*: add a vector-search directory and update links (#19893) (#19894)

TOC-tidb-cloud.md

@@ -10,7 +10,7 @@
   - [Roadmap](/tidb-cloud/tidb-cloud-roadmap.md)
 - Get Started
   - [Try Out TiDB Cloud](/tidb-cloud/tidb-cloud-quickstart.md)
-  - [Try Out TiDB + AI](/vector-search-get-started-using-python.md)
+  - [Try Out TiDB + AI](/vector-search/vector-search-get-started-using-python.md)
   - [Try Out HTAP](/tidb-cloud/tidb-cloud-htap-quickstart.md)
   - [Try Out TiDB Cloud CLI](/tidb-cloud/get-started-with-cli.md)
   - [Perform a PoC](/tidb-cloud/tidb-cloud-poc.md)
@@ -241,27 +241,27 @@
 - Explore Data
   - [Chat2Query (Beta) in SQL Editor](/tidb-cloud/explore-data-with-chat2query.md)
 - Vector Search (Beta)
-  - [Overview](/vector-search-overview.md)
+  - [Overview](/vector-search/vector-search-overview.md)
   - Get Started
-    - [Get Started with SQL](/vector-search-get-started-using-sql.md)
-    - [Get Started with Python](/vector-search-get-started-using-python.md)
+    - [Get Started with SQL](/vector-search/vector-search-get-started-using-sql.md)
+    - [Get Started with Python](/vector-search/vector-search-get-started-using-python.md)
   - Integrations
-    - [Overview](/vector-search-integration-overview.md)
+    - [Overview](/vector-search/vector-search-integration-overview.md)
     - AI Frameworks
-      - [LlamaIndex](/vector-search-integrate-with-llamaindex.md)
-      - [Langchain](/vector-search-integrate-with-langchain.md)
+      - [LlamaIndex](/vector-search/vector-search-integrate-with-llamaindex.md)
+      - [Langchain](/vector-search/vector-search-integrate-with-langchain.md)
     - Embedding Models/Services
-      - [Jina AI](/vector-search-integrate-with-jinaai-embedding.md)
+      - [Jina AI](/vector-search/vector-search-integrate-with-jinaai-embedding.md)
     - ORM Libraries
-      - [SQLAlchemy](/vector-search-integrate-with-sqlalchemy.md)
-      - [peewee](/vector-search-integrate-with-peewee.md)
-      - [Django ORM](/vector-search-integrate-with-django-orm.md)
+      - [SQLAlchemy](/vector-search/vector-search-integrate-with-sqlalchemy.md)
+      - [peewee](/vector-search/vector-search-integrate-with-peewee.md)
+      - [Django ORM](/vector-search/vector-search-integrate-with-django-orm.md)
   - Reference
-    - [Vector Data Types](/vector-search-data-types.md)
-    - [Vector Functions and Operators](/vector-search-functions-and-operators.md)
-    - [Vector Index](/vector-search-index.md)
-  - [Improve Performance](/vector-search-improve-performance.md)
-  - [Limitations](/vector-search-limitations.md)
+    - [Vector Data Types](/vector-search/vector-search-data-types.md)
+    - [Vector Functions and Operators](/vector-search/vector-search-functions-and-operators.md)
+    - [Vector Index](/vector-search/vector-search-index.md)
+  - [Improve Performance](/vector-search/vector-search-improve-performance.md)
+  - [Limitations](/vector-search/vector-search-limitations.md)
   - [Changelogs](/tidb-cloud/vector-search-changelogs.md)
 - Data Service (Beta)
   - [Overview](/tidb-cloud/data-service-overview.md)

