Support Dots.ocr model (#11071)

python/sglang/srt/configs/__init__.py

@@ -1,6 +1,7 @@
 from sglang.srt.configs.chatglm import ChatGLMConfig
 from sglang.srt.configs.dbrx import DbrxConfig
 from sglang.srt.configs.deepseekvl2 import DeepseekVL2Config
+from sglang.srt.configs.dots_ocr import DotsOCRConfig
 from sglang.srt.configs.dots_vlm import DotsVLMConfig
 from sglang.srt.configs.exaone import ExaoneConfig
 from sglang.srt.configs.janus_pro import MultiModalityConfig
@@ -28,4 +29,5 @@ __all__ = [
     "Step3VisionEncoderConfig",
     "Qwen3NextConfig",
     "DotsVLMConfig",
+    "DotsOCRConfig",
 ]

python/sglang/srt/configs/dots_ocr.py

@@ -0,0 +1,64 @@
+from typing import Optional
+
+from transformers import AutoProcessor, Qwen2_5_VLProcessor
+from transformers.image_processing_utils import BaseImageProcessor
+from transformers.models.qwen2 import Qwen2Config
+
+from sglang.srt.configs.dots_vlm import DotsVisionConfig
+
+
+class DotsOCRConfig(Qwen2Config):
+    model_type = "dots_ocr"
+
+    def __init__(
+        self,
+        image_token_id=151665,
+        video_token_id=151656,
+        vision_config: Optional[dict] = None,
+        *args,
+        **kwargs
+    ):
+        super().__init__(*args, **kwargs)
+        self.image_token_id = image_token_id
+        self.video_token_id = video_token_id
+        self.vision_config = DotsVisionConfig(**(vision_config or {}))
+
+    def save_pretrained(self, save_directory, **kwargs):
+        self._auto_class = None
+        super().save_pretrained(save_directory, **kwargs)
+
+
+class DummyVideoProcessor(BaseImageProcessor):
+    model_input_names = ["pixel_values"]
+
+    def __call__(self, *args, **kwargs):
+        return None
+
+
+class DotsVLProcessor(Qwen2_5_VLProcessor):
+    def __init__(
+        self,
+        image_processor=None,
+        tokenizer=None,
+        video_processor=None,
+        chat_template=None,
+        **kwargs
+    ):
+        if video_processor is None:
+            video_processor = DummyVideoProcessor()
+        super().__init__(
+            image_processor, tokenizer, video_processor, chat_template=chat_template
+        )
+        self.image_token = (
+            "<|imgpad|>"
+            if not hasattr(tokenizer, "image_token")
+            else tokenizer.image_token
+        )
+        self.image_token_id = (
+            tokenizer.image_token_id
+            if getattr(tokenizer, "image_token_id", None) is not None
+            else tokenizer.convert_tokens_to_ids(self.image_token)
+        )
+
+
+AutoProcessor.register(DotsOCRConfig, DotsVLProcessor)

python/sglang/srt/configs/model_config.py

@@ -778,6 +778,7 @@ multimodal_model_archs = [
     "VILAForConditionalGeneration",
     "Step3VLForConditionalGeneration",
     "DotsVLMForCausalLM",
+    "DotsOCRForCausalLM",
     "Sarashina2VisionForCausalLM",
 ]