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new 005d3e10 docs: update blog's title (#438)
0e03726c8e8268cc168a5e20085c91abb1ec83a2
005d3e10 is described below
commit 005d3e10940e1ae92b73bd0b5c87e5a069929cac
Author: imbajin <[email protected]>
AuthorDate: Thu Dec 11 08:05:20 2025 +0000
docs: update blog's title (#438) 0e03726c8e8268cc168a5e20085c91abb1ec83a2
---
blog/2025/09/30/toplingdb-yaml-configuration-file/index.html | 2 +-
blog/2025/10/09/toplingdb-quick-start/index.html | 2 +-
blog/2025/10/29/agentic-graphrag/index.html | 6 +++---
blog/computing/index.html | 2 +-
blog/hugegraph-ai/index.html | 4 ++--
blog/hugegraph/index.html | 2 +-
blog/hugegraph/toplingdb/index.html | 2 +-
blog/index.html | 4 ++--
blog/toolchain/index.html | 2 +-
cn/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html | 2 +-
cn/blog/2025/10/09/toplingdb-quick-start/index.html | 2 +-
cn/blog/2025/10/29/agentic-graphrag/index.html | 6 +++---
cn/blog/computing/index.html | 2 +-
cn/blog/hugegraph-ai/index.html | 6 +++---
cn/blog/hugegraph/index.html | 2 +-
cn/blog/hugegraph/toplingdb/index.html | 2 +-
cn/blog/index.html | 6 +++---
cn/blog/toolchain/index.html | 2 +-
cn/sitemap.xml | 2 +-
en/sitemap.xml | 2 +-
sitemap.xml | 2 +-
21 files changed, 31 insertions(+), 31 deletions(-)
diff --git a/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
b/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
index 9ba11236..a56b39f5 100644
--- a/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
+++ b/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
@@ -9,7 +9,7 @@ This document focuses on the extended parameters of ToplingDB,
helping readers u
ToplingDB introduces a SidePlugin + YAML mechanism, making configuration more
modular and composable.
This document focuses on the extended parameters of ToplingDB, helping readers
understand their purpose and usage.
0. rocksdb_plus.yaml used in HugeGraph The following includes only the
configuration parameters used in HugeGraph. For the full configuration
supported by ToplingDB, refer to the SidePlugin Wiki:"><link rel=preload
href=/scss/main.min.3276a99ddd5b15fbe3fcf20f8237086c2cbb526b572f4f06a2246fa9279ed395.css
as=style><link
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rel=stylesheet integrity><script src=/js/jquery.min.js></script>
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[...]
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href=/css/prism.css><script>document.addEventListener("DOMContentLoaded",function(){var
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[...]
<a
href=https://github.com/apache/incubator-hugegraph-doc/edit/master/content/en/blog/hugegraph/toplingdb/toplingdb-configuration-yaml.md
class=td-page-meta--edit target=_blank rel=noopener><i class="fa fa-edit
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[...]
<a
href="https://github.com/apache/incubator-hugegraph-doc/issues/new?title=ToplingDB%20YAML%20configuration%20file";
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diff --git a/blog/2025/10/09/toplingdb-quick-start/index.html
b/blog/2025/10/09/toplingdb-quick-start/index.html
index f90c05b9..d923a4d1 100644
--- a/blog/2025/10/09/toplingdb-quick-start/index.html
+++ b/blog/2025/10/09/toplingdb-quick-start/index.html
@@ -6,7 +6,7 @@ Update hugegraph.properties
backend=rocksdb serializer=binary rocksdb.data_path=. rocksdb.wal_path=. #
Path to YAML configuration file # For security reasons, HG only allows YAML
files to be located under the `conf/graphs` directory
rocksdb.option_path=./conf/graphs/rocksdb_plus.yaml # Enable Web Server
rocksdb.open_http=true Initialize the database (required on the first startup,
or a new configuration was manually added under
‘conf/graphs/’)"><meta itemprop=datePublished
content="2025-10-09T00:00:00+0 [...]
Update hugegraph.properties
backend=rocksdb serializer=binary rocksdb.data_path=. rocksdb.wal_path=. #
Path to YAML configuration file # For security reasons, HG only allows YAML
files to be located under the `conf/graphs` directory
rocksdb.option_path=./conf/graphs/rocksdb_plus.yaml # Enable Web Server
rocksdb.open_http=true Initialize the database (required on the first startup,
or a new configuration was manually added under
‘conf/graphs/’)"><link rel=preload
href=/scss/main.min.3276a99ddd5b15fbe3fcf [...]
