Miscellaneous editorial updates (#6805)

### What problem does this PR solve?



### Type of change

- [x] Documentation Update

docs/configurations.md

@@ -74,6 +74,8 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
 
 ### MinIO
 
+RAGFlow utilizes MinIO as its object storage solution, leveraging its scalability to store and manage all uploaded files.
+
 - `MINIO_CONSOLE_PORT`  
   The port used to expose the MinIO console interface to the host machine, allowing **external** access to the web-based console running inside the Docker container. Defaults to `9001`
 - `MINIO_PORT`  

docs/faq.mdx

@@ -108,7 +108,7 @@ Yes, we do.
 
 ---
 
-### Is it possible to share dialogue through URL?
+### Do you support sharing dialogue through URL?
 
 No, this feature is not supported.
 
@@ -449,3 +449,7 @@ To switch your document engine from Elasticsearch to [Infinity](https://github.c
 ```bash
 $ docker compose -f docker-compose.yml up -d
 ```
+
+### Where are my uploaded files stored in RAGFlow's image?
+
+All uploaded files are stored in Minio, RAGFlow's object storage solution. For instance, if you upload your file directly to a knowledge base, it is located at `<knowledgebase_id>/filename`.

docs/guides/agent/agent_component_reference/begin.mdx

@@ -31,10 +31,6 @@ An opening greeting is the agent's first message to the user. It can be a welcom
 
 You can set global variables within the **Begin** component, which can be either required or optional. Once established, users will need to provide values for these variables when interacting or chatting with the agent. Click **+ Add variable** to add a global variable, each with the following attributes:
 
-:::caution WARNING
-If your agent's **Begin** component takes a variable, you *cannot* embed it into a webpage.
-:::
-
 - **Key**: *Required*  
   The unique variable name.
 - **Name**: *Required*  
@@ -50,8 +46,15 @@ If your agent's **Begin** component takes a variable, you *cannot* embed it into
   - **boolean**: Requires the user to toggle between on and off.
 - **Optional**: A toggle indicating whether the variable is optional. 
 
-:::danger IMPORTAN
-If you set the key type as **file**, ensure the token count of the uploaded file does not exceed your model provider's maximum token limit; otherwise, the plain text in your file will be truncated and incomplete.
+:::tip NOTE
+To pass in parameters from a client, call:
+- HTTP method [Converse with agent](../../references/http_api_reference.md#converse-with-agent), or
+- Python method [Converse with agent](../../referencespython_api_reference.md#converse-with-agent).
+:::
+
+:::danger IMPORTANT
+- If you set the key type as **file**, ensure the token count of the uploaded file does not exceed your model provider's maximum token limit; otherwise, the plain text in your file will be truncated and incomplete.
+- If your agent's **Begin** component takes a variable, you *cannot* embed it into a webpage.
 :::
 
 ## Examples

docs/guides/chat/start_chat.md

@@ -44,6 +44,9 @@ You start an AI conversation by creating an assistant.
      - If **Rerank model** is selected, the hybrid score system uses keyword similarity and reranker score, and the default weight assigned to the reranker score is 1-0.7=0.3.
    - **Variable** refers to the variables (keys) to be used in the system prompt. `{knowledge}` is a reserved variable. Click **Add** to add more variables for the system prompt.
       - If you are uncertain about the logic behind **Variable**, leave it *as-is*.
+      - As of v0.17.2, if you add custom variables here, the only way you can pass in their values is to call:
+         - HTTP method [Converse with chat assistant](../../references/http_api_reference.md#converse-with-chat-assistant), or
+         - Python method [Converse with chat assistant](../../references/python_api_reference.md#converse-with-chat-assistant).
 
 4. Update **Model Setting**:
 

docs/guides/models/deploy_local_llm.mdx

@@ -28,7 +28,7 @@ This user guide does not intend to cover much of the installation or configurati
 - For a complete list of supported models and variants, see the [Ollama model library](https://ollama.com/library).
 :::
 
-### 1. Deploy ollama using docker
+### 1. Deploy Ollama using Docker
 
 ```bash
 sudo docker run --name ollama -p 11434:11434 ollama/ollama
@@ -36,14 +36,14 @@ time=2024-12-02T02:20:21.360Z level=INFO source=routes.go:1248 msg="Listening on
 time=2024-12-02T02:20:21.360Z level=INFO source=common.go:49 msg="Dynamic LLM libraries" runners="[cpu cpu_avx cpu_avx2 cuda_v11 cuda_v12]"
 ```
 
-Ensure ollama is listening on all IP address:
+Ensure Ollama is listening on all IP address:
 ```bash
 sudo ss -tunlp | grep 11434
 tcp   LISTEN 0      4096                  0.0.0.0:11434      0.0.0.0:*    users:(("docker-proxy",pid=794507,fd=4))
 tcp   LISTEN 0      4096                     [::]:11434         [::]:*    users:(("docker-proxy",pid=794513,fd=4))
 ```
 
