docs: add links between docs (#18609)

Add links between related documentation pages to make relevant guides
easier to navigate and discover.

docs/guides/dataset/artifacts_knowledge_artifact_generation_and_management.md

@@ -12,4 +12,4 @@ sidebar_custom_props: {
 
 Artifacts are generated by **Knowledge Compilation**. Knowledge Compilation further organizes and processes knowledge content based on documents and parsing results in the dataset, and generates corresponding knowledge artifacts according to the knowledge compilation template used. Different knowledge compilation templates can generate different forms of artifacts, such as **Wiki**, **Navigation**, and **Graph**. Generated artifacts can be viewed and browsed through the **Artifacts** entry in the dataset.
 
-Creation and maintenance of artifacts are not completed on the **Artifacts** page. For knowledge compilation template configuration, artifact generation, update, regeneration, and **To Skill** operations, see **Knowledge Compilation**.
+Creation and maintenance of artifacts are not completed on the **Artifacts** page. For knowledge compilation template configuration, artifact generation, update, regeneration, and **To Skill** operations, see [**Knowledge Compilation**](../file/link_dataset.md).

docs/guides/dataset/configuration.md

@@ -119,7 +119,7 @@ Usage:
 
 If no pipeline is currently available, you can use the entry provided in the pipeline area to go to **Agent** and create one.
 
-> Note: For pipeline creation, node configuration, and flow orchestration, see **Agent > Pipeline**.
+> Note: For pipeline creation, node configuration, and flow orchestration, see [**Ingestion Pipeline**](../../guides/agent/agent_overview.md).
 
 ### Auto Metadata: Automatic Metadata Configuration
 
@@ -145,7 +145,7 @@ After saving, the system generates corresponding metadata from document content
 - **update_time**: Records the document update time.
 - **file_name**: Records the document file name.
 
-Select the fields to use, enable their switches, and then click **Save** to save the configuration. Generated metadata can be used in document management and retrieval filtering. To view or edit generated metadata, see **Metadata Management**.
+Select the fields to use, enable their switches, and then click **Save** to save the configuration. Generated metadata can be used in document management and retrieval filtering. To view or edit generated metadata, [**Metadata management**](../dataset/metadata_management.md).
 
 ### Table Column Role Configuration
 
@@ -182,4 +182,4 @@ The **Data source** area is used to associate the current dataset with data sour
 
 Click **Link data source** and select the data source to associate from existing data sources. After association, the current dataset can use the data provided by that data source. This area is only used to establish and manage the association between the dataset and data sources. It does not provide data source creation or connection configuration.
 
-> Tip: To add a new data source, or configure data source connection information, synchronization methods, and other settings, see the data source-related chapters. After adding the data source, return to the dataset configuration page to associate it.
+> Tip: To add a new data source, or configure data source connection information, synchronization methods, and other settings, see [**Data source**](../../guides/data_source/overview_and_page_management.md). After adding the data source, return to the dataset configuration page to associate it.

docs/guides/dataset/files_dataset_document_management.md

@@ -51,11 +51,13 @@ Operation steps:
 3. Select the documents to add.
 4. Confirm the addition and view the document status in the document list.
 
-### Add Documents from File Management
+### Add Documents from File
 
-Documents can also be added from RAGFlow's file management module. This method is suitable when files have already been uploaded to file management and need to be referenced by a dataset.
+Add documents from File Management
 
-After documents are added to the dataset, subsequent parsing and enabling status are still managed on the dataset's **Files** page. Documents that have not been parsed cannot generate chunks or participate in retrieval.
+Files that have already been uploaded to **File** can be added to a knowledge base by connecting them to the target knowledge base.
+Once connected, the files will be processed according to the configuration of the target knowledge base.
+For detailed instructions, see [**File > Connect to a knowledge base**](../file/link_dataset.md)
 
 ## Parse Documents
 

docs/guides/dataset/logs.md

@@ -33,26 +33,26 @@ If parsing fails for only one document, a document stays processing for a long t
 
 ## Dataset-Level Logs
 
-Dataset-level logs are used to view task execution records whose processing object is the entire dataset. Unlike document logs for single-document parsing tasks, dataset-level logs mainly record dataset-level processing tasks, such as **Knowledge Graph**, **RAPTOR**, **Artifact**, **Skill**, **Mind Map**, and **Timeline**.
+Dataset-level logs are used to view task execution records whose processing object is the entire dataset. Unlike document logs for single-document parsing tasks, dataset-level logs mainly record dataset-level processing tasks, such as **Knowledge Compilation**.
 
 Dataset-level logs mainly include:
 
 - **ID**: The unique identifier of the task record.
 - **Start date**: The task start time.
-- **Processing type**: The processing type, used to indicate the current dataset-level task, such as **Knowledge Graph**, **RAPTOR**, or **Artifact**.
+- **Processing type**: The processing type, used to indicate the current dataset-level task, such as **Wiki**.
 - **Status**: The current task execution status.
 - **Operations**: Operation entry. You can view log details and execution information for the current task.
 
 When a dataset-level processing task fails, does not complete for a long time, or needs execution confirmation, view the corresponding task record and log details here.
 
-> Tip: For tasks executed on a single document, such as document parsing, view document logs. For tasks executed on the entire dataset, such as **Knowledge Graph**, **RAPTOR**, and **Artifact**, view dataset-level logs.
+> Tip: For tasks executed on a single document, such as document parsing, view document logs. For tasks executed on the entire dataset, such as **Knowledge Compilation**, view dataset-level logs.
 
 ## Log Troubleshooting Suggestions
 
 When task execution is abnormal or does not complete for a long time, first select the corresponding logs based on task type, then troubleshoot based on task status and log details.
 
 - **Document processing tasks**: View document logs. Document logs record processing tasks for specific documents. Use information such as **Filename**, **Source**, **Ingestion pipeline**, **Task**, and **Status** to confirm which document and processing flow has the exception. For documents processed with **Data Pipeline**, you can also use the entry in **Operations** to view the corresponding pipeline execution result.
-- **Dataset-level processing tasks**: View dataset-level logs. Dataset-level tasks such as **Knowledge Graph**, **RAPTOR**, **Artifact**, **Skill**, **Mind Map**, and **Timeline** are recorded here. Use **Processing type** and **Status** to find the corresponding task, and view log details through **Operations**.
+- **Dataset-level processing tasks**: View dataset-level logs. Dataset-level tasks such as **Knowledge Compilation** are recorded here. Use **Processing type** and **Status** to find the corresponding task, and view log details through **Operations**.
 - **Task execution failed**: When **Status** is **Failed**, open the corresponding task log details and view the specific error information.
 - **Task does not complete for a long time**: When a task stays in **Pending**, **Running**, or **Schedule** for a long time, first confirm the current task status and start time, then view log details to determine whether the task is still running normally.