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[...]
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href=/css/prism.css><script>document.addEventListener("DOMContentLoaded",function(){var
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[...]
<a
href=https://github.com/apache/incubator-hugegraph-doc/edit/master/content/en/blog/hugegraph/toplingdb/toplingdb-quick-start.md
class=td-page-meta--edit target=_blank rel=noopener><i class="fa fa-edit
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[...]
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diff --git a/blog/2025/10/29/agentic-graphrag/index.html
b/blog/2025/10/29/agentic-graphrag/index.html
index 9d234832..f0e631eb 100644
--- a/blog/2025/10/29/agentic-graphrag/index.html
+++ b/blog/2025/10/29/agentic-graphrag/index.html
@@ -1,9 +1,9 @@
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rel="shortcut icon" href=/favicons/favicon.ico> [...]
To address the problem of temporal discrepancies between model training data
and real-world data, Retrieval-Augmented Generation …"><meta
property="og:title" content="Agentic GraphRAG"><meta property="og:description"
content="Project Background To address the problem of temporal discrepancies
between model training data and real-world data, Retrieval-Augmented Generation
(RAG) technology has emerged. RAG, as the name suggests, is a technique that
retrieves relevant data from external dat [...]
-The earliest RAG employed a simple Retrieval-Generation architecture. We take
the user’s question, perform some pre-processing (keyword extraction,
etc."><meta property="og:type" content="article"><meta property="og:url"
content="/blog/2025/10/29/agentic-graphrag/"><meta property="article:section"
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content="2025-10-29T00:00:00+00:00"><meta property="article:modified_time"
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etc."><meta itemprop=datePublished content="2025-10-29T00:00:00+00:00"><meta
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name=twitter:card content="summary"><meta name=twitter:title content="Agentic
GraphRAG"><meta name=twitter:description conten [...]
+The earliest RAG employed a simple Retrieval-Generation architecture. We take
the user’s question, perform some pre-processing (keyword extraction,
etc."><meta property="og:type" content="article"><meta property="og:url"
content="/blog/2025/10/29/agentic-graphrag/"><meta property="article:section"
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content="2025-12-11T16:04:44+08:00"><meta property="og:si [...]
+The earliest RAG employed a simple Retrieval-Generation architecture. We take
the user’s question, perform some pre-processing (keyword extraction,
etc."><meta itemprop=datePublished content="2025-10-29T00:00:00+00:00"><meta
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itemprop=wordCount content="4810"><meta itemprop=keywords content><meta
name=twitter:card content="summary"><meta name=twitter:title content="Agentic
GraphRAG"><meta name=twitter:description conten [...]
The earliest RAG employed a simple Retrieval-Generation architecture. We take
the user’s question, perform some pre-processing (keyword extraction,
etc."><link rel=preload
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href=/css/prism.css><script>document.addEventListener("DOMContentLoaded",function(){var
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[...]
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[...]
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diff --git a/blog/computing/index.html b/blog/computing/index.html
index 76795047..452bad71 100644
--- a/blog/computing/index.html
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@@ -1,5 +1,5 @@
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[...]
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diff --git a/blog/hugegraph-ai/index.html b/blog/hugegraph-ai/index.html
index 3ed5cf57..d6e1bf5c 100644
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diff --git a/blog/hugegraph/index.html b/blog/hugegraph/index.html
index 2cc6ac97..74c39216 100644
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index 788bde37..b650eba8 100644
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diff --git a/blog/index.html b/blog/index.html
index d71fccd7..087da7b1 100644
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Here you will find technical articles, best practices, and community updates
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Update hugegraph.properties
backend=rocksdb serializer=binary …</p><p class=pt-0><a
href=/blog/2025/10/09/toplingdb-quick-start/ aria-label="Read more - ToplingDB
Quick Start">Read more</a></p></div></li><li class="media mb-4"><div
class=media-body><h5 class="mt-0 mb-1"><a
href=/blog/2025/09/30/toplingdb-yaml-configuration-file/>ToplingDB YAML
configuration file</a></h5><p class="mb-2 mb-md-3"><small
class=text-muted>Tuesday, September 30, 2025 in ToplingDB</small></p><header
class=article-meta></header><p class="p [...]
