[LLM] First commit the llm deployment code

fastdeploy/input/preprocess.py

@@ -0,0 +1,59 @@
+"""
+# Copyright (c) 2025  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+
+from fastdeploy.engine.config import ModelConfig
+
+class InputPreprocessor:
+    """
+        Args:
+        model_name_or_path (str):
+            Model name or path to the pretrained model. If a model name is provided, it should be a
+            key in the Hugging Face Transformers' model registry (https://huggingface.co/models).
+            The model will be downloaded from the Hugging Face model hub if necessary.
+            If a path is provided, the model will be loaded from that path.
+        enable_mm (bool, optional):
+            Whether to use the multi-modal model processor. Defaults to False.
+
+        Raises:
+            ValueError:
+                If the model name is not found in the Hugging Face Transformers' model registry and the path does not
+                exist.
+    """
+    def __init__(
+        self,
+        model_name_or_path: str,
+        enable_mm: bool = False,
+    ) -> None:
+
+        self.model_name_or_path = model_name_or_path
+        self.enable_mm = enable_mm
+
+
+    def create_processor(self):
+        """
+            创建数据处理器。如果启用了多模态注册表，则使用该表中的模型；否则，使用传递给构造函数的模型名称或路径。
+        返回值：DataProcessor（如果不启用多模态注册表）或MultiModalRegistry.Processor（如果启用多模态注册表）。
+
+        Args:
+            无参数。
+
+        Returns:
+            DataProcessor or MultiModalRegistry.Processor (Union[DataProcessor, MultiModalRegistry.Processor]): 数据处理器。
+        """
+        architectures = ModelConfig(self.model_name_or_path).architectures
+        from fastdeploy.input.text_processor import DataProcessor
+        self.processor = DataProcessor(model_name_or_path=self.model_name_or_path)
+        return self.processor