TOC.md

@@ -82,23 +82,23 @@
       - [Stale Read](/develop/dev-guide-use-stale-read.md)
     - [HTAP Queries](/develop/dev-guide-hybrid-oltp-and-olap-queries.md)
   - Vector Search
-    - [Overview](/vector-search-overview.md)
+    - [Overview](/vector-search/vector-search-overview.md)
     - Get Started
-      - [Get Started with SQL](/vector-search-get-started-using-sql.md)
-      - [Get Started with Python](/vector-search-get-started-using-python.md)
+      - [Get Started with SQL](/vector-search/vector-search-get-started-using-sql.md)
+      - [Get Started with Python](/vector-search/vector-search-get-started-using-python.md)
     - Integrations
-      - [Overview](/vector-search-integration-overview.md)
+      - [Overview](/vector-search/vector-search-integration-overview.md)
       - AI Frameworks
-        - [LlamaIndex](/vector-search-integrate-with-llamaindex.md)
-        - [Langchain](/vector-search-integrate-with-langchain.md)
+        - [LlamaIndex](/vector-search/vector-search-integrate-with-llamaindex.md)
+        - [Langchain](/vector-search/vector-search-integrate-with-langchain.md)
       - Embedding Models/Services
-        - [Jina AI](/vector-search-integrate-with-jinaai-embedding.md)
+        - [Jina AI](/vector-search/vector-search-integrate-with-jinaai-embedding.md)
       - ORM Libraries
-        - [SQLAlchemy](/vector-search-integrate-with-sqlalchemy.md)
-        - [peewee](/vector-search-integrate-with-peewee.md)
-        - [Django](/vector-search-integrate-with-django-orm.md)
-    - [Improve Performance](/vector-search-improve-performance.md)
-    - [Limitations](/vector-search-limitations.md)
+        - [SQLAlchemy](/vector-search/vector-search-integrate-with-sqlalchemy.md)
+        - [peewee](/vector-search/vector-search-integrate-with-peewee.md)
+        - [Django](/vector-search/vector-search-integrate-with-django-orm.md)
+    - [Improve Performance](/vector-search/vector-search-improve-performance.md)
+    - [Limitations](/vector-search/vector-search-limitations.md)
   - Transaction
     - [Overview](/develop/dev-guide-transaction-overview.md)
     - [Optimistic and Pessimistic Transactions](/develop/dev-guide-optimistic-and-pessimistic-transaction.md)
@@ -891,7 +891,7 @@
       - [Date and Time Types](/data-type-date-and-time.md)
       - [String Types](/data-type-string.md)
       - [JSON Type](/data-type-json.md)
-      - [Vector Types](/vector-search-data-types.md)
+      - [Vector Types](/vector-search/vector-search-data-types.md)
     - Functions and Operators
       - [Overview](/functions-and-operators/functions-and-operators-overview.md)
       - [Type Conversion in Expression Evaluation](/functions-and-operators/type-conversion-in-expression-evaluation.md)
@@ -905,7 +905,7 @@
       - [Encryption and Compression Functions](/functions-and-operators/encryption-and-compression-functions.md)
       - [Locking Functions](/functions-and-operators/locking-functions.md)
       - [Information Functions](/functions-and-operators/information-functions.md)
-      - [Vector Functions and Operators](/vector-search-functions-and-operators.md)
+      - [Vector Functions and Operators](/vector-search/vector-search-functions-and-operators.md)
       - JSON Functions
         - [Overview](/functions-and-operators/json-functions.md)
         - [Functions That Create JSON](/functions-and-operators/json-functions/json-functions-create.md)
@@ -926,7 +926,7 @@
       - [TiDB Specific Functions](/functions-and-operators/tidb-functions.md)
       - [Comparisons between Functions and Syntax of Oracle and TiDB](/oracle-functions-to-tidb.md)
     - [Clustered Indexes](/clustered-indexes.md)
-    - [Vector Index](/vector-search-index.md)
+    - [Vector Index](/vector-search/vector-search-index.md)
     - [Constraints](/constraints.md)
     - [Generated Columns](/generated-columns.md)
     - [SQL Mode](/sql-mode.md)

