存储和搜索内存

在本文中，您将创建一个代理内存组件，存储线程消息和持久内存，然后重新搜索它们。

提示：有关软件包设置，请参见 Get Started with Agent Memory 。如果此示例需要本地 Oracle AI Database，请参见 Run Oracle AI Database Locally 。

存储消息和记忆

创建具有 Oracle DB 连接或池的代理内存组件，添加一个短线程，并在消息旁边保留一个持久的用户内存。

注：默认情况下， OracleAgentMemory 需要 LLM，以便 OracleThread 可以定期从通过 add_messages() 添加的最近线程消息中提取持久内存。如果不希望自动提取内存，请在构建客户机或调用 create_thread() 时设置 extract_memories=False。

from oracleagentmemory.core.oracleagentmemory import OracleAgentMemory
from oracleagentmemory.apis.searchscope import SearchScope
from oracleagentmemory.core.embedders.embedder import Embedder
from oracleagentmemory.core.llms.llm import Llm

embedder = Embedder(model="YOUR_EMBEDDING_MODEL")
llm = Llm(model="YOUR_LLM")
db_pool = ...  #an oracledb connection or connection pool
memory = OracleAgentMemory(connection=db_pool, embedder=embedder, llm=llm)

messages = [
    {
        "role": "user",
        "content": (
            "Orange juice has become my favorite breakfast drink lately, "
            "what can I pair it with?"
        ),
    },
    {
        "role": "assistant",
        "content": (
            "Nice! Orange juice goes great with something savory. "
            "Try eggs and toast, avocado toast, or a breakfast sandwich."
        ),
    },
]

thread = memory.create_thread(user_id="user_123")
#add_messages will add messages to the DB and extract memories automatically
thread.add_messages(messages)
#add_memory adds memory to the DB
thread.add_memory("The user likes orange juice with breakfast.")

搜索代理内存

搜索存储的内存和消息，并限定到该用户。

results = memory.search(query="orange juice", scope=SearchScope(user_id="user_123"))
for result in results:
    print(f"- [{result.record.record_type}] {result.content}")

输出：

- [memory] The user likes orange juice with breakfast.
- [message] Orange juice has become my favorite breakfast drink lately, what can I pair it with?
- [message] Nice! Orange juice goes great with something savory.
        Try eggs and toast, avocado toast, or a breakfast sandwich.

注：前面显示的输出具有说明性。将来的版本可能会返回其他结果类型、字段或排序模式。

小结

在本文中，我们学习了如何为单个用户创建代理内存客户端，将线程消息与持久存储器一起存储，并通过用户范围的检索来搜索这些记录。

提示：了解核心单用户内存工作流后，您可能还对将代理内存短期 API 与 LangGraph 一起使用感兴趣。

完整代码

#Copyright © 2026 Oracle and/or its affiliates.
#This software is under the Apache License 2.0
#(LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0) or Universal Permissive License
#(UPL) 1.0 (LICENSE-UPL or https://oss.oracle.com/licenses/upl), at your option.

#Agent Memory Code Example - Quickstart
#---------------------------------------

##Add memories

from oracleagentmemory.core.oracleagentmemory import OracleAgentMemory
from oracleagentmemory.apis.searchscope import SearchScope
from oracleagentmemory.core.embedders.embedder import Embedder
from oracleagentmemory.core.llms.llm import Llm

embedder = Embedder(model="YOUR_EMBEDDING_MODEL")
llm = Llm(model="YOUR_LLM")
db_pool = ...  #an oracledb connection or connection pool
memory = OracleAgentMemory(connection=db_pool, embedder=embedder, llm=llm)

messages = [
    {
        "role": "user",
        "content": (
            "Orange juice has become my favorite breakfast drink lately, "
            "what can I pair it with?"
        ),
    },
    {
        "role": "assistant",
        "content": (
            "Nice! Orange juice goes great with something savory. "
            "Try eggs and toast, avocado toast, or a breakfast sandwich."
        ),
    },
]

thread = memory.create_thread(user_id="user_123")
thread.add_messages(messages)
thread.add_memory("The user likes orange juice with breakfast.")

##Search memories

results = memory.search(query="orange juice", scope=SearchScope(user_id="user_123"))
for result in results:
    print(f"- [{result.record.record_type}] {result.content}")
#- [memory] The user likes orange juice with breakfast.
#- [message] Orange juice has become my favorite breakfast drink lately, what can I pair it with?
#- [message] Nice! Orange juice goes great with something savory. Try eggs and toast,
#avocado toast, or a breakfast sandwich.