Docs: Miscellaneous editorial updates (#8237)

### What problem does this PR solve?


### Type of change


- [x] Documentation Update

docs/guides/dataset/autokeyword_autoquestion.mdx

 # Auto-keyword Auto-question
 import APITable from '@site/src/components/APITable';
 
-Use a chat model to generate keywords and questions from each chunk in the knowledge base.
+Use a chat model to generate keywords or questions from each chunk in the knowledge base.
 
 ---
 
-When selecting a chunking method, you can also enable auto-keyword or auto-question generation to increase retrieval rates. This feature uses a chat model to produce a specified number of keywords and questions from each created chunk, generating a layer of "higher-level information" from the original content.
+When selecting a chunking method, you can also enable auto-keyword or auto-question generation to increase retrieval rates. This feature uses a chat model to produce a specified number of keywords and questions from each created chunk, generating an "additional layer of information" from the original content.
 
 :::caution WARNING
 Enabling this feature increases document indexing time and uses extra tokens, as all created chunks will be sent to the chat model for keyword or question generation.
 **Values**:  
 
 - 0: (Default) Disabled.  
-- Between 3 and 5 (invlusive): Recommended if you have chunks of approximately 1,000 characters. 
+- Between 3 and 5 (inclusive): Recommended if you have chunks of approximately 1,000 characters. 
 - 30 (maximum) 
 
 :::tip NOTE

docs/guides/dataset/use_tag_sets.md

 
 Auto-tagging applies in situations where chunks are so similar to each other that the intended chunks cannot be distinguished from the rest. For example, when you have a few chunks about iPhone and a majority about iPhone case or iPhone accessaries, it becomes difficult to retrieve those chunks about iPhone without additional information.
 
-## Create tag set
+## 1. Create tag set
 
 You can consider a tag set as a closed set, and the tags to attach to the chunks in your dataset (knowledge base) are *exclusively* from the specified tag set. You use a tag set to "inform" RAGFlow which chunks to tag and which tags to apply.
 
 
 ### Create a tag set
 
+:::danger IMPORTANT
+A tag set is *not* involved in document indexing or retrieval. Do not specify a tag set when configuring your chat assistant or agent.
+:::
+
 1. Click **+ Create knowledge base** to create a knowledge base.
 2. Navigate to the **Configuration** page of the created knowledge base and choose **Tag** as the default chunking method.
 3. Navigate to the **Dataset** page and upload and parse your table file in XLSX, CSV, or TXT formats.  
 4. Click the **Table** tab to view the tag frequency table:  
    ![Image](https://github.com/user-attachments/assets/af91d10c-5ea5-491f-ab21-3803d5ebf59f)
 
-:::danger IMPORTANT
-A tag set is *not* involved in document indexing or retrieval. Do not specify a tag set when configuring your chat assistant or agent.
-:::
-
-## Tag chunks
+## 2. Tag chunks
 
 Once a tag set is created, you can apply it to your dataset:
 
 3. Re-parse your documents to start the auto-tagging process.  
    _In an AI chat scenario using auto-tagged datasets, each query will be tagged using the corresponding tag set(s) and chunks with these tags will have a higher chance to be retrieved._
 
-## Update tag set
+## 3. Update tag set
 
 Creating a tag set is *not* for once and for all. Oftentimes, you may find it necessary to update or delete existing tags or add new entries. 
 

docs/references/http_api_reference.md

 
 ---
 
-### Related Questions
+### Generate related questions
 
 **POST** `/v1/sessions/related_questions`
 
 Generates five to ten alternative question strings from the user's original query to retrieve more relevant search results.
 
-This operation requires a `Bearer Login Token`, typically expires with in 24 hours. You can find the it in the browser request easily.
+This operation requires a `Bearer Login Token`, which typically expires with in 24 hours. You can find the it in the Request Headers in your browser easily.
 
 :::tip NOTE
-The chat model dynamically determines the number of questions to generate based on the instruction, typically between five and ten.
+The chat model autonomously determines the number of questions to generate based on the instruction, typically between five and ten.
 :::
 
 #### Request