ravendb · ppekrol · Aug 6, 2025 · Aug 6, 2025
diff --git a/cloud/cloud-instances.mdx b/cloud/cloud-instances.mdx
@@ -19,10 +19,10 @@ import LanguageContent from "@site/src/components/LanguageContent";
 - Use your portal's [Products tab](../cloud/portal/cloud-portal-products-tab.mdx) to raise or modify 
 a Free node, a Development node, or a Production cluster.  
 - Free and Development nodes, as well as Production "basic" grade clusters, are operated by 
-[burstable instances](../cloud/cloud-overview.mdx#burstable-vs.-reserved-clusters).  
+[burstable instances](../cloud/cloud-overview.mdx#burstable-vs-reserved-clusters).  
 - The Production cluster grades [Standard](../cloud/cloud-instances.mdx#standard-grade-production-cluster) 
 and [Performance](../cloud/cloud-instances.mdx#performance-grade-production-cluster) are 
-[Reserved clusters](../cloud/cloud-overview.mdx#burstable-vs.-reserved-clusters).  
+[Reserved clusters](../cloud/cloud-overview.mdx#burstable-vs-reserved-clusters).  
 
 In this page:  
 

diff --git a/cloud/cloud-overview.mdx b/cloud/cloud-overview.mdx
@@ -37,7 +37,7 @@ like adding or removing nodes, and run recurring tasks like backing up your data
     * [RavenDB on the Cloud](../cloud/cloud-overview.mdx#ravendb-on-the-cloud)
         * [Instances, Provisioning and RavenDB Products](../cloud/cloud-overview.mdx#instances-provisioning-and-ravendb-products)
         * [RavenDB Tiers: Free, Development and Production](../cloud/cloud-overview.mdx#ravendb-tiers)
-        * [Burstable vs. Reserved clusters](../cloud/cloud-overview.mdx#burstable-vs.-reserved-clusters)
+        * [Burstable vs. Reserved clusters](../cloud/cloud-overview.mdx#burstable-vs-reserved-clusters)
         * [Budget, Credits and Throttling](../cloud/cloud-overview.mdx#budget-credits-and-throttling)
     * [RavenDB Studio - Graphic User Interface](../cloud/cloud-overview.mdx#ravendb-studio---graphic-user-interface)
         * [Accessing RavenDB Cloud Studio](../cloud/cloud-overview.mdx#accessing-ravendb-cloud-studio)

diff --git a/cloud/cloud-security.mdx b/cloud/cloud-security.mdx
@@ -101,7 +101,7 @@ We recommend that you generate and use **different certificates** for your clien
 </Admonition>
 
 <Admonition type="info" title="Info">
-If your instance runs on a [burstable CPU](../cloud/cloud-overview.mdx#burstable-vs.-reserved-clusters), especially if it is a low-end one, 
+If your instance runs on a [burstable CPU](../cloud/cloud-overview.mdx#burstable-vs-reserved-clusters), especially if it is a low-end one, 
 RavenDB may take a while to generate certificates and spend a lot of your [CPU credits](../cloud/cloud-overview.mdx#budget-credits-and-throttling) in the 
 process.  
 We therefore recommend that you generate your certificates off-cloud and import them to your cloud instance.  

diff --git a/cloud/portal/cloud-portal-products-tab.mdx b/cloud/portal/cloud-portal-products-tab.mdx
@@ -42,10 +42,10 @@ To provision a new product, open your Portal's Products tab and click **Add Prod
 
 The New Product wizard will open and walk you through the following simple stages:  
 
-A. [Plan](../../cloud/portal/cloud-portal-products-tab.mdx#a.-new-product-plan)  
-B. [Billing](../../cloud/portal/cloud-portal-products-tab.mdx#b.-new-product-billing)  
-C. [Customize](../../cloud/portal/cloud-portal-products-tab.mdx#c.-new-product-customize)  
-D. [Summary](../../cloud/portal/cloud-portal-products-tab.mdx#d.-new-product-summary)  
+A. [Plan](../../cloud/portal/cloud-portal-products-tab.mdx#a-new-product-plan)  
+B. [Billing](../../cloud/portal/cloud-portal-products-tab.mdx#b-new-product-billing)  
+C. [Customize](../../cloud/portal/cloud-portal-products-tab.mdx#c-new-product-customize)  
+D. [Summary](../../cloud/portal/cloud-portal-products-tab.mdx#d-new-product-summary)  
 #### A. New Product: Plan
 Use the Plan page to choose your product's cloud **Provider**, **Region** and **Tier**.  
 

