Unify the model type checking (#1905)

python/sglang/srt/managers/tokenizer_manager.py

@@ -18,7 +18,6 @@ limitations under the License.
 import asyncio
 import copy
 import dataclasses
-import json
 import logging
 import os
 import signal
@@ -31,12 +30,8 @@ import zmq
 import zmq.asyncio
 from fastapi import BackgroundTasks
 
-from sglang.srt.hf_transformers_utils import (
-    get_config,
-    get_context_length,
-    get_processor,
-    get_tokenizer,
-)
+from sglang.srt.configs.model_config import ModelConfig
+from sglang.srt.hf_transformers_utils import get_processor, get_tokenizer
 from sglang.srt.managers.image_processor import (
     get_dummy_image_processor,
     get_image_processor,
@@ -59,12 +54,7 @@ from sglang.srt.managers.io_struct import (
 )
 from sglang.srt.sampling.sampling_params import SamplingParams
 from sglang.srt.server_args import PortArgs, ServerArgs
-from sglang.srt.utils import (
-    get_zmq_socket,
-    is_generation_model,
-    is_multimodal_model,
-    kill_child_process,
-)
+from sglang.srt.utils import get_zmq_socket, kill_child_process
 
 asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
 
@@ -103,18 +93,17 @@ class TokenizerManager:
         # Read model args
         self.model_path = server_args.model_path
         self.served_model_name = server_args.served_model_name
-        self.hf_config = get_config(
-            self.model_path,
+        self.model_config = ModelConfig(
+            server_args.model_path,
             trust_remote_code=server_args.trust_remote_code,
-            model_override_args=json.loads(server_args.json_model_override_args),
-        )
-        self.is_generation = is_generation_model(
-            self.hf_config.architectures, self.server_args.is_embedding
-        )
-        self.context_len = server_args.context_length or get_context_length(
-            self.hf_config
+            context_length=server_args.context_length,
+            model_override_args=server_args.json_model_override_args,
+            is_embedding=server_args.is_embedding,
         )
 
+        self.is_generation = self.model_config.is_generation
+        self.context_len = self.model_config.context_len
+
         # Create image processor placeholder
         self.image_processor = get_dummy_image_processor()
 
@@ -122,7 +111,7 @@ class TokenizerManager:
         if server_args.skip_tokenizer_init:
             self.tokenizer = self.processor = None
         else:
-            if is_multimodal_model(self.hf_config.architectures):
+            if self.model_config.is_multimodal:
                 self.processor = get_processor(
                     server_args.tokenizer_path,
                     tokenizer_mode=server_args.tokenizer_mode,
@@ -133,7 +122,7 @@ class TokenizerManager:
 
                 # We want to parallelize the image pre-processing so we create an executor for it
                 self.image_processor = get_image_processor(
-                    self.hf_config, server_args, self.processor
+                    self.model_config.hf_config, server_args, self.processor
                 )
             else:
                 self.tokenizer = get_tokenizer(