Updated UI (#4011)

### What problem does this PR solve?



### Type of change


- [x] Documentation Update

docs/guides/manage_team_members.md

@@ -7,6 +7,8 @@ slug: /manage_team_members
 
 Invite or remove team members, join or leave a team.
 
+---
+
 By default, each RAGFlow user is assigned a single team named after their name. RAGFlow allows you to invite RAGFlow users to your team. Your team members can help you:
 
 - Upload documents to your datasets.

docs/references/http_api_reference.md

@@ -1380,7 +1380,7 @@ curl --request POST \
   - `"frequency penalty"`: `float`  
     Similar to the presence penalty, this reduces the model’s tendency to repeat the same words frequently. Defaults to `0.7`.
   - `"max_token"`: `integer`  
-    The maximum length of the model’s output, measured in the number of tokens (words or pieces of words). Defaults to `512`.  
+    The maximum length of the model's output, measured in the number of tokens (words or pieces of words). If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses. Defaults to `512`.  
 - `"prompt"`: (*Body parameter*), `object`  
   Instructions for the LLM to follow. If it is not explicitly set, a JSON object with the following values will be generated as the default. A `prompt` JSON object contains the following attributes:  
   - `"similarity_threshold"`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted reranking score during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
@@ -1515,7 +1515,7 @@ curl --request PUT \
   - `"frequency penalty"`: `float`  
     Similar to the presence penalty, this reduces the model’s tendency to repeat the same words frequently. Defaults to `0.7`.
   - `"max_token"`: `integer`  
-    The maximum length of the model’s output, measured in the number of tokens (words or pieces of words). Defaults to `512`.  
+    The maximum length of the model's output, measured in the number of tokens (words or pieces of words). If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses. Defaults to `512`.  
 - `"prompt"`: (*Body parameter*), `object`  
   Instructions for the LLM to follow.  A `prompt` object contains the following attributes:  
   - `"similarity_threshold"`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted rerank score during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.

docs/references/python_api_reference.md

@@ -951,7 +951,7 @@ The LLM settings for the chat assistant to create. Defaults to `None`. When the
 - `frequency penalty`: `float`  
   Similar to the presence penalty, this reduces the model’s tendency to repeat the same words frequently. Defaults to `0.7`.
 - `max_token`: `int`  
-  The maximum length of the model’s output, measured in the number of tokens (words or pieces of words). Defaults to `512`.
+  The maximum length of the model's output, measured in the number of tokens (words or pieces of words). If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses. Defaults to `512`.
 
 #### prompt: `Chat.Prompt`
 
@@ -1013,7 +1013,7 @@ A dictionary representing the attributes to update, with the following keys:
   - `"top_p"`, `float` Also known as “nucleus sampling”, this parameter sets a threshold to select a smaller set of words to sample from.  
   - `"presence_penalty"`, `float` This discourages the model from repeating the same information by penalizing words that have appeared in the conversation.
   - `"frequency penalty"`, `float` Similar to presence penalty, this reduces the model’s tendency to repeat the same words.
-  - `"max_token"`, `int` The maximum length of the model’s output, measured in the number of tokens (words or pieces of words).
+  - `"max_token"`, `int` The maximum length of the model's output, measured in the number of tokens (words or pieces of words). If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses. Defaults to `512`.
 - `"prompt"` : Instructions for the LLM to follow.
   - `"similarity_threshold"`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted rerank score during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
   - `"keywords_similarity_weight"`: `float` This argument sets the weight of keyword similarity in the hybrid similarity score with vector cosine similarity or reranking model similarity. By adjusting this weight, you can control the influence of keyword similarity in relation to other similarity measures. The default value is `0.7`.

web/src/locales/en.ts

@@ -366,10 +366,7 @@ The above is the content you need to summarize.`,
       topN: 'Top N',
       topNTip: `Not all chunks with similarity score above the 'similarity threshold' will be sent to the LLM. This selects 'Top N' chunks from the retrieved ones.`,
       variable: 'Variable',
-      variableTip: `If you use dialog APIs, the varialbes might help you chat with your clients with different strategies. 
-      The variables are used to fill-in the 'System' part in prompt in order to give LLM a hint.
-      The 'knowledge' is a very special variable which will be filled-in with the retrieved chunks.
-      All the variables in 'System' should be curly bracketed.`,
+      variableTip: `Variables can assist in developing more flexible strategies, particularly when you are using our chat assistant management APIs. These variables will be used by 'System' as part of the prompts for the LLM. The variable {knowledge} is a reserved special variable representing your selected knowledge base(s), and all variables should be enclosed in curly braces {}.`,
       add: 'Add',
       key: 'Key',
       optional: 'Optional',
@@ -381,15 +378,15 @@ The above is the content you need to summarize.`,
       improvise: 'Improvise',
       precise: 'Precise',
       balance: 'Balance',
-      freedomTip: `'Precise' means the LLM will be conservative and answer your question cautiously. 'Improvise' means the you want LLM talk much and freely. 'Balance' is between cautiously and freely.`,
+      freedomTip: `Set the freedom level to 'Precise' to strictly confine the LLM's response to your selected knowledge base(s). Choose 'Improvise' to grant the LLM greater freedom in its responses, which may lead to hallucinations. 'Balance' is an intermediate level; choose 'Balance' for more balanced responses.`,
       temperature: 'Temperature',
       temperatureMessage: 'Temperature is required',
       temperatureTip:
-        'This parameter controls the randomness of predictions by the model. A lower temperature makes the model more confident in its responses, while a higher temperature makes it more creative and diverse.',
+        `This parameter controls the randomness of the model's predictions. A lower temperature results in more conservative responses, while a higher temperature yields more creative and diverse responses.`,
       topP: 'Top P',
       topPMessage: 'Top P is required',
       topPTip:
-        'Also known as “nucleus sampling,” this parameter sets a threshold to select a smaller set of words to sample from. It focuses on the most likely words, cutting off the less probable ones.',
+        'Also known as "nucleus sampling", this parameter sets a threshold for selecting a smaller set of the most likely words to sample from, cutting off the less probable ones.',
       presencePenalty: 'Presence penalty',
       presencePenaltyMessage: 'Presence penalty is required',
       presencePenaltyTip:
@@ -401,7 +398,7 @@ The above is the content you need to summarize.`,
       maxTokens: 'Max tokens',
       maxTokensMessage: 'Max tokens is required',
       maxTokensTip:
-        'This sets the maximum length of the model’s output, measured in the number of tokens (words or pieces of words).',
+        `This sets the maximum length of the model's output, measured in the number of tokens (words or pieces of words). If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses. Defaults to 512.`,
       maxTokensInvalidMessage: 'Please enter a valid number for Max Tokens.',
       maxTokensMinMessage: 'Max Tokens cannot be less than 0.',
       quote: 'Show quote',
@@ -456,7 +453,8 @@ The above is the content you need to summarize.`,
       profileDescription: 'Update your photo and personal details here.',
       maxTokens: 'Max Tokens',
       maxTokensMessage: 'Max Tokens is required',
-      maxTokensTip: `This sets the maximum length of the model's output, measured in the number of tokens (words or pieces of words).`,
+      maxTokensTip:
+        `This sets the maximum length of the model's output, measured in the number of tokens (words or pieces of words). If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses. Defaults to 512.`,
       maxTokensInvalidMessage: 'Please enter a valid number for Max Tokens.',
       maxTokensMinMessage: 'Max Tokens cannot be less than 0.',
       password: 'Password',