Minor style changes (#11554)

### What problem does this PR solve?

### Type of change


- [ ] Documentation Update

docs/guides/agent/agent_component_reference/agent.mdx

@@ -22,7 +22,7 @@ An **Agent** component is essential when you need the LLM to assist with summari
 
 1. Ensure you have a chat model properly configured:
 
-![Set default models](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/set_default_models.jpg)
+  ![Set default models](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/set_default_models.jpg)
 
 2. If your Agent involves dataset retrieval, ensure you [have properly configured your target dataset(s)](../../dataset/configure_knowledge_base.md).
 
@@ -91,7 +91,7 @@ Update your MCP server's name, URL (including the API key), server type, and oth
 
    *The target MCP server appears below your Agent component, and your Agent will autonomously decide when to invoke the available tools it offers.*
 
-![](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/choose_tavily_mcp_server.jpg)
+  ![](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/choose_tavily_mcp_server.jpg)
 
 ### 5. Update system prompt to specify trigger conditions (Optional)
 

docs/guides/agent/sandbox_quickstart.md

@@ -62,9 +62,9 @@ docker build -t sandbox-executor-manager:latest ./executor_manager
 
 3. Add the following entry to your /etc/hosts file to resolve the executor manager service:
 
-```bash
-127.0.0.1 es01 infinity mysql minio redis sandbox-executor-manager
-```
+    ```bash
+    127.0.0.1 es01 infinity mysql minio redis sandbox-executor-manager
+    ```
 
 4. Start the RAGFlow service as usual.
 
@@ -74,24 +74,24 @@ docker build -t sandbox-executor-manager:latest ./executor_manager
 
 1. Initialize the environment variables:
 
-```bash
-cp .env.example .env
-```
+    ```bash
+    cp .env.example .env
+    ```
 
 2. Launch the sandbox services with Docker Compose:
 
-```bash
-docker compose -f docker-compose.yml up
-```
+    ```bash
+    docker compose -f docker-compose.yml up
+    ```
 
 3. Test the sandbox setup:
 
-```bash
-source .venv/bin/activate
-export PYTHONPATH=$(pwd)
-uv pip install -r executor_manager/requirements.txt
-uv run tests/sandbox_security_tests_full.py
-```
+    ```bash
+    source .venv/bin/activate
+    export PYTHONPATH=$(pwd)
+    uv pip install -r executor_manager/requirements.txt
+    uv run tests/sandbox_security_tests_full.py
+    ```
 
 ### Using Makefile
 

docs/guides/chat/start_chat.md

@@ -83,13 +83,13 @@ You start an AI conversation by creating an assistant.
 
 1. Click the light bulb icon above the answer to view the expanded system prompt:
 
-![prompt_display](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/prompt_display.jpg)
+   ![prompt_display](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/prompt_display.jpg)
 
    *The light bulb icon is available only for the current dialogue.*
 
 2. Scroll down the expanded prompt to view the time consumed for each task:
 
-![time_elapsed](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/time_elapsed.jpg)
+   ![time_elapsed](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/time_elapsed.jpg)
 :::
 
 ## Update settings of an existing chat assistant

docs/guides/dataset/use_tag_sets.md

@@ -56,9 +56,9 @@ Once a tag set is created, you can apply it to your dataset:
 1. Navigate to the **Configuration** page of your dataset.
 2. Select the tag set from the **Tag sets** dropdown and click **Save** to confirm.
 
-:::tip NOTE
-If the tag set is missing from the dropdown, check that it has been created or configured correctly.
-:::
+   :::tip NOTE
+   If the tag set is missing from the dropdown, check that it has been created or configured correctly.
+   :::
 
 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._