ToplingDB introduces a SidePlugin + YAML mechanism, making configuration more
modular and composable.
diff --git a/blog/toolchain/index.html b/blog/toolchain/index.html
index 7d8592de..b956b6f5 100644
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@@ -1,5 +1,5 @@
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diff --git a/cn/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
b/cn/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
index 41a43872..59a1b4ce 100644
--- a/cn/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
+++ b/cn/blog/2025/09/30/toplingdb-yaml-configuration-file/index.html
@@ -13,7 +13,7 @@ ToplingDB 在此基础上引入了 SidePlugin + YAML 的方式，使得配置更
本文重点介绍 ToplingDB 扩展参数 的部分，帮助读者理解这些配置的意义。
术语说明 MemTable: LSM-Tree 在内存中的可写数据结构，接收新写入的数据 SST (Sorted String Table):
Memtable 持久化到磁盘后生成的有序键值对文件 Flush: 将 MemTable 数据写入磁盘生成 SST 的过程 Compaction: 合并多个
SST 文件以优化存储和查询性能的过程 L0, L1, … L6: LSM-Tree 的不同层级，数字越大层级越深 0. HugeGraph
中提供的rocksdb_plus.yaml 下文只包括HugeGraph中所使用的配置参数，ToplingDB支持的完整配置请参考：SidePlugin
Wiki
http: # Web Server 相关配置 # normally parent path of db path document_root:
/dev/shm/rocksdb_resource # 静态资源目录, HugeGraph中通过`preload_topling.sh`进行静态资源提取
listening_ports: '127.0.0.1:2011' # Web Server监听端口，用于管理/监控 如端口被占用，请改为其他端口，例如
2012 或 2013 setenv: # 环境变量设置 StrSimpleEnvNameNotOverwrite: StringValue
IntSimpleEnvNameNotOverwrite: 16384 OverwriteThisEnv: #comment: overwrite is
default to false overwrite: true value: force overwrite this env by overwrite
true Cache: # Cache 相关配置 lru_cache: # 定 [...]
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diff --git a/cn/blog/2025/10/09/toplingdb-quick-start/index.html
b/cn/blog/2025/10/09/toplingdb-quick-start/index.html
index ad9ab114..fe610c43 100644
--- a/cn/blog/2025/10/09/toplingdb-quick-start/index.html
+++ b/cn/blog/2025/10/09/toplingdb-quick-start/index.html
@@ -23,7 +23,7 @@ backend=rocksdb serializer=binary rocksdb.data_path=.
rocksdb.wal_path=. # 配
cd *hugegraph-${version} bin/init-store.sh 启动 server
bin/start-hugegraph.sh Starting HugeGraphServer... Connecting to
HugeGraphServer (http://127.0.0.1:8080/graphs)....OK 提示的 url 与
rest-server.properties 中配置的 restserver.url 一致
Web Server 的监听端口在 YAML 文件中通过 http.listening_ports 字段进行配置"><link rel=preload
href=/scss/main.min.3276a99ddd5b15fbe3fcf20f8237086c2cbb526b572f4f06a2246fa9279ed395.css
as=style><link
href=/scss/main.min.3276a99ddd5b15fbe3fcf20f8237086c2cbb526b572f4f06a2246fa9279ed395.css
rel=stylesheet integrity><script src=/js/jquery.min.js></script>
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[...]
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href=/css/prism.css><script>document.addEventListener("DOMContentLoaded",function(){var
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diff --git a/cn/blog/2025/10/29/agentic-graphrag/index.html
b/cn/blog/2025/10/29/agentic-graphrag/index.html
index a6140391..5e800bd8 100644
--- a/cn/blog/2025/10/29/agentic-graphrag/index.html
+++ b/cn/blog/2025/10/29/agentic-graphrag/index.html
@@ -13,7 +13,7 @@ class Operator: @abstractmethod def run(context: dict[str,
Any]) -> dict[str,Any
👉🏼 理论上现有设计已经可以正常过渡到Agentic GraphRAG，但是现有设计存在诸多悬而未决的问题： 1.
