[Feature] remove dependency on enable_mm and refine multimodal's code (#3014)

* remove dependency on enable_mm

* fix codestyle check error

* fix codestyle check error

* update docs

* resolve conflicts on model config

* fix unit test error

* fix code style check error

---------

Co-authored-by: shige <1021937542@qq.com>
Co-authored-by: Jiang-Jia-Jun <163579578+Jiang-Jia-Jun@users.noreply.github.com>

fastdeploy/entrypoints/engine_client.py

@@ -19,9 +19,11 @@ import uuid
 
 import numpy as np
 
+from fastdeploy.engine.config import ModelConfig
 from fastdeploy.input.preprocess import InputPreprocessor
 from fastdeploy.inter_communicator import IPCSignal, ZmqClient
 from fastdeploy.metrics.work_metrics import work_process_metrics
+from fastdeploy.multimodal.registry import MultimodalRegistry
 from fastdeploy.platforms import current_platform
 from fastdeploy.utils import EngineError, api_server_logger
 
@@ -33,26 +35,34 @@ class EngineClient:
 
     def __init__(
         self,
+        model_name_or_path,
         tokenizer,
         max_model_len,
         tensor_parallel_size,
         pid,
         limit_mm_per_prompt,
         mm_processor_kwargs,
-        enable_mm=False,
+        # enable_mm=False,
         reasoning_parser=None,
         data_parallel_size=1,
         enable_logprob=False,
     ):
+        import fastdeploy.model_executor.models  # noqa: F401
+
+        architectures = ModelConfig({"model": model_name_or_path}).architectures[0]
+        if MultimodalRegistry.contains_model(architectures):
+            self.enable_mm = True
+        else:
+            self.enable_mm = False
+
         input_processor = InputPreprocessor(
             tokenizer,
             reasoning_parser,
             limit_mm_per_prompt,
             mm_processor_kwargs,
-            enable_mm,
+            self.enable_mm,
         )
         self.enable_logprob = enable_logprob
-        self.enable_mm = enable_mm
         self.reasoning_parser = reasoning_parser
         self.data_processor = input_processor.create_processor()
         self.max_model_len = max_model_len