Updated max_tokens descriptions (#6751)

### What problem does this PR solve?

#6721 

### Type of change


- [x] Documentation Update

docs/guides/agent/agent_component_reference/categorize.mdx

 - **Model**: The chat model to use.  
   - Ensure you set the chat model correctly on the **Model providers** page.
   - You can use different models for different components to increase flexibility or improve overall performance.
-- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.  
+- **Freedom**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.  
   This parameter has three options:  
   - **Improvise**: Produces more creative responses.
   - **Precise**: (Default) Produces more conservative responses.
 - **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
   - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
   - Defaults to 0.7.
-- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
-  - Defaults to 512. 
-  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
 
 :::tip NOTE
 - It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.

docs/guides/agent/agent_component_reference/keyword.mdx

 - **Model**: The chat model to use.  
   - Ensure you set the chat model correctly on the **Model providers** page.
   - You can use different models for different components to increase flexibility or improve overall performance.
-- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
+- **Freedom**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
   This parameter has three options:
   - **Improvise**: Produces more creative responses.
   - **Precise**: (Default) Produces more conservative responses.
 - **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
   - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
   - Defaults to 0.7.
-- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
-  - Defaults to 512. 
-  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
 
 :::tip NOTE
 - It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.

docs/guides/agent/agent_component_reference/rewrite.mdx

 - **Model**: The chat model to use.  
   - Ensure you set the chat model correctly on the **Model providers** page.
   - You can use different models for different components to increase flexibility or improve overall performance.
-- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
+- **Freedom**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
   This parameter has three options:
   - **Improvise**: Produces more creative responses.
   - **Precise**: (Default) Produces more conservative responses.
 - **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
   - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
   - Defaults to 0.7.
-- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
-  - Defaults to 512. 
-  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
 
 :::tip NOTE
 - It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.

docs/guides/chat/start_chat.md

 4. Update **Model Setting**:
 
    - In **Model**: you select the chat model. Though you have selected the default chat model in **System Model Settings**, RAGFlow allows you to choose an alternative chat model for your dialogue.
-   - **Preset configurations** refers to the level that the LLM improvises. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.
-   - **Temperature**: Level of the prediction randomness of the LLM. The higher the value, the more creative the LLM is.
-   - **Top P** is also known as "nucleus sampling". See [here](https://en.wikipedia.org/wiki/Top-p_sampling) for more information.
-   - **Max Tokens**: The maximum length of the LLM's responses. Note that the responses may be curtailed if this value is set too low.
+   - **Freedom**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
+   This parameter has three options:
+      - **Improvise**: Produces more creative responses.
+      - **Precise**: (Default) Produces more conservative responses.
+      - **Balance**: A middle ground between **Improvise** and **Precise**.
+   - **Temperature**: The randomness level of the model's output.  
+   Defaults to 0.1.
+      - Lower values lead to more deterministic and predictable outputs.
+      - Higher values lead to more creative and varied outputs.
+      - A temperature of zero results in the same output for the same prompt.
+   - **Top P**: Nucleus sampling.  
+      - Reduces the likelihood of generating repetitive or unnatural text by setting a threshold *P* and restricting the sampling to tokens with a cumulative probability exceeding *P*.
+      - Defaults to 0.3.
+   - **Presence penalty**: Encourages the model to include a more diverse range of tokens in the response.  
+      - A higher **presence penalty** value results in the model being more likely to generate tokens not yet been included in the generated text.
+      - Defaults to 0.4.
+   - **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
+      - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
+      - Defaults to 0.7.
 
 5. Now, let's start the show:
 

docs/guides/team/join_or_leave_team.md

 
 ## Leave a joined team
 
-![Image](https://github.com/user-attachments/assets/4e4c6971-131b-490b-85d8-b362e0811b86)
+![quit](https://github.com/user-attachments/assets/a9d812a9-382d-4913-83b9-d72cb5e7c953)

docs/release_notes.md

 
 Released on March 13, 2025.
 
+### Compatibility changes
+
+- Removes the **Max_tokens** setting from **Chat configuration**.
+- Removes the **Max_tokens** setting from **Generate**, **Rewrite**, **Categorize**, **Keyword** agent components.
+
+From this release onwards, if you still see RAGFlow's responses being cut short or truncated, check the **Max_tokens** setting of your model provider.
+
 ### Improvements
 
 - Adds OpenAI-compatible APIs.