feat(memory)!: Uses the new MemoryEntry schema for all memory related components.

BREAKING CHANGE. This commit changes all memory related interface to using the newly introduced MemoryEntry class.

PiperOrigin-RevId: 758464887

src/google/adk/tools/_memory_entry_utils.py

@@ -0,0 +1,30 @@
+# Copyright 2025 Google LLC
+#
+# 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 __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+  from ..memory.memory_entry import MemoryEntry
+
+
+def extract_text(memory: MemoryEntry, splitter: str = ' ') -> str:
+  """Extracts the text from the memory entry."""
+  if not memory.content.parts:
+    return ''
+  return splitter.join(
+      [part.text for part in memory.content.parts if part.text]
+  )

src/google/adk/tools/load_memory_tool.py

@@ -17,19 +17,25 @@ from __future__ import annotations
 from typing import TYPE_CHECKING
 
 from google.genai import types
+from openai import BaseModel
+from pydantic import Field
 from typing_extensions import override
 
+from ..memory.memory_entry import MemoryEntry
 from .function_tool import FunctionTool
 from .tool_context import ToolContext
 
 if TYPE_CHECKING:
-  from ..memory.base_memory_service import MemoryResult
   from ..models import LlmRequest
 
 
+class LoadMemoryResponse(BaseModel):
+  memories: list[MemoryEntry] = Field(default_factory=list)
+
+
 async def load_memory(
     query: str, tool_context: ToolContext
-) -> 'list[MemoryResult]':
+) -> LoadMemoryResponse:
   """Loads the memory for the current user.
 
   Args:
@@ -38,12 +44,15 @@ async def load_memory(
   Returns:
     A list of memory results.
   """
-  response = await tool_context.search_memory(query)
-  return response.memories
+  search_memory_response = await tool_context.search_memory(query)
+  return LoadMemoryResponse(memories=search_memory_response.memories)
 
 
 class LoadMemoryTool(FunctionTool):
-  """A tool that loads the memory for the current user."""
+  """A tool that loads the memory for the current user.
+
+  NOTE: Currently this tool only uses text part from the memory.
+  """
 
   def __init__(self):
     super().__init__(load_memory)

src/google/adk/tools/preload_memory_tool.py

@@ -14,11 +14,11 @@
 
 from __future__ import annotations
 
-from datetime import datetime
 from typing import TYPE_CHECKING
 
 from typing_extensions import override
 
+from . import _memory_entry_utils
 from .base_tool import BaseTool
 from .tool_context import ToolContext
 
@@ -27,7 +27,10 @@ if TYPE_CHECKING:
 
 
 class PreloadMemoryTool(BaseTool):
-  """A tool that preloads the memory for the current user."""
+  """A tool that preloads the memory for the current user.
+
+  NOTE: Currently this tool only uses text part from the memory.
+  """
 
   def __init__(self):
     # Name and description are not used because this tool only
@@ -41,29 +44,35 @@ class PreloadMemoryTool(BaseTool):
       tool_context: ToolContext,
       llm_request: LlmRequest,
   ) -> None:
-    parts = tool_context.user_content.parts
-    if not parts or not parts[0].text:
+    user_content = tool_context.user_content
+    if (
+        not user_content
+        or not user_content.parts
+        or not user_content.parts[0].text
+    ):
       return
-    query = parts[0].text
-    response = await tool_context.search_memory(query)
+
+    user_query: str = user_content.parts[0].text
+    response = await tool_context.search_memory(user_query)
     if not response.memories:
       return
-    memory_text = ''
+
+    memory_text_lines = []
     for memory in response.memories:
-      time_str = datetime.fromtimestamp(memory.events[0].timestamp).isoformat()
-      memory_text += f'Time: {time_str}\n'
-      for event in memory.events:
-        # TODO: support multi-part content.
-        if (
-            event.content
-            and event.content.parts
-            and event.content.parts[0].text
-        ):
-          memory_text += f'{event.author}: {event.content.parts[0].text}\n'
+      if time_str := (f'Time: {memory.timestamp}' if memory.timestamp else ''):
+        memory_text_lines.append(time_str)
+      if memory_text := _memory_entry_utils.extract_text(memory):
+        memory_text_lines.append(
+            f'{memory.author}: {memory_text}' if memory.author else memory_text
+        )
+    if not memory_text_lines:
+      return
+
+    full_memory_text = '\n'.join(memory_text_lines)
     si = f"""The following content is from your previous conversations with the user.
 They may be useful for answering the user's current query.
 <PAST_CONVERSATIONS>
-{memory_text}
+{full_memory_text}
 </PAST_CONVERSATIONS>
 """
     llm_request.append_instructions([si])