chore(ltm): optimize memory structure

.gitleaks.toml

@@ -73,4 +73,4 @@ description = "Empty environment variables with KEY pattern"
 regex = '''os\.environ\[".*?KEY"\]\s*=\s*".+"'''
 
 [allowlist]
-paths = ["requirements.txt"]
+paths = ["requirements.txt", "tests"]

docs/content/6.memory/3.long-term-memory.md

@@ -7,13 +7,13 @@ navigation:
 
 ## 使用方法
 
-VeADK 的长期记忆通常存储在数据库中，通过如下方式定义一个长期记忆：
+VeADK 的长期记忆通常存储在数据库中，你需要在初始化长期记忆时定义 `index` 来指定后端索引名称。通过如下方式定义一个长期记忆：
 
 ```python
 from veadk.memory.long_term_memory import LongTermMemory
 
-# 由于长期记忆需要构建索引，因此你必须在初始化长期记忆时定义 `app_name` 以及 `user_id`
-long_term_memory = LongTermMemory(app_name="my_app_name", user_id="user_id")
+# 
+long_term_memory = LongTermMemory(index="my_index")
 ```
 
 通过如下例子说明长期记忆：
@@ -32,7 +32,7 @@ user_id = "temp_user"
 teaching_session_id = "teaching_session"
 student_session_id = "student_session"
 
-long_term_memory = LongTermMemory(backend="local", app_name=app_name, user_id=user_id)
+long_term_memory = LongTermMemory(backend="local", index=app_name)
 
 agent = Agent(long_term_memory=long_term_memory)
 
@@ -90,8 +90,4 @@ print(response)
   ::field{name="app_name" type="string"}
   Agent 应用名称，用于多应用区分。默认空字符串。
   ::
-
-  ::field{name="user_id" type="string"}
-  Agent 用户 ID，用于区分不同用户的长期记忆。默认空字符串。
-  ::
 ::

docs/content/7.knowledgebase/1.knowledgebase.md

@@ -9,7 +9,7 @@ navigation:
 
