images) > 0:
-                    llama_text = self.llama_template_images.format(text)
-                else:
-                    llama_text = self.llama_template.format(text)
+            if llama_template is not None:
+                template = llama_template
+            elif len(images) == 0:
+                template = self.llama_template
             else:
-                llama_text = llama_template.format(text)
+                template = self.llama_template_images
+                if len(images) > 1:
+                    vision_block = "<|vision_start|><|image_pad|><|vision_end|>"
+                    template = template.replace(vision_block, vision_block * len(images), 1)
+            llama_text = template.format(text)
             if not thinking:
                 llama_text += "<think>\n</think>\n"
 

comfy_api_nodes/nodes_anthropic.py

@@ -49,7 +49,7 @@ def _claude_model_inputs():
             min=0.0,
             max=1.0,
             step=0.01,
-            tooltip="Controls randomness. 0.0 is deterministic, 1.0 is most random.",
+            tooltip="Controls randomness. 0.0 is deterministic, 1.0 is most random. Ignored for Opus 4.7.",
             advanced=True,
         ),
     ]
@@ -208,7 +208,7 @@ class ClaudeNode(IO.ComfyNode):
         validate_string(prompt, strip_whitespace=True, min_length=1)
         model_label = model["model"]
         max_tokens = model["max_tokens"]
-        temperature = model["temperature"]
+        temperature = None if model_label == "Opus 4.7" else model["temperature"]
 
         image_tensors: list[Input.Image] = [t for t in (images or {}).values() if t is not None]
         if sum(get_number_of_images(t) for t in image_tensors) > CLAUDE_MAX_IMAGES:

execution.py

@@ -626,7 +626,7 @@ async def execute(server, dynprompt, caches, current_item, extra_data, executed,
 
         if comfy.model_management.is_oom(ex):
             tips = "This error means you ran out of memory on your GPU.\n\nTIPS: If the workflow worked before you might have accidentally set the batch_size to a large number."
-            logging.info("Memory summary: {}".format(comfy.model_management.debug_memory_summary()))
+            logging.info("Memory summary:\n{}".format(comfy.model_management.debug_memory_summary()))
             logging.error("Got an OOM, unloading all loaded models.")
             comfy.model_management.unload_all_models()
         elif isinstance(ex, RuntimeError) and ("mat1 and mat2 shapes" in str(ex)) and "Sampler" in class_type: