for glm-4.1V update (#22000)

Signed-off-by: Isotr0py <2037008807@qq.com>
Signed-off-by: zRzRzRzRzRzRzR <2448370773@qq.com>
Co-authored-by: Isotr0py <2037008807@qq.com>

docs/models/supported_models.md

@@ -591,7 +591,8 @@ See [this page](generative_models.md) for more information on how to use generat
 | `Gemma3ForConditionalGeneration` | Gemma 3 | T + I<sup>+</sup> | `google/gemma-3-4b-it`, `google/gemma-3-27b-it`, etc. | ✅︎ | ✅︎ | ⚠️ |
 | `GLM4VForCausalLM`<sup>^</sup> | GLM-4V | T + I | `THUDM/glm-4v-9b`, `THUDM/cogagent-9b-20241220`, etc. | ✅︎ | ✅︎ | ✅︎ |
 | `Glm4vForConditionalGeneration` | GLM-4.1V-Thinking | T + I<sup>E+</sup> + V<sup>E+</sup> | `THUDM/GLM-4.1V-9B-Thinking`, etc. | ✅︎ | ✅︎ | ✅︎ |
-| `Glm4MoeForCausalLM` | GLM-4.5 | T + I<sup>E+</sup> + V<sup>E+</sup> | `THUDM/GLM-4.5`, etc. | ✅︎ | ✅︎ | ✅︎ |
+| `Glm4MoeForCausalLM` | GLM-4.5 | T + I<sup>E+</sup> + V<sup>E+</sup> | `zai-org/GLM-4.5`, etc. | ✅︎ | ✅︎ | ✅︎ |
+| `Glm4v_moeForConditionalGeneration` | GLM-4.5V | T + I<sup>E+</sup> + V<sup>E+</sup> | `zai-org/GLM-4.5V-Air`, etc. | ✅︎ | ✅︎ | ✅︎ |
 | `GraniteSpeechForConditionalGeneration` | Granite Speech | T + A | `ibm-granite/granite-speech-3.3-8b` | ✅︎ | ✅︎ | ✅︎ |
 | `H2OVLChatModel` | H2OVL | T + I<sup>E+</sup> | `h2oai/h2ovl-mississippi-800m`, `h2oai/h2ovl-mississippi-2b`, etc. | | ✅︎ | ✅︎ |
 | `Idefics3ForConditionalGeneration` | Idefics3 | T + I | `HuggingFaceM4/Idefics3-8B-Llama3`, etc. | ✅︎ | | ✅︎ |

tests/models/registry.py

@@ -377,9 +377,10 @@ _MULTIMODAL_EXAMPLE_MODELS = {
     "GLM4VForCausalLM": _HfExamplesInfo("THUDM/glm-4v-9b",
                                         trust_remote_code=True,
                                         hf_overrides={"architectures": ["GLM4VForCausalLM"]}),  # noqa: E501
-    "Glm4vForConditionalGeneration": _HfExamplesInfo("THUDM/GLM-4.1V-9B-Thinking", min_transformers_version="4.53"),  # noqa: E501
-    "Glm4MoeForCausalLM": _HfExamplesInfo("THUDM/GLM-4.5",
-                                          min_transformers_version="4.54",
+    "Glm4vForConditionalGeneration": _HfExamplesInfo("THUDM/GLM-4.1V-9B-Thinking"),  # noqa: E501
+    "Glm4MoeForCausalLM": _HfExamplesInfo("zai-org/GLM-4.5",
+                                          min_transformers_version="4.54"),   # noqa: E501
+    "Glm4v_moeForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.5V-Air",
                                           is_available_online=False),   # noqa: E501
     "H2OVLChatModel": _HfExamplesInfo("h2oai/h2ovl-mississippi-800m",
                                       extras={"2b": "h2oai/h2ovl-mississippi-2b"},  # noqa: E501
@@ -515,8 +516,8 @@ _SPECULATIVE_DECODING_EXAMPLE_MODELS = {
                                             is_available_online=False,
                                             speculative_model="openbmb/MiniCPM-2B-sft-bf16",
                                             tokenizer="openbmb/MiniCPM-2B-sft-bf16"),
-    "Glm4MoeMTPModel": _HfExamplesInfo("THUDM/GLM-4.5",
-                                        speculative_model="THUDM/GLM-4.5",
+    "Glm4MoeMTPModel": _HfExamplesInfo("zai-org/GLM-4.5",
+                                        speculative_model="zai-org/GLM-4.5",
                                         min_transformers_version="4.54",
                                         is_available_online=False),
     "MiMoMTPModel": _HfExamplesInfo("XiaomiMiMo/MiMo-7B-RL",

tests/tool_use/test_glm4_moe_tool_parser.py

@@ -12,7 +12,7 @@ from vllm.transformers_utils.tokenizer import get_tokenizer
 
 pytest.skip("skip glm4_moe parser test", allow_module_level=True)
 # Use a common model that is likely to be available
-MODEL = "THUDM/GLM-4.5"
+MODEL = "zai-org/GLM-4.5"
 
 
 @pytest.fixture(scope="module")

vllm/model_executor/layers/rotary_embedding.py

@@ -1096,7 +1096,7 @@ class MRotaryEmbedding(RotaryEmbedding):
                 audio_feature_lengths=audio_feature_lengths,
                 use_audio_in_video=use_audio_in_video,
             )
-        elif "glm4v" in hf_config.model_type:
+        elif hf_config.model_type in ["glm4v", "glm4v_moe"]:
             return cls._glm4v_get_input_positions_tensor(
                 input_tokens=input_tokens,
                 hf_config=hf_config,

vllm/model_executor/models/glm4_1v.py

@@ -37,8 +37,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 from einops import rearrange
 from transformers import BatchFeature
-from transformers.models.glm4v.configuration_glm4v import (Glm4vConfig,
-                                                           Glm4vVisionConfig)
+from transformers.models.glm4v.configuration_glm4v import Glm4vVisionConfig
 from transformers.models.glm4v.image_processing_glm4v import (
     Glm4vImageProcessor, smart_resize)
 from transformers.models.glm4v.video_processing_glm4v import (
@@ -801,7 +800,7 @@ class Glm4vVisionTransformer(nn.Module):
 class Glm4vProcessingInfo(BaseProcessingInfo):
 
     def get_hf_config(self):
-        return self.ctx.get_hf_config(Glm4vConfig)
+        return self.ctx.get_hf_config()
 
     def get_tokenizer(self):
         return self.ctx.tokenizer
@@ -1253,7 +1252,7 @@ class Glm4vForConditionalGeneration(nn.Module, SupportsMultiModal,
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
         super().__init__()
-        config: Glm4vConfig = vllm_config.model_config.hf_config
+        config = vllm_config.model_config.hf_config
         quant_config = vllm_config.quant_config
         multimodal_config = vllm_config.model_config.multimodal_config
 
@@ -1267,12 +1266,18 @@ class Glm4vForConditionalGeneration(nn.Module, SupportsMultiModal,
             prefix=maybe_prefix(prefix, "visual"),
         )
 
+        if config.model_type == "glm4v":
+            architectures = ["Glm4ForCausalLM"]
+        elif config.model_type == "glm4v_moe":
+            architectures = ["Glm4MoeForCausalLM"]
+        else:
+            architectures = None
+
         self.language_model = init_vllm_registered_model(
             vllm_config=vllm_config,
-            prefix=maybe_prefix(prefix, ""),
-            architectures=["Glm4ForCausalLM"],
-            hf_config=self.config.get_text_config(),
-        )
+            hf_config=config.text_config,
+            prefix=maybe_prefix(prefix, "language_model"),
+            architectures=architectures)
 
         self.make_empty_intermediate_tensors = (
             self.language_model.make_empty_intermediate_tensors)

vllm/model_executor/models/registry.py

@@ -206,6 +206,7 @@ _MULTIMODAL_MODELS = {
     "Gemma3ForConditionalGeneration": ("gemma3_mm", "Gemma3ForConditionalGeneration"),  # noqa: E501
     "GLM4VForCausalLM": ("glm4v", "GLM4VForCausalLM"),
     "Glm4vForConditionalGeneration": ("glm4_1v", "Glm4vForConditionalGeneration"),  # noqa: E501
+    "Glm4v_moeForConditionalGeneration": ("glm4_1v", "Glm4vForConditionalGeneration"),  # noqa: E501
     "GraniteSpeechForConditionalGeneration": ("granite_speech", "GraniteSpeechForConditionalGeneration"),  # noqa: E501
     "H2OVLChatModel": ("h2ovl", "H2OVLChatModel"),
     "InternVLChatModel": ("internvl", "InternVLChatModel"),