basic-features.md

@@ -27,15 +27,15 @@ You can try out TiDB features on [TiDB Playground](https://play.tidbcloud.com/?u
 | [Date and time types](/data-type-date-and-time.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [String types](/data-type-string.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [JSON type](/data-type-json.md) | Y | Y | Y | Y | Y | E | E | E | E | E |
-| [Vectort types](/vector-search-data-types.md) | E | N | N | N | N | N | N | N | N | N |
+| [Vectort types](/vector-search/vector-search-data-types.md) | E | N | N | N | N | N | N | N | N | N |
 | [Control flow functions](/functions-and-operators/control-flow-functions.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [String functions](/functions-and-operators/string-functions.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [Numeric functions and operators](/functions-and-operators/numeric-functions-and-operators.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [Date and time functions](/functions-and-operators/date-and-time-functions.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [Bit functions and operators](/functions-and-operators/bit-functions-and-operators.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [Cast functions and operators](/functions-and-operators/cast-functions-and-operators.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [Encryption and compression functions](/functions-and-operators/encryption-and-compression-functions.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
-| [Vector functions and operators](/vector-search-functions-and-operators.md) | E | N | N | N | N | N | N | N | N | N |
+| [Vector functions and operators](/vector-search/vector-search-functions-and-operators.md) | E | N | N | N | N | N | N | N | N | N |
 | [Information functions](/functions-and-operators/information-functions.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
 | [JSON functions](/functions-and-operators/json-functions.md) | Y | Y | Y | Y | Y | E | E | E | E | E |
 | [Aggregation functions](/functions-and-operators/aggregate-group-by-functions.md) | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |
@@ -66,7 +66,7 @@ You can try out TiDB features on [TiDB Playground](https://play.tidbcloud.com/?u
 | [Foreign key](/foreign-key.md) | Y | E | E | E | N | N | N | N | N | N |
 | [TiFlash late materialization](/tiflash/tiflash-late-materialization.md) | Y | Y | Y | Y | N | N | N | N | N | N |
 | [Global index](/partitioned-table.md#global-indexes) | Y |  N | N  | N | N | N | N | N | N | N |
-| [Vector index](/vector-search-index.md) | E | N | N | N | N | N | N | N | N | N |
+| [Vector index](/vector-search/vector-search-index.md) | E | N | N | N | N | N | N | N | N | N |
 
 ## SQL statements
 
@@ -97,7 +97,7 @@ You can try out TiDB features on [TiDB Playground](https://play.tidbcloud.com/?u
 
 | Advanced SQL features | 8.5 | 8.1 | 7.5 | 7.1 | 6.5 | 6.1 | 5.4 | 5.3 | 5.2 | 5.1 |
 |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
-| [Vector search](/vector-search-overview.md) |  E |  N |  N  | N | N | N | N | N | N | N |
+| [Vector search](/vector-search/vector-search-overview.md) |  E |  N |  N  | N | N | N | N | N | N | N |
 | [Prepared statement cache](/sql-prepared-plan-cache.md) | Y | Y | Y | Y | Y | Y | Y | Y | E | E |
 | [Non-prepared statement cache](/sql-non-prepared-plan-cache.md) | Y | Y | Y | E | N | N | N | N | N | N |
 | [Instance-level execution plan cache](/system-variables.md#tidb_enable_instance_plan_cache-new-in-v840) | E | N | N | N | N | N | N | N | N | N |

br/backup-and-restore-overview.md

@@ -117,7 +117,7 @@ Backup and restore might go wrong when some TiDB features are enabled or disable
 | Global temporary tables | | Make sure that you are using v5.3.0 or a later version of BR to back up and restore data. Otherwise, an error occurs in the definition of the backed global temporary tables. |
 | TiDB Lightning Physical Import| | If the upstream database uses the physical import mode of TiDB Lightning, data cannot be backed up in log backup. It is recommended to perform a full backup after the data import. For more information, see [When the upstream database imports data using TiDB Lightning in the physical import mode, the log backup feature becomes unavailable. Why?](/faq/backup-and-restore-faq.md#when-the-upstream-database-imports-data-using-tidb-lightning-in-the-physical-import-mode-the-log-backup-feature-becomes-unavailable-why).|
 | TiCDC | | BR v8.2.0 and later: if the target cluster to be restored has a changefeed and the changefeed [CheckpointTS](/ticdc/ticdc-architecture.md#checkpointts) is earlier than the BackupTS, BR does not perform the restoration. BR versions before v8.2.0: if the target cluster to be restored has any active TiCDC changefeeds, BR does not perform the restoration. |
-| Vector search | | Make sure that you are using v8.4.0 or a later version of BR to back up and restore data. Restoring tables with [vector data types](/vector-search-data-types.md) to TiDB clusters earlier than v8.4.0 is not supported. |
+| Vector search | | Make sure that you are using v8.4.0 or a later version of BR to back up and restore data. Restoring tables with [vector data types](/vector-search/vector-search-data-types.md) to TiDB clusters earlier than v8.4.0 is not supported. |
 