diff --git a/docs/ai-integration/connection-strings/azure-open-ai.mdx b/docs/ai-integration/connection-strings/azure-open-ai.mdx
@@ -65,7 +65,7 @@ export const supportedLanguages = ["csharp"];
    * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
      Requests to generate such query embeddings via the AI provider are sent in batches.
    * This parameter defines the maximum number of these batches that can be processed concurrently.  
-     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 10. Click **Test Connection** to confirm the connection string is set up correctly.
 

diff --git a/docs/ai-integration/connection-strings/embedded.mdx b/docs/ai-integration/connection-strings/embedded.mdx
@@ -51,7 +51,7 @@ export const supportedLanguages = ["csharp"];
    * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
      Requests to generate such query embeddings via the AI provider are sent in batches.
    * This parameter defines the maximum number of these batches that can be processed concurrently.  
-     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 5. Click **Save** to store the connection string or **Cancel** to discard changes.
 

diff --git a/docs/ai-integration/connection-strings/google-ai.mdx b/docs/ai-integration/connection-strings/google-ai.mdx
@@ -64,7 +64,7 @@ export const supportedLanguages = ["csharp"];
    * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
      Requests to generate such query embeddings via the AI provider are sent in batches.
    * This parameter defines the maximum number of these batches that can be processed concurrently.  
-     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 9. Click **Test Connection** to confirm the connection string is set up correctly.
 

diff --git a/docs/ai-integration/connection-strings/hugging-face.mdx b/docs/ai-integration/connection-strings/hugging-face.mdx
@@ -58,7 +58,7 @@ export const supportedLanguages = ["csharp"];
    * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
      Requests to generate such query embeddings via the AI provider are sent in batches.
    * This parameter defines the maximum number of these batches that can be processed concurrently.  
-     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 8. Click **Test Connection** to confirm the connection string is set up correctly.
 

diff --git a/docs/ai-integration/connection-strings/mistral-ai.mdx b/docs/ai-integration/connection-strings/mistral-ai.mdx
@@ -56,7 +56,7 @@ export const supportedLanguages = ["csharp"];
    * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
      Requests to generate such query embeddings via the AI provider are sent in batches.
    * This parameter defines the maximum number of these batches that can be processed concurrently.  
-     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 8. Click **Test Connection** to confirm the connection string is set up correctly.
 

diff --git a/docs/ai-integration/connection-strings/ollama.mdx b/docs/ai-integration/connection-strings/ollama.mdx
@@ -53,7 +53,7 @@ export const supportedLanguages = ["csharp"];
    * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
      Requests to generate such query embeddings via the AI provider are sent in batches.
    * This parameter defines the maximum number of these batches that can be processed concurrently.  
-     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+     You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 7. Click **Test Connection** to confirm the connection string is set up correctly.
 

diff --git a/docs/ai-integration/connection-strings/open-ai.mdx b/docs/ai-integration/connection-strings/open-ai.mdx
@@ -79,7 +79,7 @@ export const supportedLanguages = ["csharp"];
     * When making vector search queries, the content of the search terms must also be converted to embeddings to compare them against the stored vectors.
       Requests to generate such query embeddings via the AI provider are sent in batches.
     * This parameter defines the maximum number of these batches that can be processed concurrently.  
-      You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxconcurrentbatches) configuration key.
+      You can set a default value using the [Ai.Embeddings.MaxConcurrentBatches](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxconcurrentbatches) configuration key.
 
