fix ainode deployment

src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md

@@ -27,7 +27,7 @@
  AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection.
 
 ### 1.2 Delivery Method
- It is an additional package outside the IoTDB cluster, with independent installation and activation.
+ It is an additional package outside the IoTDB cluster, with independent installation.
 
 ### 1.3 Deployment mode
 <div >
@@ -82,42 +82,31 @@
 
   Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory
 
-  3. Switch to the iotdb dedicated folder to install the Python environment
-
-  Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example:
+3. Verify Python version
 
 ```shell
-  bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh
-  ```
-> Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt <br>
-> Close the current SSH window and reconnect
-
-   4. Create a dedicated environment
-
-```shell
-  conda create -n ainode_py python=3.11.9
+  python --version
   ```
+4. Create a virtual environment (execute in the ainode directory)
 
-  Type 'y' according to the prompt
+  ```shell
+   python -m venv venv
+   ```
 
-   5. Activate dedicated environment
+5. Activate the virtual environment
 
-```shell
-  conda activate ainode_py
-  ```
+  ```shell
+   source venv/bin/activate
+   ```
 
-   6. Verify Python version
 
-```shell
-  python --version
-  ```
-   7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
+  6. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
 
 ```shell
   unzip iotdb-enterprise-ainode-1.3.3.2.zip
   ```
 
-   8. Configuration item modification
+ 7. Configuration item modification
 
 ```shell
   vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties
@@ -127,13 +116,13 @@
 > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)<br>
 > ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode)
 
-   9. Replace Python source
+ 8. Replace Python source
 
 ```shell
   pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
   ```
 
-   10. Start the AINode node
+  9. Start the AINode node
 
 ```shell
   nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh  > myout.file 2>& 1 &

src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md

@@ -27,7 +27,7 @@
  AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection.
 
 ### 1.2 Delivery Method
- It is an additional package outside the IoTDB cluster, with independent installation and activation.
+ It is an additional package outside the IoTDB cluster, with independent installation.
 
 ### 1.3 Deployment mode
 <div >
@@ -107,71 +107,59 @@
     ./start-datanode.sh   -d   #The parameter'd 'will be started in the background 
     ```
 
-    2. Check the kernel architecture of Linux
+2. Check the kernel architecture of Linux
   ```shell
     uname -m
-    ```
+  ```
 
-    3. Import Python environment [Download](https://repo.anaconda.com/miniconda/)
+3. Import Python environment [Download](https://repo.anaconda.com/miniconda/)
 
     Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory
 
-    4. Switch to the iotdb dedicated folder to install the Python environment
-
-    Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example:
-
-  ```shell
-    bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh
-    ```
-  > Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt <br>
-  > Close the current SSH window and reconnect
+4. Verify Python version
 
-   5. Create a dedicated environment
+```shell
+  python --version
+  ```
+5. Create a virtual environment (execute in the ainode directory)
 
   ```shell
-    conda create -n ainode_py python=3.11.9
-    ```
+   python -m venv venv
+   ```
 
-    Type 'y' according to the prompt
-
-   6. Activate dedicated environment
+6. Activate the virtual environment
 
   ```shell
-    conda activate ainode_py
-    ```
+   source venv/bin/activate
+   ```
 
-   7. Verify Python version
-
-  ```shell
-    python --version
-    ```
-   8. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
+7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
 
   ```shell
     unzip iotdb-enterprise-ainode-1.3.3.2.zip
-    ```
+  ```
 
-   9. Configuration item modification
+8. Configuration item modification
 
   ```shell
     vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties
-    ```
+  ```
    Configuration item modification：[detailed information](#configuration-item-modification)
 
   > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)<br>
   > ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode)
 
-   10. Replace Python source
+9. Replace Python source
 
   ```shell
     pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
-    ```
+  ```
 
