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Jetson AGX Thor📖
1.Get started
  • 01.Learning Route
  • 02.Getting Started Quickly
2.Jetson basic course
  • 01.Jetson board introduction
  • 02.Flashing a Pure Jetson System via SDK
  • 03.Flashing a Pure Jetson System via USB Drive
  • 04.Flashing the Jetson Bootloader using L4T
  • 05.Replacing the SSD
  • 06.Install Jetpack environment
  • 07.Backup SSD system
  • 08.Restore factory image system
  • 09.SSD expansion
  • 10.SSD Speed Test
3.Basic setting course
  • 01.Basic knowledge
  • 02.Network configuration
  • 03.SSH remote login
  • 04.VNC remote control
  • 05.Remote file transfer
  • 06.Jtop tool
  • 07.Exchange space expansion
  • 08.Use VSCode
  • 09.Use VMware
  • 10.Change screen resolution
  • 11.Virtual Desktop
  • 12.Set root user password
  • 13.Configure sudo passwordless operation
  • 14.Managing custom services
  • 15.View system version information
4.OpenCV basic course
  • 01.Image reading
  • 02.Image saving
  • 03.Image modification
  • 04.Image scaling
  • 05.Image cropping
  • 06.Image translation
  • 07.Image mirroring
  • 08.Image grayscale conversion
  • 09.Image binarization
  • 10.Image edge detection
  • 11.Add line segments
  • 12.Add rectangles
  • 13.Add circular shape
  • 14.Add ellipses
  • 15.Add polygons
  • 16.Add Text
5.Vision basic course
  • 01.USB camera preview
  • 02.Use Jupyter Lab
  • 03.Use JetCam
6.Vision advanced course
01.Environment construction
  • 01.TensorFlow
  • 02.PyTorch
  • 03.Torchvision
  • 04.Torchaudio
02.DeepStream development
  • 01.DeepStream environment
  • 02.Four types of detection(traffic)
03.YOLO26 development
  • 01.YOLO Environment Setup
  • 02.CLI Usage
  • 03.Object Detection
  • 04.Instance Segmentation
  • 05.Pose Estimation
  • 06.Image Classification
  • 07.Oriented Bounding Boxes Object Detection
  • 08.Model Conversion
  • 09.Dataset Annotation
  • 10.Model Training_Conversion
  • 11.Model Prediction
04.Mediapipe development
  • 01.Mediapipe environment
  • 02.Hand detection
  • 03.Face detection
  • 04.Face effects
  • 05.3D object recognition
  • 06.Virtual brush
  • 07.Gesture recognition
  • 08.Finger control
  • 09.Posture estimation
  • 10.Face mask
  • 11.Overall detection
  • 12.Green scene removal(Human)
05.QR code recognition
  • 01.Barcode Recognition
  • 02.QR Code Recognition
  • 03.Machine Code Recognition
  • 04.Handwritten Digit Recognition
7.Docker basic course
  • 01.Docker introduction
  • 02.Docker installation
  • 03.Docker command
  • 04.Docker usage
  • 05.Docker interaction
8.ROS2-jazzy
1.ROS2 basic course
  • 1.Introduction to ROS2
  • 2.ROS2 install Jazzy
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
2.ROS2 vision course
  • 01.Camera preview (USB)
  • 02.Camera calibration (USB)
  • 03.AR vision (USB)
9.Offline AI model course
Offline large model (Text Interaction)
  • 1.Al large model environment deployment
  • 2.Install large model dialogue platform
  • 3.Meta Al Llama3.2 model
  • 4.Alibaba Cloud Qwen3 model
  • 5.Microsoft Phi-4-mini model
  • 6.DeepSeek DeepSeek-R1 model
  • 7.Alibaba Cloud Qwen2.5v visual multimodal large model
  • 8.Google Gemma3 visual multimodal large model
  • 9.Lava visual multimodal large model
  • 10.MiniCPM-V visual multimodal large model
  • 11.Multimodal visual understand application
  • 12.Multimodal text image application
  • 13.Multimodal video analysis application
  • 14.Multi module visual position application
  • 15.Multimodal table scanning application
  • 16.Multimodal autonomous agent application
Offline large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Offline speech to text (ASR)
  • 2.Offline text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal text and graphics application
  • 6.Multimodal video analysis application
  • 7.Multi module visual position application
  • 8.Multimodal table scanning application
  • 9.Multimodal autonomous proxy application
  • 10.AI large model offline voice assistant
10.Online AI model course
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal Video Analysis Applications
  • 3.Multimodal visual localization application
  • 4.Multimodal table scanning application
  • 5.Multimodal autonomous proxy application
Online large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Online speech to text (ASR)
  • 2.Online text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multi module visual position application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model offline voice assistant
11.Generative AI Applications
12.OpenClaw Advanced Development
  • 00.OpenClaw Quick Start on Jetson Platform
  • 01.OpenClaw Installation
  • 02.OpenClaw Online Platform Deployment
  • 03.OpenClaw Local Model Deployment
  • 04.OpenClaw TUI Interaction
  • 05.OpenClaw WebChat Interaction
  • 06.OpenClaw Tools Introduction
  • 07.OpenClawGate Gateway User Manual
  • 08.OpenClaw Features Overview
  • 09.OpenClawClawHub Introduction (Skill Installation)
  • 10. OpenClaw Switching Models
  • 11.OpenClaw Application - File Management
  • 12.OpenClaw Application - Camera
  • 13.OpenClaw Application - Browser Control
  • 14.OpenClaw Application - Script Execution
  • 15.OpenClaw Application - AI Programming
  • 16.OpenClaw Application - Dedicated AI Assistant
  • 17.OpenClaw WhatsApp Plugin Application
  • 18.OpenClaw Voice Assistant
Download
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  • Tools
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Welcome to Jetson AGX Thor repository

8.AI large model offline voice assistant

8.AI large model offline voice assistant

AI Large-Scale Online Voice Assistant

AI Large-Scale Online Voice Assistant1. Online Voice Configuration2. Creating a Startup Script2.1 Creating the Startup Script3. Startup Management3.1 Disabling the Startup Program3.2 Enabling the Startup Program

1. Online Voice Configuration

Before setting up auto-start, we must ensure that the program itself can work independently while online. This requires modifying the configuration file.

