From fed4ad40d8e1f97e2fd75c0245f57e54eeb414c4 Mon Sep 17 00:00:00 2001
From: "jinli.yl" <jinli.yl@alibaba-inc.com>
Date: Tue, 9 Sep 2025 14:15:59 +0800
Subject: [PATCH] docs(service): update service description layout and content

- Simplified table structure for better readability
- Adjusted column widths for a more balanced layout
- Moved GitHub link and environment variable information to the Note column
- Improved consistency in language and formatting across both service descriptions
---
 reme_ai/service/service_description.md | 50 ++++++++++++--------------
 1 file changed, 22 insertions(+), 28 deletions(-)

diff --git a/reme_ai/service/service_description.md b/reme_ai/service/service_description.md
index 59c0beb1..8588a994 100644
--- a/reme_ai/service/service_description.md
+++ b/reme_ai/service/service_description.md
@@ -1,30 +1,24 @@
 <table>
-<colgroup>
-<col style="width: 20%">
-<col style="width: 25%">
-<col style="width: 15%">
-<col style="width: 40%">
-</colgroup>
-<thead>
-<tr>
-<th>Memory Type</th>
-<th>Import</th>
-<th>Note</th>
-<th>Description</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td>ReMe.PersonalMemoryService</td>
-<td><code>from reme_ai.service.personal_memory_service import PersonalMemoryService</code></td>
-<td><a href="https://github.com/modelscope/ReMe">GitHub</a><br>Env: <code>FLOW_EMBEDDING_API_KEY</code>, <code>FLOW_EMBEDDING_BASE_URL</code>, <code>FLOW_LLM_API_KEY</code>, <code>FLOW_LLM_BASE_URL</code></td>
-<td>ReMe's personalized memory service (formerly MemoryScope) empowers you to generate, retrieve, and share customized memories. Leveraging advanced LLM, embedding, and vector store technologies, it builds a comprehensive memory system with intelligent, context- and time-aware memory management—seamlessly enabling you to configure and deploy powerful AI agents.</td>
-</tr>
-<tr>
-<td>ReMe.TaskMemoryService</td>
-<td><code>from reme_ai.service.task_memory_service import TaskMemoryService</code></td>
-<td>Same as above</td>
-<td>ReMe's task-oriented memory service helps you efficiently manage and schedule task-related memories, enhancing both the accuracy and efficiency of task execution. Powered by LLM capabilities, it supports flexible creation, retrieval, update, and deletion of memories across diverse task scenarios—enabling you to effortlessly build and scale robust agent-based task systems.</td>
-</tr>
-</tbody>
+  <thead>
+    <tr>
+      <th width="100">MemoryType</th>
+      <th width="200">Import</th>
+      <th width="400">Desc</th>
+      <th width="400">Note</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td align="center">ReMe.PersonalMemoryService</td>
+      <td><code>from reme_ai.service.personal_memory_service import PersonalMemoryService</code></td>
+      <td>ReMe's personalized memory service (formerly MemoryScope) empowers you to generate, retrieve, and share customized memories. Leveraging advanced LLM, embedding, and vector store technologies, it builds a comprehensive memory system with intelligent, context- and time-aware memory management—seamlessly enabling you to configure and deploy powerful AI agents.</td>
+      <td align="center">https://github.com/modelscope/ReMe Need to configure environment variables: <code>FLOW_EMBEDDING_API_KEY</code>, <code>FLOW_EMBEDDING_BASE_URL</code>, <code>FLOW_LLM_API_KEY</code> and <code>FLOW_LLM_BASE_URL</code></td>
+    </tr>
+    <tr>
+      <td align="center">ReMe.TaskMemoryService</td>
+      <td><code>from reme_ai.service.task_memory_service import TaskMemoryService</code></td>
+      <td>ReMe's task-oriented memory service helps you efficiently manage and schedule task-related memories, enhancing both the accuracy and efficiency of task execution. Powered by LLM capabilities, it supports flexible creation, retrieval, update, and deletion of memories across diverse task scenarios—enabling you to effortlessly build and scale robust agent-based task systems.</td>
+      <td>the same as <code>ReMe.PersonalMemoryService</code></td>
+    </tr>
+  </tbody>
 </table>