-   11. Start the AINode node
+10. Start the AINode node
 
   ```shell
     nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh  > myout.file 2>& 1 &
-    ```
+  ```
   > Return to the default environment of the system: conda deactivate
 
  ### 3.2 Configuration item modification

src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md

@@ -27,7 +27,7 @@
  AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection.
 
 ### Delivery Method
- It is an additional package outside the IoTDB cluster, with independent installation and activation.
+ It is an additional package outside the IoTDB cluster, with independent installation.
 
 ### Deployment mode
 <div >
@@ -82,42 +82,31 @@
 
   Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory
 
-  3. Switch to the iotdb dedicated folder to install the Python environment
-
-  Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example:
+  3. Verify Python version
 
 ```shell
-  bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh
-  ```
-> Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt <br>
-> Close the current SSH window and reconnect
-
-   4. Create a dedicated environment
-
-```shell
-  conda create -n ainode_py python=3.11.9
+  python --version
   ```
+4. Create a virtual environment (execute in the ainode directory)
 
-  Type 'y' according to the prompt
+  ```shell
+   python -m venv venv
+   ```
 
-   5. Activate dedicated environment
+5. Activate the virtual environment
 
-```shell
-  conda activate ainode_py
-  ```
+  ```shell
+   source venv/bin/activate
+   ```
 
-   6. Verify Python version
 
-```shell
-  python --version
-  ```
-   7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
+6. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
 
 ```shell
   unzip iotdb-enterprise-ainode-1.3.3.2.zip
   ```
 
-   8. Configuration item modification
+ 7. Configuration item modification
 
 ```shell
   vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties
@@ -127,13 +116,13 @@
 > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)<br>
 > ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode)
 
-   9. Replace Python source
+8. Replace Python source
 
 ```shell
   pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
   ```
 
-   10. Start the AINode node
+9. Start the AINode node
 
 ```shell
   nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh  > myout.file 2>& 1 &

src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md

@@ -27,7 +27,7 @@
  AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection.
 
 ### Delivery Method
- It is an additional package outside the IoTDB cluster, with independent installation and activation.
+ It is an additional package outside the IoTDB cluster, with independent installation.
 
 ### Deployment mode
 <div >
@@ -107,71 +107,59 @@
     ./start-datanode.sh   -d   #The parameter'd 'will be started in the background 
     ```
 
-    2. Check the kernel architecture of Linux
+2. Check the kernel architecture of Linux
   ```shell
-    uname -m
-    ```
+   uname -m
+   ```
 
-    3. Import Python environment [Download](https://repo.anaconda.com/miniconda/)
+3. Import Python environment [Download](https://repo.anaconda.com/miniconda/)
 
-    Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory
-
-    4. Switch to the iotdb dedicated folder to install the Python environment
-
-    Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example:
+   Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory
 
-  ```shell
-    bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh
-    ```
-  > Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt <br>
-  > Close the current SSH window and reconnect
+ 4. Verify Python version
 
-   5. Create a dedicated environment
+```shell
+  python --version
+  ```
+5. Create a virtual environment (execute in the ainode directory)
 
   ```shell
-    conda create -n ainode_py python=3.11.9
-    ```
-
-    Type 'y' according to the prompt
+   python -m venv venv
+   ```
 
-   6. Activate dedicated environment
+6. Activate the virtual environment
 
   ```shell
-    conda activate ainode_py
-    ```
+   source venv/bin/activate
+   ```
 
-   7. Verify Python version
-
-  ```shell
-    python --version
-    ```
-   8. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
+  7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package
 
   ```shell
     unzip iotdb-enterprise-ainode-1.3.3.2.zip
-    ```
+  ```
 
-   9. Configuration item modification
+   8. Configuration item modification
 
   ```shell
     vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties
-    ```
+  ```
    Configuration item modification：[detailed information](#configuration-item-modification)
 
   > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)<br>
   > ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode)
 
-   10. Replace Python source
+   9. Replace Python source
 
   ```shell
     pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
-    ```
+  ```
 
-   11. Start the AINode node
+   10. Start the AINode node
 
   ```shell
     nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh  > myout.file 2>& 1 &
-    ```
+  ```
   > Return to the default environment of the system: conda deactivate
 
  ### Configuration item modification