现有调度器仅仅支持链状Workflow，缺失了可能存在的并行空间 2. 现有调度器无法复用被反复使用到的Workflow 打破链式束缚，拥抱全新架构
之前的调度器给我们的启发是Operator粒度的解耦是一个不错的设计理念，但是调度器本身能力有限，限制了Workflow的能力。因此我们计划替换项目中的调度器！经过对几种不同的Workflow编排框架进行简单的调研之后，我们认为下面几个特性是我们筛选调度器的标准。（下面我们统一将框架编排对象称为Workflow，Workflow由一系列Task组成）
并行性：Workflow中没有数据依赖关系的不同Task能否支持自动并行
低耦合：Task的具体实现应该和Workflow本身解耦（用人话：一种Task可以作为多种不同的Workflow的节点，同时Task的实现是否需要包含与其他Task依赖关系约束？）
数据共享：由于我们希望不同的Task之间的依赖关系解耦，那我们就需要Workflow粒度的数据共享机制用来在不同的Task共享数据（用于参数传递）
提供Python接口 AI框架大乱斗 我们首先将目光放到了现在炙手可热的AI
Workflow调度框架。围绕前面提到的几个维度，我们分别调研了下面几种不同的Workflow编排框架——LlamaIndex，Agno，Pydantic-Ai，LangGraph。
LlamaIndex 对于LlamaIndex，我们用一个常见的例子说明LlamaIndex这个框架的设计理念。
-from workflows import Workflow, Context, step from workflows."><meta
property="og:type" content="article"><meta property="og:url"
content="/cn/blog/2025/10/29/agentic-graphrag/"><meta
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+from workflows import Workflow, Context, step from workflows."><meta
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最早的RAG采用简单的Retrieval -
Generation架构，我们拿到用户给出的问题，进行一定的预处理（关键词提取等等），得到预处理之后的问题，接着通过Embedding
Model从海量资料中抓取相关的资料作为Prompt交给大模型用于增强模型回答的质量。
但是基于语义相似性匹配进行相关语料的抓取未必能够处理所有情况，因为能够用于增强回答质量的语料不一定和问题本身存在语义相似性。一个常见的例子就是：**告诉我“提出水是万物的本源”的哲学家的徒弟提出的本体论观点。**而我们的语料中并不直接存在这个问题的答案，语料库中可能提到：
泰勒斯提出水是万物的本源 泰勒斯的弟子有阿纳克西曼德 阿纳克西曼德将没有任何形式规定性的阿派朗认定为万物的本源
如果单纯从语义相似度匹配出发，我们大概率只能retrieval到第一个句子用于增强大模型的回答。但是缺失语料2和语料3的情况下，如果我们所使用的大模型训练语料中没有哲学相关知识，在缺失这些关键信息的情况下，大模型将无法正确回答这些问题，甚至会出现“幻觉”。
@@ -26,7 +26,7 @@ class Operator: @abstractmethod def run(context: dict[str,
Any]) -> dict[str,Any
👉🏼 理论上现有设计已经可以正常过渡到Agentic GraphRAG，但是现有设计存在诸多悬而未决的问题： 1.
现有调度器仅仅支持链状Workflow，缺失了可能存在的并行空间 2. 现有调度器无法复用被反复使用到的Workflow 打破链式束缚，拥抱全新架构
之前的调度器给我们的启发是Operator粒度的解耦是一个不错的设计理念，但是调度器本身能力有限，限制了Workflow的能力。因此我们计划替换项目中的调度器！经过对几种不同的Workflow编排框架进行简单的调研之后，我们认为下面几个特性是我们筛选调度器的标准。（下面我们统一将框架编排对象称为Workflow，Workflow由一系列Task组成）
并行性：Workflow中没有数据依赖关系的不同Task能否支持自动并行
低耦合：Task的具体实现应该和Workflow本身解耦（用人话：一种Task可以作为多种不同的Workflow的节点，同时Task的实现是否需要包含与其他Task依赖关系约束？）
数据共享：由于我们希望不同的Task之间的依赖关系解耦，那我们就需要Workflow粒度的数据共享机制用来在不同的Task共享数据（用于参数传递）
提供Python接口 AI框架大乱斗 我们首先将目光放到了现在炙手可热的AI
Workflow调度框架。围绕前面提到的几个维度，我们分别调研了下面几种不同的Workflow编排框架——LlamaIndex，Agno，Pydantic-Ai，LangGraph。
LlamaIndex 对于LlamaIndex，我们用一个常见的例子说明LlamaIndex这个框架的设计理念。
-from workflows import Workflow, Context, step from workflows."><meta
itemprop=datePublished content="2025-10-29T00:00:00+00:00"><meta
itemprop=dateModified content="2025-11-10T18:31:26+08:00"><meta
itemprop=wordCount content="799"><meta itemprop=keywords content><meta
name=twitter:card content="summary"><meta name=twitter:title content="Agentic
GraphRAG"><meta name=twitter:description content="项目背景
为了应对模型训练数据和现实生活中实际数据之间存在的时效性差异问题，RAG技术应运而生。RAG，顾名思义就是通过向外部数据源获取对应的数据（Retrieval），用于增强（Argum
[...]