  1. Locate the Configuration File:

In your project code, find and open the configuration file:

config/yahboom.yaml

  1. Modify Configuration Parameters:

Please check the following parameters in the file and ensure that their values are consistent with those shown below. If the parameters are not present, please add them.

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   asr:                                    # Voice Node Parameters
     ros__parameters:
       VAD_MODE: 2                        #VAD Sensitivity
       sample_rate: 16000                  #ASR Recording Audio Sampling Rate
       frame_duration_ms:  30              #VAD frame size (in milliseconds)
       use_oline_asr: True                # Whether to use online ASR (True: use online; False: use offline)
       mic_serial_port: "/dev/ttyUSB0"     #Microphone Serial Port Alias
       mic_index: 0                        #Microphone Index
       language: 'zh'                      #ASR Language
   
   model_service:                          # Model Server Node Parameters
     ros__parameters:
       language: 'zh'                      #Large Language Model API
       useolinetts: True                   # Whether to use online speech synthesis (True for online, False for offline)
   
        # Large Model Configuration
       # llm_platform: 'ollama'              # Available Platforms: 'ollama', 'tongyi', 'spark', 'qianfan', 'openrouter'
       llm_platform: 'tongyi'              # Here, we take Tongyi as an example.
   
  • use_online_asr and use_online_tts must be set to tongyi.
  • llm_platform must be set to tongyi.

With these settings, the entire system will operate in a purely online mode.

  1. Save the file and rebuild the project to apply the changes:
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cd ~/yahboom_ws
colcon build
source install/setup.bash

Once this step is complete, the program will function as a purely online voice service.

 

2. Creating a Startup Script

Now, we will create a startup script to ensure that largemodel_control.launch.py runs automatically whenever the system boots up.

2.1 Creating the Startup Script

To ensure the system correctly loads the ROS 2 environment, the best practice is to create a simple script that opens a new terminal window to execute the launch command.

  1. Create the script file: In the directory ~/yahboom_ws/src/largemodel/, create a file named start_largemodel.sh.
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vim ~/yahboom_ws/src/largemodel/start_largemodel.sh
  1. Write the script content: Copy and paste the following content into the script file.
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#!/bin/bash
​
sleep 10
gnome-terminal -- bash -c "export RUN_PROGRAMS='ros2 launch largemodel largemodel_control.launch.py';exec bash"

Here, RUN_PROGRAMS specifies the command to be executed.

  1. Save and exit the editor.
  2. Grant execute permissions to the script:
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chmod +x ~/yahboom_ws/src/largemodel/start_largemodel.sh
  1. Add the execution command to .bashrc

Open ~/.bashrc:

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vim ~/.bashrc

Copy and paste the following line to the very end of the file:

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eval $RUN_PROGRAMS

Save and exit. ### 2.2 Creating the Startup File

  1. Open the system terminal, then create and edit the start_largemodel.desktop startup file:
xxxxxxxxxx
vim ~/.config/autostart/start_largemodel.desktop
  1. Copy the following content into start_largemodel.desktop, then save and exit.
xxxxxxxxxx
[Desktop Entry]
Type=Application
Exec=sh /home/jetson/yahboom_ws/src/largemodel/start_largemodel.sh
Hidden=false
NoDisplay=false
X-GNOME-Autostart-enabled=true
Name[en_US]=start_largemodel
Name=start_largemodel
Comment[en_US]=
Comment=

image-20260407171543457

In the above configuration: Exec specifies the command used to execute the script; X-GNOME-Autostart-enabled determines whether the program launches automatically upon system startup; and Name specifies the display name.

Restart the system, and the startup program will automatically launch upon boot.

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sudo reboot

 

3. Startup Management

After restarting the system, a system terminal window will pop up, automatically running the voice assistant program. If you need to temporarily exit the program, press the [Ctrl+C] keys, and then close the terminal window.

3.1 Disabling the Startup Program

If you no longer require the program to launch automatically upon system startup, edit the start_largemodel.desktop startup file. Change the X-GNOME-Autostart-enabled parameter to false, then save and exit. This ensures that the program will not launch the next time the system starts up.

xxxxxxxxxx
vim ~/.config/autostart/start_largemodel.desktop

Example Content:

xxxxxxxxxx
[Desktop Entry]
Type=Application
Exec=sh /home/jetson/yahboom_ws/src/largemodel/start_largemodel.sh
Hidden=false
NoDisplay=false
X-GNOME-Autostart-enabled=false
Name[en_US]=start_largemodel
Name=start_largemodel
Comment[en_US]=
Comment=

3.2 Enabling the Startup Program

If you require the program to launch automatically upon system startup, edit the start_largemodel.desktop startup file. Change the X-GNOME-Autostart-enabled parameter to true, then save and exit. Upon restarting the system, the program will launch automatically.

xxxxxxxxxx
vim ~/.config/autostart/start_largemodel.desktop

Example Content:

xxxxxxxxxx
Multimodal autonomous proxy application
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