 11. Click **Test Connection** to confirm the connection string is set up correctly.
 

diff --git a/docs/ai-integration/generating-embeddings/overview.mdx b/docs/ai-integration/generating-embeddings/overview.mdx
@@ -71,9 +71,9 @@ import LanguageContent from "@site/src/components/LanguageContent";
   * Embeddings generation tasks are [Ongoing Tasks](../../studio/database/tasks/ongoing-tasks/general-info.mdx) that process documents as they change.  
     Before contacting the provider after a document change, the task first checks the cache to see if a matching embedding already exists, avoiding unnecessary requests.
   * The requests to generate embeddings from the source text are sent to the provider in batches.  
-    The batch size is configurable, see the [Ai.Embeddings.MaxBatchSize](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxbatchsize) configuration key.  
+    The batch size is configurable, see the [Ai.Embeddings.MaxBatchSize](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxbatchsize) configuration key.  
   * A failed embeddings generation task will retry after the duration set in the  
-    [Ai.Embeddings.MaxFallbackTimeInSec](../../server/configuration/ai-integration-configuration.mdx#ai.embeddings.maxfallbacktimeinsec) configuration key.
+    [Ai.Embeddings.MaxFallbackTimeInSec](../../server/configuration/ai-integration-configuration.mdx#aiembeddingsmaxfallbacktimeinsec) configuration key.
 
 </Admonition>
 <Admonition type="note" title="Note">
@@ -126,8 +126,8 @@ import LanguageContent from "@site/src/components/LanguageContent";
 
 * The number of embeddings generation tasks across all databases can also be monitored using [SNMP](../../server/administration/snmp/snmp-overview.mdx).  
   The following SNMP OIDs provide relevant metrics:
-  * [5.1.11.25](../../server/administration/snmp/snmp-overview.mdx#5.1.11.25) – Total number of enabled embeddings generation tasks.
-  * [5.1.11.26](../../server/administration/snmp/snmp-overview.mdx#5.1.11.26) – Total number of active embeddings generation tasks.
+  * [5.1.11.25](../../server/administration/snmp/snmp-overview.mdx#511125) – Total number of enabled embeddings generation tasks.
+  * [5.1.11.26](../../server/administration/snmp/snmp-overview.mdx#511126) – Total number of active embeddings generation tasks.
 
 
 
diff --git a/docs/ai-integration/vector-search/vector-search-using-dynamic-query.mdx b/docs/ai-integration/vector-search/vector-search-using-dynamic-query.mdx
@@ -123,7 +123,7 @@ export const supportedLanguages = ["csharp"];
 
 * **Search results**:  
   By default, the resulting documents will be ordered by their score.
-  You can modify this behavior using the [Indexing.Corax.VectorSearch.OrderByScoreAutomatically](../../server/configuration/indexing-configuration.mdx#indexing.corax.vectorsearch.orderbyscoreautomatically) configuration key.  
+  You can modify this behavior using the [Indexing.Corax.VectorSearch.OrderByScoreAutomatically](../../server/configuration/indexing-configuration.mdx#indexingcoraxvectorsearchorderbyscoreautomatically) configuration key.  
   In addition, you can apply any of the 'order by' methods to your query, as explained in [sort query results](../../client-api/session/querying/sort-query-results.mdx).
 
 </Admonition>
@@ -147,7 +147,7 @@ export const supportedLanguages = ["csharp"];
       it is recommended to explicitly specify the minimum similarity level at query time.
 
     If not specified, the default value is taken from the following configuration key:
-    [Indexing.Corax.VectorSearch.DefaultMinimumSimilarity](../../server/configuration/indexing-configuration.mdx#indexing.corax.vectorsearch.defaultminimumsimilarity).
+    [Indexing.Corax.VectorSearch.DefaultMinimumSimilarity](../../server/configuration/indexing-configuration.mdx#indexingcoraxvectorsearchdefaultminimumsimilarity).
 
 * **Number of candidates**  
   You can specify the maximum number of vectors that RavenDB will return from a graph search.  
@@ -156,7 +156,7 @@ export const supportedLanguages = ["csharp"];
     * higher than the number of candidates - when the same vector is shared between multiple documents.
 
     If not specified, the default value is taken from the following configuration key:
-    [Indexing.Corax.VectorSearch.DefaultNumberOfCandidatesForQuerying](../../server/configuration/indexing-configuration.mdx#indexing.corax.vectorsearch.defaultnumberofcandidatesforquerying).
+    [Indexing.Corax.VectorSearch.DefaultNumberOfCandidatesForQuerying](../../server/configuration/indexing-configuration.mdx#indexingcoraxvectorsearchdefaultnumberofcandidatesforquerying).
 