-Pull models as you need. It's recommended to start with `llama3.2` (a 3B chat model) and `bge-m3` (a 567M embedding model):
+Pull models as you need. We recommend that you start with `llama3.2` (a 3B chat model) and `bge-m3` (a 567M embedding model):
 ```bash
 sudo docker exec ollama ollama pull llama3.2
 pulling dde5aa3fc5ff... 100% ▕████████████████▏ 2.0 GB
@@ -58,20 +58,20 @@ success
 
 ### 2. Ensure Ollama is accessible
 
-If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessible from inside the RAGFlow container:
+- If RAGFlow runs in Docker and Ollama runs on the same host machine, check if Ollama is accessible from inside the RAGFlow container:
 ```bash
 sudo docker exec -it ragflow-server bash
-root@8136b8c3e914:/ragflow# curl  http://host.docker.internal:11434/
+curl  http://host.docker.internal:11434/
 Ollama is running
 ```
 
-If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessible from RAGFlow host machine:
+- If RAGFlow is launched from source code and Ollama runs on the same host machine as RAGFlow, check if Ollama is accessible from RAGFlow's host machine:
 ```bash
 curl  http://localhost:11434/
 Ollama is running
 ```
 
-If RAGFlow and Ollama run on different machines, check if ollama is accessible from RAGFlow host machine:
+- If RAGFlow and Ollama run on different machines, check if Ollama is accessible from RAGFlow's host machine:
 ```bash
 curl  http://${IP_OF_OLLAMA_MACHINE}:11434/
 Ollama is running
@@ -88,8 +88,8 @@ In RAGFlow, click on your logo on the top right of the page **>** **Model provid
 
 In the popup window, complete basic settings for Ollama:
 
-1. Ensure model name and type match those been pulled at step 1, For example, (`llama3.2`, `chat`), (`bge-m3`, `embedding`).
-2. Ensure that the base URL match which been determined at step 2.
+1. Ensure that your model name and type match those been pulled at step 1 (Deploy Ollama using Docker). For example, (`llama3.2` and `chat`) or (`bge-m3` and `embedding`).
+2. Ensure that the base URL match the URL determined at step 2 (Ensure Ollama is accessible).
 3. OPTIONAL: Switch on the toggle under **Does it support Vision?** if your model includes an image-to-text model.
 
 
@@ -104,15 +104,12 @@ Max retries exceeded with url: /api/chat (Caused by NewConnectionError('<urllib3
 
 Click on your logo **>** **Model providers** **>** **System Model Settings** to update your model:
    
-*You should now be able to find **llama3.2** from the dropdown list under **Chat model**, and **bge-m3** from the dropdown list under **Embedding model**.*
-
-> If your local model is an embedding model, you should find your local model under **Embedding model**.
+- *You should now be able to find **llama3.2** from the dropdown list under **Chat model**, and **bge-m3** from the dropdown list under **Embedding model**.*
+- _If your local model is an embedding model, you should find it under **Embedding model**._
 
 ### 7. Update Chat Configuration
 
-Update your chat model accordingly in **Chat Configuration**:
-
-> If your local model is an embedding model, update it on the configuration page of your knowledge base.
+Update your model(s) accordingly in **Chat Configuration**.
 
 ## Deploy a local model using Xinference
 

docs/guides/team/join_or_leave_team.md

@@ -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. To view and update the team owner's shared knowledge base, the team owner must set a knowledge base's **Permissions** to **Team**.
 
 ## Accept or decline team invite
 
@@ -39,4 +39,4 @@ _After accepting the team invite, you should be able to view and update the team
 
 ## Leave a joined team
 
-![quit](https://github.com/user-attachments/assets/a9d812a9-382d-4913-83b9-d72cb5e7c953)
+![leave_team](https://github.com/user-attachments/assets/16f31462-27e5-4a13-b9dc-dd7f1bcc43f0)

docs/guides/team/manage_team_members.md

@@ -3,7 +3,7 @@ sidebar_position: 1
 slug: /manage_team_members
 ---
 
-# Team
+# Manage team members
 
 Invite or remove team members.
 

docs/references/http_api_reference.md

@@ -2679,9 +2679,13 @@ Asks a specified agent a question to start an AI-powered conversation.
   - `"sync_dsl"`: `boolean` (optional)
   - other parameters: `string`
 
+:::info IMPORTANT
+You can include custom parameters in the request body, but first ensure they are defined in the [Begin](../guides/agent/agent_component_reference/begin.mdx) agent component.
+:::
+
 ##### Request example
 
-If the **Begin** component does not take parameters, the following code will create a session.
+- If the **Begin** component does not take parameters, the following code will create a session.
 
 ```bash
 curl --request POST \
@@ -2693,7 +2697,7 @@ curl --request POST \
      }'
 ```
 
-If the **Begin** component takes parameters, the following code will create a session.
+- If the **Begin** component takes parameters, the following code will create a session.  
 
 ```bash
 curl --request POST \