 VeADK 基于 Llama-index 作为知识库的主要处理入口。开发者可上传文本、文件、目录，我们会为您进行自动切片。
 
-创建知识库时，您必须要提供您的 `app_name`（将会用来自动构建索引名称），或指定一个知识库的索引：
+创建知识库时，您必须要提供您的知识库后端索引名称 `index`，或指定 `app_name` 来作为索引名称：
 
 ```python
 from veadk.knowledgebase import KnowledgeBase

tests/test_agent.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
 from unittest.mock import Mock, patch
 
 from google.adk.agents.llm_agent import LlmAgent
@@ -33,11 +34,10 @@
 
 
 def test_agent():
-    knowledgebase = KnowledgeBase(
-        index="test_index",
-        backend="local",
-        backend_config={"embedding_config": {"api_key": "test"}},
-    )
+    os.environ["MODEL_EMBEDDING_API_KEY"] = "mocked_api_key"
+
+    knowledgebase = KnowledgeBase(index="test_index", backend="local")
+
     long_term_memory = LongTermMemory(backend="local")
     tracer = OpentelemetryTracer()
 
@@ -69,8 +69,6 @@ def test_agent():
 
     assert agent.knowledgebase == knowledgebase
     assert agent.knowledgebase.backend == "local"  # type: ignore
-    assert load_knowledgebase_tool.knowledgebase == agent.knowledgebase
-    assert load_knowledgebase_tool.load_knowledgebase_tool in agent.tools
 
     assert agent.long_term_memory.backend == "local"  # type: ignore
     assert load_memory in agent.tools

tests/test_knowledgebase.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
 
 import pytest
 
@@ -21,11 +22,9 @@
 
 @pytest.mark.asyncio
 async def test_knowledgebase():
+    os.environ["MODEL_EMBEDDING_API_KEY"] = "mocked_api_key"
+
     app_name = "kb_test_app"
-    kb = KnowledgeBase(
-        backend="local",
-        app_name=app_name,
-        backend_config={"embedding_config": {"api_key": "test"}},
-    )
+    kb = KnowledgeBase(backend="local", app_name=app_name)
 
     assert isinstance(kb._backend, InMemoryKnowledgeBackend)

tests/test_long_term_memory.py

@@ -13,23 +13,20 @@
 # limitations under the License.
 
 
+import os
+
 import pytest
 from google.adk.tools import load_memory
 
 from veadk.agent import Agent
 from veadk.memory.long_term_memory import LongTermMemory
 
-app_name = "test_ltm"
-user_id = "test_user"
-
 
 @pytest.mark.asyncio
 async def test_long_term_memory():
-    long_term_memory = LongTermMemory(
-        backend="local",
-        # app_name=app_name,
-        # user_id=user_id,
-    )
+    os.environ["MODEL_EMBEDDING_API_KEY"] = "mocked_api_key"
+    long_term_memory = LongTermMemory(backend="local")
+
     agent = Agent(
         name="all_name",
         model_name="test_model_name",
@@ -43,7 +40,8 @@ async def test_long_term_memory():
 
     assert load_memory in agent.tools, "load_memory tool not found in agent tools"
 
-    assert not agent.long_term_memory._backend
+    assert agent.long_term_memory
+    assert agent.long_term_memory._backend
 
     # assert agent.long_term_memory._backend.index == build_long_term_memory_index(
     #     app_name, user_id

tests/test_runner.py

@@ -12,16 +12,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 from google.genai import types
 
 from veadk.agent import Agent
 from veadk.memory.long_term_memory import LongTermMemory
 from veadk.memory.short_term_memory import ShortTermMemory
-from veadk.runner import Runner
-
 
 # Import the standalone function instead of accessing as class method
-from veadk.runner import _convert_messages
+from veadk.runner import Runner, _convert_messages
 
 
 def _test_convert_messages(runner):
@@ -67,6 +67,8 @@ def _test_convert_messages(runner):
 
 def test_runner():
     """Test Runner class initialization and core properties"""
+    os.environ["MODEL_EMBEDDING_API_KEY"] = "mocked_api_key"
+
     short_term_memory = ShortTermMemory()
     long_term_memory = LongTermMemory(backend="local")
     agent = Agent(

veadk/agent.py

@@ -133,10 +133,14 @@ def model_post_init(self, __context: Any) -> None:
             )
 
         if self.knowledgebase:
-            from veadk.tools import load_knowledgebase_tool
+            from veadk.tools.builtin_tools.load_knowledgebase import (
+                LoadKnowledgebaseTool,
+            )
 
-            load_knowledgebase_tool.knowledgebase = self.knowledgebase
-            self.tools.append(load_knowledgebase_tool.load_knowledgebase_tool)
+            load_knowledgebase_tool = LoadKnowledgebaseTool(
+                knowledgebase=self.knowledgebase
+            )
+            self.tools.append(load_knowledgebase_tool)
 
         if self.long_term_memory is not None:
             from google.adk.tools import load_memory

veadk/knowledgebase/knowledgebase.py

@@ -12,10 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from typing import Any, Callable, Literal
+from __future__ import annotations
+
+from typing import Any, Callable, Literal, Union
 
 from pydantic import BaseModel, Field
-from typing_extensions import Union
 
 from veadk.knowledgebase.backends.base_backend import BaseKnowledgebaseBackend
 from veadk.knowledgebase.entry import KnowledgebaseEntry
@@ -54,11 +55,11 @@ def _get_backend_cls(backend: str) -> type[BaseKnowledgebaseBackend]:
     raise ValueError(f"Unsupported knowledgebase backend: {backend}")
 
 
-def build_knowledgebase_index(app_name: str):
-    return f"veadk_kb_{app_name}"
+class KnowledgeBase(BaseModel):
+    name: str = "user_knowledgebase"
 
+    description: str = "This knowledgebase stores some user-related information."
 
-class KnowledgeBase(BaseModel):
     backend: Union[
         Literal["local", "opensearch", "viking", "redis"], BaseKnowledgebaseBackend
     ] = "local"
@@ -73,9 +74,7 @@ class KnowledgeBase(BaseModel):
     """Configuration for the backend"""
 
     top_k: int = 10
-    """Number of top similar documents to retrieve during search.
-
-    Default is 10."""
+    """Number of top similar documents to retrieve during search"""
 
     app_name: str = ""
 
@@ -85,38 +84,27 @@ class KnowledgeBase(BaseModel):
     def model_post_init(self, __context: Any) -> None:
         if isinstance(self.backend, BaseKnowledgebaseBackend):
             self._backend = self.backend
+            self.index = self._backend.index
             logger.info(
                 f"Initialized knowledgebase with provided backend instance {self._backend.__class__.__name__}"
             )
             return
 
-        # must provide at least one of them
-        if not self.app_name and not self.index:
-            raise ValueError(
-                "Either `app_name` or `index` must be provided one of them."
-            )
-
-        # priority use index
-        if self.app_name and self.index:
-            logger.warning(
-                "`app_name` and `index` are both provided, using `index` as the knowledgebase index name."
-            )
+        # Once user define backend config, use it directly
+        if self.backend_config:
+            self._backend = _get_backend_cls(self.backend)(**self.backend_config)
+            return
 
-        # generate index name if `index` not provided but `app_name` is provided
-        if self.app_name and not self.index:
-            self.index = build_knowledgebase_index(self.app_name)
-            logger.info(
-                f"Knowledgebase index is set to {self.index} (generated by the app_name: {self.app_name})."
-            )
+        self.index = self.index or self.app_name
+        if not self.index:
+            raise ValueError("Either `index` or `app_name` must be provided.")
 
         logger.info(
-            f"Initializing knowledgebase: backend={self.backend} top_k={self.top_k}"
-        )
-        self._backend = _get_backend_cls(self.backend)(
-            index=self.index, **self.backend_config if self.backend_config else {}
+            f"Initializing knowledgebase: backend={self.backend} index={self.index} top_k={self.top_k}"
         )
+        self._backend = _get_backend_cls(self.backend)(index=self.index)
         logger.info(
-            f"Initialized knowledgebase with backend {self._backend.__class__.__name__}"
+            f"Initialized knowledgebase with backend {self.backend.__class__.__name__}"
         )
 
     def add_from_directory(self, directory: str, **kwargs) -> bool:
@@ -133,8 +121,7 @@ def add_from_text(self, text: str | list[str], **kwargs) -> bool:
 
     def search(self, query: str, top_k: int = 0, **kwargs) -> list[KnowledgebaseEntry]:
         """Search knowledge from knowledgebase"""
-        if top_k == 0:
-            top_k = self.top_k
+        top_k = top_k if top_k != 0 else self.top_k
 
         _entries = self._backend.search(query=query, top_k=top_k, **kwargs)