 ### Version compatibility
 

releases/release-8.4.0.md

@@ -200,13 +200,13 @@ Quick access: [Quick start](https://docs.pingcap.com/tidb/v8.4/quick-start-with-
 
     Vector search is a search method based on data semantics, which provides more relevant search results. As one of the core functions of AI and large language models (LLMs), vector search can be used in various scenarios such as Retrieval-Augmented Generation (RAG), semantic search, and recommendation systems.
 
-    Starting from v8.4.0, TiDB supports [vector data types](/vector-search-data-types.md) and [vector search indexes](/vector-search-index.md), offering powerful vector search capabilities. TiDB vector data types support up to 16,383 dimensions and support various [distance functions](/vector-search-functions-and-operators.md#vector-functions), including L2 distance (Euclidean distance), cosine distance, negative inner product, and L1 distance (Manhattan distance).
+    Starting from v8.4.0, TiDB supports [vector data types](/vector-search/vector-search-data-types.md) and [vector search indexes](/vector-search/vector-search-index.md), offering powerful vector search capabilities. TiDB vector data types support up to 16,383 dimensions and support various [distance functions](/vector-search/vector-search-functions-and-operators.md#vector-functions), including L2 distance (Euclidean distance), cosine distance, negative inner product, and L1 distance (Manhattan distance).
 
     To start vector search, you only need to create a table with vector data types, insert vector data, and then perform a query of vector data. You can also perform mixed queries of vector data and traditional relational data.
 
-    To enhance the performance of vector search, you can create and use [vector search indexes](/vector-search-index.md). Note that TiDB vector search indexes rely on TiFlash. Before using vector search indexes, make sure that TiFlash nodes are deployed in your TiDB cluster.
+    To enhance the performance of vector search, you can create and use [vector search indexes](/vector-search/vector-search-index.md). Note that TiDB vector search indexes rely on TiFlash. Before using vector search indexes, make sure that TiFlash nodes are deployed in your TiDB cluster.
 
-    For more information, see [documentation](/vector-search-overview.md).
+    For more information, see [documentation](/vector-search/vector-search-overview.md).
 
 ### DB operations
 

ticdc/ticdc-compatibility.md

@@ -78,7 +78,7 @@ If the upstream cluster contains a global temporary table, the downstream TiDB c
 
 ### Compatibility with vector data types
 
-Starting from v8.4.0, TiCDC supports replicating tables with [vector data types](/vector-search-data-types.md) to downstream (experimental).
+Starting from v8.4.0, TiCDC supports replicating tables with [vector data types](/vector-search/vector-search-data-types.md) to downstream (experimental).
 
 When the downstream is Kafka or a storage service (such as Amazon S3, GCS, Azure Blob Storage, or NFS), TiCDC converts vector data types into string types before writing to the downstream.
 

tidb-cloud/data-service-manage-endpoint.md

@@ -44,7 +44,7 @@ In TiDB Cloud Data Service, you can generate one or multiple endpoints automatic
 
         For each operation you select, TiDB Cloud Data Service will generate a corresponding endpoint. If you select a batch operation (such as `POST (Batch Create)`), the generated endpoint lets you operate on multiple rows in a single request.
 
