GITBOOK-32: change request with no subject merged in GitBook

en/advanced/annotation-reply.md

@@ -19,6 +19,8 @@ The feature provides an alternative system for enhancing retrieval, skipping the
 4. Without a match, the query follows the standard LLM or RAG process.
 5. Deactivating Annotation Reply ceases matching replies from the annotations.
 
+<figure><img src="../.gitbook/assets/image.png" alt="" width="563"><figcaption><p>Annotation Reply Process</p></figcaption></figure>
+
 ## Activation
 
 Navigate to “Build Apps -> Add Feature” to enable the Annotation Reply feature.

en/advanced/datasets/README.md

@@ -76,11 +76,11 @@ Modify Documents For technical reasons, if developers make the following changes
 1. Adjust segmentation and cleaning settings
 2. Re-upload the file
 
-Dify support customizing the segmented and cleaned text by adding, deleting, and editing paragraphs. You can dynamically adjust your segmentation to make your knowledge more accurate. Click **Document --> paragraph --> Edit** in the knowledge to modify paragraphs content and custom keywords. Click **Document --> paragraph --> Add  segment --> Add a segment** to manually add new paragraph. Or click **Document --> paragraph --> Add  segment --> Batch add** to batch add new paragraph.
+Dify support customizing the segmented and cleaned text by adding, deleting, and editing paragraphs. You can dynamically adjust your segmentation to make your knowledge more accurate. Click **Document --> paragraph --> Edit** in the knowledge to modify paragraphs content and custom keywords. Click **Document --> paragraph --> Add segment --> Add a segment** to manually add new paragraph. Or click **Document --> paragraph --> Add segment --> Batch add** to batch add new paragraph.
 
 <figure><img src="../../.gitbook/assets/image (3) (1).png" alt=""><figcaption><p>Edit</p></figcaption></figure>
 
-<figure><img src="../../.gitbook/assets/image (1) (1) (1).png" alt=""><figcaption><p>add</p></figcaption></figure>
+<figure><img src="../../.gitbook/assets/image (1) (1) (1) (1).png" alt=""><figcaption><p>add</p></figcaption></figure>
 
 ### Disabling and Archiving of Documents
 

en/advanced/datasets/sync-from-notion.md

@@ -43,13 +43,11 @@ Click the " **New integration** " button, the type is Internal by default (canno
 
 Once the integration is created, you can update its settings as needed under the **Capabilities** tab and click the "**Show**" button under **Secrets** and then copy the Secrets.
 
-<figure><img src="../../.gitbook/assets/image (1) (1) (1) (1).png" alt=""><figcaption></figcaption></figure>
+<figure><img src="../../.gitbook/assets/image (1) (1) (1) (1) (1).png" alt=""><figcaption></figcaption></figure>
 
 Copy it and back to the Dify source code , in the **.env** file configuration related environment variables, environment variables as follows:
 
-**NOTION\_INTEGRATION\_TYPE** = internal
-or
-**NOTION\_INTEGRATION\_TYPE** = public
+**NOTION\_INTEGRATION\_TYPE** = internal or **NOTION\_INTEGRATION\_TYPE** = public
 
 **NOTION\_INTERNAL\_SECRET**=you-internal-secret
 
@@ -67,9 +65,9 @@ After your integration has been successfully made public in your [integration’
 
 Back to the Dify source code , in the **.env** file configuration related environment variables , environment variables as follows:
 
-**NOTION\_INTEGRATION\_TYPE**=public&#x20;
+**NOTION\_INTEGRATION\_TYPE**=public
 
-**NOTION\_CLIENT\_SECRET**=you-client-secret&#x20;
+**NOTION\_CLIENT\_SECRET**=you-client-secret
 
 **NOTION\_CLIENT\_ID**=you-client-id
 

en/advanced/model-configuration/xinference.md

@@ -47,7 +47,7 @@ There are two ways to deploy Xinference, namely [local deployment](https://githu
 
     Visit `http://127.0.0.1:9997`, select the model and specification you need to deploy,  as shown below:
 
-    <figure><img src="../../.gitbook/assets/image (1).png" alt=""><figcaption></figcaption></figure>
+    <figure><img src="../../.gitbook/assets/image (1) (1).png" alt=""><figcaption></figcaption></figure>
 
     As different models have different compatibility on different hardware platforms, please refer to [Xinference built-in models](https://inference.readthedocs.io/en/latest/models/builtin/index.html) to ensure the created model supports the current hardware platform.
 4.  Obtain the model UID

en/advanced/retrieval-augment/README.md

@@ -8,7 +8,7 @@ Developers can utilize this technology to cost-effectively build AI-powered cust
 
 In the diagram below, when a user asks, "Who is the President of the United States?", the system doesn't directly relay the question to the large model for an answer. Instead, it first conducts a vector search in a knowledge base (like Wikipedia, as shown in the diagram) for the user's query. It finds relevant content through semantic similarity matching (for instance, "Biden is the current 46th President of the United States…"), and then provides the user's question along with the found knowledge to the large model. This enables the model to have sufficient and complete knowledge to answer the question, thereby yielding a more reliable response.
 
-<figure><img src="../../.gitbook/assets/image (1) (1).png" alt=""><figcaption><p>Basic Architecture of RAG</p></figcaption></figure>
+<figure><img src="../../.gitbook/assets/image (1) (1) (1).png" alt=""><figcaption><p>Basic Architecture of RAG</p></figcaption></figure>
 
 ## Why is this necessary?&#x20;