+from workflows import Workflow, Context, step from workflows."><meta
itemprop=datePublished content="2025-10-29T00:00:00+00:00"><meta
itemprop=dateModified content="2025-12-11T16:04:44+08:00"><meta
itemprop=wordCount content="799"><meta itemprop=keywords content><meta
name=twitter:card content="summary"><meta name=twitter:title content="Agentic
GraphRAG"><meta name=twitter:description content="项目背景
为了应对模型训练数据和现实生活中实际数据之间存在的时效性差异问题，RAG技术应运而生。RAG，顾名思义就是通过向外部数据源获取对应的数据（Retrieval），用于增强（Argum
[...]
最早的RAG采用简单的Retrieval -
Generation架构，我们拿到用户给出的问题，进行一定的预处理（关键词提取等等），得到预处理之后的问题，接着通过Embedding
Model从海量资料中抓取相关的资料作为Prompt交给大模型用于增强模型回答的质量。
但是基于语义相似性匹配进行相关语料的抓取未必能够处理所有情况，因为能够用于增强回答质量的语料不一定和问题本身存在语义相似性。一个常见的例子就是：**告诉我“提出水是万物的本源”的哲学家的徒弟提出的本体论观点。**而我们的语料中并不直接存在这个问题的答案，语料库中可能提到：
泰勒斯提出水是万物的本源 泰勒斯的弟子有阿纳克西曼德 阿纳克西曼德将没有任何形式规定性的阿派朗认定为万物的本源
如果单纯从语义相似度匹配出发，我们大概率只能retrieval到第一个句子用于增强大模型的回答。但是缺失语料2和语料3的情况下，如果我们所使用的大模型训练语料中没有哲学相关知识，在缺失这些关键信息的情况下，大模型将无法正确回答这些问题，甚至会出现“幻觉”。
@@ -40,7 +40,7 @@ class Operator: @abstractmethod def run(context: dict[str,
Any]) -> dict[str,Any
并行性：Workflow中没有数据依赖关系的不同Task能否支持自动并行
低耦合：Task的具体实现应该和Workflow本身解耦（用人话：一种Task可以作为多种不同的Workflow的节点，同时Task的实现是否需要包含与其他Task依赖关系约束？）
数据共享：由于我们希望不同的Task之间的依赖关系解耦，那我们就需要Workflow粒度的数据共享机制用来在不同的Task共享数据（用于参数传递）
提供Python接口 AI框架大乱斗 我们首先将目光放到了现在炙手可热的AI
Workflow调度框架。围绕前面提到的几个维度，我们分别调研了下面几种不同的Workflow编排框架——LlamaIndex，Agno，Pydantic-Ai，LangGraph。
LlamaIndex 对于LlamaIndex，我们用一个常见的例子说明LlamaIndex这个框架的设计理念。
from workflows import Workflow, Context, step from workflows."><link
rel=preload
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index ee96ef9a..131d44f6 100644
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-最早的RAG采用简单的Retrieval -
Generation架构，我们拿到用户给出的问题，进行一定的预处理（关键词提取等等），得到预处理之后的问题，接着通过Embedding
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+最早的RAG采用简单的Retrieval -
Generation架构，我们拿到用户给出的问题，进行一定的预处理（关键词提取等等），得到预处理之后的问题，接着通过Embedding
Model从海量资料中抓取相关的资料作为Prompt交给大模型用于增 …</p><p class=pt-0><a
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index 089d0cca..10917618 100644
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diff --git a/cn/blog/index.html b/cn/blog/index.html
index ebff9a5b..98499c78 100644
--- a/cn/blog/index.html
+++ b/cn/blog/index.html
@@ -4,13 +4,13 @@
HugeGraph (OLTP): 图数据库核心功能、性能优化、存储引擎等
HugeGraph-AI: AI 与图计算结合的应用案例
HugeGraph Computing (OLAP): …"><meta property="og:title" content="Blog"><meta
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HugeGraph 官网"><meta name=twitter:card content="summary"><meta
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content="Apache [...]
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href=/css/prism.css><script>document.addEventListener("DOMContentLoaded",function(){var
t=document.querySelectorAll("pre code.language-mermaid, code.language-mermaid,
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href=https://github.com/apache/incubator-hugegraph-doc/edit/master/content/cn/blog/_index.md
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<a
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entire section</a></div></aside><main class="col-12 col-md-9 col-xl-8 pl-md-5
pr-md-4" role=main><a class="btn btn-lg -bg-orange td-rss-button d-none
d-lg-block" href=/cn/blog/index.xml target=_blank>RSS <i class="fa fa-rss
ml-2"></i></a><div class=row><div class=col-12><h2>Posts in 2025</h2><ul
class="list-unstyled mt-4"><li class="media mb-4"><div class=media-body><h5
class="mt-0 mb-1"><a href=/cn/blog/2025/10/29 [...]