-        If the table you selected contains [vector data types](/vector-search-data-types.md), you can enable the **Vector Search Operations** option and select a vector distance function to generate a vector search endpoint that automatically calculates vector distances based on your selected distance function. The supported [vector distance functions](/vector-search-functions-and-operators.md) include the following:
+        If the table you selected contains [vector data types](/vector-search/vector-search-data-types.md), you can enable the **Vector Search Operations** option and select a vector distance function to generate a vector search endpoint that automatically calculates vector distances based on your selected distance function. The supported [vector distance functions](/vector-search/vector-search-functions-and-operators.md) include the following:
 
         - `VEC_L2_DISTANCE` (default): calculates the L2 distance (Euclidean distance) between two vectors.
         - `VEC_COSINE_DISTANCE`: calculates the cosine distance between two vectors.

tidb-cloud/tidb-cloud-release-notes.md

@@ -75,7 +75,7 @@ This page lists the release notes of [TiDB Cloud](https://www.pingcap.com/tidb-c
 
 - [Data Service (beta)](https://tidbcloud.com/console/data-service) supports automatically generating vector search endpoints.
 
-    If your table contains [vector data types](/vector-search-data-types.md), you can automatically generate a vector search endpoint that calculates vector distances based on your selected distance function.
+    If your table contains [vector data types](/vector-search/vector-search-data-types.md), you can automatically generate a vector search endpoint that calculates vector distances based on your selected distance function.
 
     This feature enables seamless integration with AI platforms such as [Dify](https://docs.dify.ai/guides/tools) and [GPTs](https://openai.com/blog/introducing-gpts), enhancing your applications with advanced natural language processing and AI capabilities for more complex tasks and intelligent solutions.
 
@@ -121,12 +121,12 @@ This page lists the release notes of [TiDB Cloud](https://www.pingcap.com/tidb-c
 
     The vector search (beta) feature provides an advanced search solution for performing semantic similarity searches across various data types, including documents, images, audio, and video. This feature enables developers to easily build scalable applications with generative artificial intelligence (AI) capabilities using familiar MySQL skills. Key features include:
 
-    - [Vector data types](/vector-search-data-types.md), [vector index](/vector-search-index.md), and [vector functions and operators](/vector-search-functions-and-operators.md).
-    - Ecosystem integrations with [LangChain](/vector-search-integrate-with-langchain.md), [LlamaIndex](/vector-search-integrate-with-llamaindex.md), and [JinaAI](/vector-search-integrate-with-jinaai-embedding.md).
-    - Programming language support for Python: [SQLAlchemy](/vector-search-integrate-with-sqlalchemy.md), [Peewee](/vector-search-integrate-with-peewee.md), and [Django ORM](/vector-search-integrate-with-django-orm.md).
-    - Sample applications and tutorials: perform semantic searches for documents using [Python](/vector-search-get-started-using-python.md) or [SQL](/vector-search-get-started-using-sql.md).
+    - [Vector data types](/vector-search/vector-search-data-types.md), [vector index](/vector-search/vector-search-index.md), and [vector functions and operators](/vector-search/vector-search-functions-and-operators.md).
+    - Ecosystem integrations with [LangChain](/vector-search/vector-search-integrate-with-langchain.md), [LlamaIndex](/vector-search/vector-search-integrate-with-llamaindex.md), and [JinaAI](/vector-search/vector-search-integrate-with-jinaai-embedding.md).
+    - Programming language support for Python: [SQLAlchemy](/vector-search/vector-search-integrate-with-sqlalchemy.md), [Peewee](/vector-search/vector-search-integrate-with-peewee.md), and [Django ORM](/vector-search/vector-search-integrate-with-django-orm.md).
+    - Sample applications and tutorials: perform semantic searches for documents using [Python](/vector-search/vector-search-get-started-using-python.md) or [SQL](/vector-search/vector-search-get-started-using-sql.md).
 
-  For more information, see [Vector search (beta) overview](/vector-search-overview.md).
+  For more information, see [Vector search (beta) overview](/vector-search/vector-search-overview.md).
 
 - [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless) now offers weekly email reports for organization owners.