Miscellaneous UI updates (#6947)

### What problem does this PR solve?


### Type of change


- [x] Documentation Update

docs/faq.mdx

@@ -119,7 +119,7 @@ No, this feature is not supported.
 Yes, we support enhancing user queries based on existing context of an ongoing conversation:
 
 1. On the **Chat** page, hover over the desired assistant and select **Edit**.
-2. In the **Chat Configuration** popup, click the **Prompt Engine** tab.
+2. In the **Chat Configuration** popup, click the **Prompt engine** tab.
 3. Switch on **Multi-turn optimization** to enable this feature.
 
 ---
@@ -419,7 +419,7 @@ It is not recommended to manually change the 32-file batch upload limit. However
 This error occurs because there are too many chunks matching your search criteria. Try reducing the **TopN** and increasing **Similarity threshold** to fix this issue:
 
 1. Click **Chat** in the middle top of the page.
-2. Right-click the desired conversation > **Edit** > **Prompt Engine**
+2. Right-click the desired conversation > **Edit** > **Prompt engine**
 3. Reduce the **TopN** and/or raise **Similarity threshold**.
 4. Click **OK** to confirm your changes.
 

docs/guides/chat/accelerate_question_answering.mdx

@@ -12,8 +12,8 @@ A checklist to speed up question answering.
 
 Please note that some of your settings may consume a significant amount of time. If you often find that your question answering is time-consuming, here is a checklist to consider:
 
-- In the **Prompt Engine** tab of your **Chat Configuration** dialogue, disabling **Multi-turn optimization** will reduce the time required to get an answer from the LLM.
-- In the **Prompt Engine** tab of your **Chat Configuration** dialogue, leaving the **Rerank model** field empty will significantly decrease retrieval time.
+- In the **Prompt engine** tab of your **Chat Configuration** dialogue, disabling **Multi-turn optimization** will reduce the time required to get an answer from the LLM.
+- In the **Prompt engine** tab of your **Chat Configuration** dialogue, leaving the **Rerank model** field empty will significantly decrease retrieval time.
 - When using a rerank model, ensure you have a GPU for acceleration; otherwise, the reranking process will be *prohibitively* slow.
 
 :::tip NOTE 

docs/guides/chat/set_chat_variables.md

@@ -17,7 +17,7 @@ In RAGFlow, variables are closely linked with the system prompt. When you add a
 
 ## Where to set variables
 
-Hover your mouse over your chat assistant, click **Edit** to open its **Chat Configuration** dialogue, then click the **Prompt Engine** tab. Here, you can work on your variables in the **System prompt** field and the **Variable** section:
+Hover your mouse over your chat assistant, click **Edit** to open its **Chat Configuration** dialogue, then click the **Prompt engine** tab. Here, you can work on your variables in the **System prompt** field and the **Variable** section:
 
 ![set_variables](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/prompt_engine.jpg)
 
@@ -33,7 +33,7 @@ In the **Variable** section, you add, remove, or update variables.
 It does not currently make a difference whether you set `{knowledge}` to optional or mandatory, but note that this design will be updated at a later point.
 :::
 
-From v0.17.0 onward, you can start an AI chat without specifying knowledge bases. In this case, we recommend removing the `{knowledge}` variable to prevent unnecessary references and keeping the **Empty response** field empty to avoid errors.
+From v0.17.0 onward, you can start an AI chat without specifying knowledge bases. In this case, we recommend removing the `{knowledge}` variable to prevent unnecessary reference and keeping the **Empty response** field empty to avoid errors.
 
 ### Custom variables
 
@@ -46,13 +46,15 @@ Besides `{knowledge}`, you can also define your own variables to pair with the s
 
 ## 2. Update system prompt
 
-After you add or remove variables in the **Variable** section, ensure your changes are reflected in the system prompt to avoid inconsistencies and errors. Here's an example:
+After you add or remove variables in the **Variable** section, ensure your changes are reflected in the system prompt to avoid inconsistencies or errors. Here's an example:
 
 ```
 You are an intelligent assistant. Please answer the question by summarizing chunks from the specified knowledge base(s)...
 
 Your answers should follow a professional and {style} style.
 
+...
+
 Here is the knowledge base:
 {knowledge}
 The above is the knowledge base.

docs/guides/chat/start_chat.md

@@ -19,7 +19,7 @@ You start an AI conversation by creating an assistant.
 
    > RAGFlow offers you the flexibility of choosing a different chat model for each dialogue, while allowing you to set the default models in **System Model Settings**.
 
-2. Update **Assistant Settings**:
+2. Update **Assistant settings**:
 
    - **Assistant name** is the name of your chat assistant. Each assistant corresponds to a dialogue with a unique combination of knowledge bases, prompts, hybrid search configurations, and large model settings.
    - **Empty response**:
@@ -28,7 +28,7 @@ You start an AI conversation by creating an assistant.
    - **Show quote**: This is a key feature of RAGFlow and enabled by default. RAGFlow does not work like a black box. Instead, it clearly shows the sources of information that its responses are based on.
    - Select the corresponding knowledge bases. You can select one or multiple knowledge bases, but ensure that they use the same embedding model, otherwise an error would occur.
 
-3. Update **Prompt Engine**:
+3. Update **Prompt engine**:
 
    - In **System**, you fill in the prompts for your LLM, you can also leave the default prompt as-is for the beginning.
    - **Similarity threshold** sets the similarity "bar" for each chunk of text. The default is 0.2. Text chunks with lower similarity scores are filtered out of the final response.

docs/guides/models/deploy_local_llm.mdx

@@ -3,11 +3,11 @@ sidebar_position: 2
 slug: /deploy_local_llm
 ---
 
-# Deploy LLM locally
+# Deploy local models
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
-Run models locally using Ollama, Xinference, or other frameworks.
+Deploy and run local models using Ollama, Xinference, or other frameworks.
 
 ---
 

docs/guides/team/join_or_leave_team.md

@@ -5,7 +5,7 @@ slug: /join_or_leave_team
 
 # Join or leave a team
 
-Accept a team invite to join a team, decline a team invite, or leave a team.
+Accept an invite to join a team, decline an invite, or leave a team.
 
 ---
 
@@ -23,7 +23,7 @@ You cannot invite users to a team unless you are its owner.
 ## Prerequisites
 
 1. Ensure that your Email address that received the team invitation is associated with a RAGFlow user account.
-2. To view and update the team owner's shared knowledge base, the team owner must set a knowledge base's **Permissions** to **Team**.
+2. The team owner should share his knowledge bases by setting their **Permission** to **Team**.
 
 ## Accept or decline team invite
 

docs/release_notes.md

@@ -74,7 +74,7 @@ Released on March 3, 2025.
 
 ### New features
 
-- AI chat: Implements Deep Research for agentic reasoning. To activate this, enable the **Reasoning** toggle under the **Prompt Engine** tab of your chat assistant dialogue.
+- AI chat: Implements Deep Research for agentic reasoning. To activate this, enable the **Reasoning** toggle under the **Prompt engine** tab of your chat assistant dialogue.
 - AI chat: Leverages Tavily-based web search to enhance contexts in agentic reasoning. To activate this, enter the correct Tavily API key under the **Assistant settings** tab of your chat assistant dialogue.
 - AI chat: Supports starting a chat without specifying knowledge bases.
 - AI chat: HTML files can also be previewed and referenced, in addition to PDF files.