-最早的RAG采用简单的Retrieval -
Generation架构，我们拿到用户给出的问题，进行一定的预处理（关键词提取等等），得到预处理之后的问题，接着通过Embedding
Model从海量资料中抓取相关的资料作为Prompt交给大模型用于增 …</p><p class=pt-0><a
href=/cn/blog/2025/10/29/agentic-graphrag/ aria-label="Read more - Agentic
GraphRAG">Read more</a></p></div></li><li class="media mb-4"><div
class=media-body><h5 class="mt-0 mb-1"><a
href=/cn/blog/2025/10/09/toplingdb-quick-start/>ToplingDB Quick
Start</a></h5><p class="mb-2 mb-md-3"><small class=text-muted>Thursday, October
09, 2025 in Topli [...]
+<a id=print href=/cn/blog/_print/><i class="fa fa-print fa-fw"></i> Print
entire section</a></div></aside><main class="col-12 col-md-9 col-xl-8 pl-md-5
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class="list-unstyled mt-4"><li class="media mb-4"><div class=media-body><h5
class="mt-0 mb-1"><a href=/cn/blog/2025/10/29 [...]
+最早的RAG采用简单的Retrieval -
Generation架构，我们拿到用户给出的问题，进行一定的预处理（关键词提取等等），得到预处理之后的问题，接着通过Embedding
Model从海量资料中抓取相关的资料作为Prompt交给大模型用于增 …</p><p class=pt-0><a
href=/cn/blog/2025/10/29/agentic-graphrag/ aria-label="Read more - Agentic
GraphRAG：模块化架构实践">Read more</a></p></div></li><li class="media mb-4"><div
class=media-body><h5 class="mt-0 mb-1"><a
href=/cn/blog/2025/10/09/toplingdb-quick-start/>ToplingDB Quick
Start</a></h5><p class="mb-2 mb-md-3"><small class=text-muted>Thursday, October
09, 2025 [...]
修改 hugegraph.properties
backend=rocksdb serializer=binary rocksdb.data_path=. …</p><p class=pt-0><a
href=/cn/blog/2025/10/09/toplingdb-quick-start/ aria-label="Read more -
ToplingDB Quick Start">Read more</a></p></div></li><li class="media mb-4"><div
class=media-body><h5 class="mt-0 mb-1"><a
href=/cn/blog/2025/09/30/toplingdb-yaml-configuration-file/>ToplingDB的YAML配置文件</a></h5><p
class="mb-2 mb-md-3"><small class=text-muted>Tuesday, September 30, 2025 in
ToplingDB</small></p><header class=article-meta></header> [...]
ToplingDB 在此基础上引入了 SidePlugin + YAML 的方式，使得配置更加模块化和可组合。
diff --git a/cn/blog/toolchain/index.html b/cn/blog/toolchain/index.html
index 8e4504bb..ab0dc591 100644
--- a/cn/blog/toolchain/index.html
+++ b/cn/blog/toolchain/index.html
@@ -1,5 +1,5 @@
<!doctype html><html lang=cn class=no-js><head><meta charset=utf-8><meta
name=viewport
content="width=device-width,initial-scale=1,shrink-to-fit=no"><meta
http-equiv=content-security-policy content="script-src 'self' 'unsafe-inline';
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[...]
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[...]
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href=https://github.com/apache/incubator-hugegraph-doc/edit/master/content/cn/blog/toolchain/_index.md
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[...]
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href="https://github.com/apache/incubator-hugegraph-doc/issues/new?title=HugeGraph%20ToolChain";
class=td-page-meta--issue target=_blank rel=noopener><i class="fab fa-github
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index 0a6dea77..f682cedf 100644
--- a/cn/sitemap.xml
+++ b/cn/sitemap.xml
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index 61b3fa7e..be68374a 100644
--- a/en/sitemap.xml
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@@ -1 +1 @@
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[...]
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xmlns:xhtml="http://www.w3.org/1999/xhtml";><url><loc>/docs/guides/architectural/</loc><lastmod>2025-06-13T21:28:50+08:00</lastmod><xhtml:link
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index f203753d..9c3adcef 100644
--- a/sitemap.xml
+++ b/sitemap.xml
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