[LLM] First commit the llm deployment code

fastdeploy/engine/kv_cache_interface.py

@@ -0,0 +1,53 @@
+"""
+# 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.
+"""
+import copy
+from dataclasses import dataclass
+from typing import list
+
+from typing_extensions import Self
+
+
+@dataclass
+class KVCacheSpec:
+    """
+    A base class for specifying the KV cache format of one layer.
+    """
+    # number of tokens in a block
+    block_size: int
+    # the memory size used by each block in bytes.
+    block_memory_used: int
+
+    @classmethod
+    def merge(cls, specs: list[Self]) -> Self:
+        """
+        Merge a list of KVCacheSpec objects into a single KVCacheSpec object.
+        """
+        # check list
+        assert all(
+            (spec.block_size == specs[0].block_size
+             and spec.block_memory_used == specs[0].block_memory_used)
+            for spec in specs[1:]), (
+                "All layers in the model must share the same block_size.")
+
+        return copy.deepcopy(specs[0])
+
+
+@dataclass
+class AttentionSpec(KVCacheSpec):
+    """ """
+    num_kv_heads: int
+    head_size: int
+    dtype: str