 * **Search method**
     * _Approximate Nearest-Neighbor search_ (Default):   
@@ -172,7 +172,7 @@ export const supportedLanguages = ["csharp"];
 #### Corax auto-indexes
 * Only [Corax indexes](../../indexes/search-engine/corax.mdx) support vector search.
 
-* Even if your **default auto-index engine** is set to Lucene (via [Indexing.Auto.SearchEngineType](../../server/configuration/indexing-configuration.mdx#indexing.auto.searchenginetype)),  
+* Even if your **default auto-index engine** is set to Lucene (via [Indexing.Auto.SearchEngineType](../../server/configuration/indexing-configuration.mdx#indexingautosearchenginetype)),  
   performing a vector search using a dynamic query will create a new auto-index based on Corax.
 
 * Normally, new dynamic queries extend existing [auto-indexes](../../client-api/session/querying/how-to-query.mdx#queries-always-provide-results-using-an-index) if they require additional fields.  
@@ -1501,8 +1501,8 @@ and (vector.search(embedding.text(Name), $searchTerm, 0.75, 25))
 * You can combine multiple vector search statements in the same query using logical operators.  
   This is useful when you want to retrieve documents that match more than one vector-based criterion.
 
-* This can be done using [DocumentQuery](../../client-api/session/querying/how-to-query.mdx#session.advanced.documentquery),
-  [RawQuery](../../client-api/session/querying/how-to-query.mdx#session.advanced.rawquery) or raw [RQL](../../client-api/session/querying/what-is-rql.mdx).
+* This can be done using [DocumentQuery](../../client-api/session/querying/how-to-query.mdx#sessionadvanceddocumentquery),
+  [RawQuery](../../client-api/session/querying/how-to-query.mdx#sessionadvancedrawquery) or raw [RQL](../../client-api/session/querying/what-is-rql.mdx).
 
 * In the example below, the results will include companies that match one of two vector search conditions:  
   * Companies from European countries with a _Name_ similar to "snack"
@@ -1653,7 +1653,7 @@ or
 
 * Each clause retrieves a limited number of candidates, determined by the _NumberOfCandidates_ parameter.
   * You can explicitly set this value in the query clause, see [query parameters](../../ai-integration/vector-search/vector-search-using-dynamic-query.mdx#the-dynamic-query-parameters).  
-  * If not specified, it is taken from the [Indexing.Corax.VectorSearch.DefaultNumberOfCandidatesForQuerying](../../server/configuration/indexing-configuration.mdx#indexing.corax.vectorsearch.defaultnumberofcandidatesforquerying) configuration key (default is 16).
+  * If not specified, it is taken from the [Indexing.Corax.VectorSearch.DefaultNumberOfCandidatesForQuerying](../../server/configuration/indexing-configuration.mdx#indexingcoraxvectorsearchdefaultnumberofcandidatesforquerying) configuration key (default is 16).
 
 * **The final result set** is computed by applying the logical operators (and, or) between these independently retrieved sets.
 
@@ -1707,10 +1707,10 @@ public IRavenQueryable<T> VectorSearch<T>(
 
 
 The default value for `minimumSimilarity` is defined by this configuration key:  
-[Indexing.Corax.VectorSearch.DefaultMinimumSimilarity ](../../server/configuration/indexing-configuration.mdx#indexing.corax.vectorsearch.defaultnumberofcandidatesforquerying).
+[Indexing.Corax.VectorSearch.DefaultMinimumSimilarity ](../../server/configuration/indexing-configuration.mdx#indexingcoraxvectorsearchdefaultnumberofcandidatesforquerying).
 
 The default value for `numberOfCandidates` is defined by this configuration key:  
-[Indexing.Corax.VectorSearch.DefaultNumberOfCandidatesForQuerying](../../server/configuration/indexing-configuration.mdx#indexing.corax.vectorsearch.defaultminimumsimilarity).
+[Indexing.Corax.VectorSearch.DefaultNumberOfCandidatesForQuerying](../../server/configuration/indexing-configuration.mdx#indexingcoraxvectorsearchdefaultminimumsimilarity).
 `IVectorFieldFactory`:
 
 <TabItem value="syntax_2" label="syntax_2">