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Jetson AGX Orin📖
01.Get started
  • 01.Learning Route
  • 02.Getting Started Quickly
02.Jetson basic course
  • 01.Jetson board introduction
  • 02.Flash new system to the onboard eMMC
  • 03.Flash new system to an NVMe SSD
  • 04.Install Jetpack environment
  • 05.Backup SSD system
  • 06.Restore factory image system
  • 07.SSD expansion
  • 08.Solid State Drive Speed Test
03.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
04.GPIO control course
  • 01.GPIO description
  • 02.GPIO library installation
  • 03.GPIO reading
  • 04.GPIO output
  • 05.Serial communication
  • 06.I2C communication
05.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
06.Vision basic course
  • 01.USB camera preview
  • 02.Use Jupyter Lab
  • 03.Use JetCam
07.Vision advanced course
01.Environment construction
  • 01.TensorFlow
  • 02.PyTorch
  • 03.Torchvision
02.DeepStream development
  • 01.DeepStream environment
  • 02.Four types of detection(traffic)
03.YOLO11 development
  • 01.YOLO environment construction
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented 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
06.YOLO26 development
  • 01.YOLO Environment Setupnew
  • 02.CLI Usagenew
  • 03.Object Detectionnew
  • 04.Instance Segmentationnew
  • 05.Pose Estimationnew
  • 06.Image Classificationnew
  • 07.Oriented Bounding Boxes Object Detectionnew
  • 08.Model Conversionnew
  • 09.Dataset Annotationnew
  • 10.Model Training_Conversionnew
  • 11.Model Predictionnew
08.Docker basic course
  • 01.Docker introduction
  • 02.Docker installation
  • 03.Docker command
  • 04.Docker usage
  • 05.Docker interaction
09.ROS2-Humble
01.ROS2 basic course
  • 3.ROS2 development environment
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 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
02.ROS2 vision course
  • 01.Camera preview (USB)
  • 02.Camera calibration (USB)
  • 03.AR vision (USB)
10.Offline AI model course
Offline large model (Text Interaction)
  • 10.AI large model offline voice assistant
  • 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
11.Online AI model course
Online large model (Text Interaction)
  • 8.AI large model offline voice assistant
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal visual understand application
  • 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
12.Offline Generative AI Applications
  • 01.Children's Storytelling Session
  • 02.Cooking Assistant
  • 03.Homework tutor
  • 04.Image to animation
13.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
Download
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  • Code
  • Tools
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Welcome to Jetson AGX Orin repository

当製品の日本語版マニュアル資料は、こちらからご取得ください。

04.OpenClaw TUI Interaction

OpenClaw TUI Interaction

OpenClaw TUI Interaction1. How to Access the TUI2. What is the TUI Interface?3. Slash Commands4. Sessions and Memory5. Quick Start Workflow6. Troubleshooting Common Issues6.1 Commands Are Unresponsive6.2 The Bot Starts "Rambling" or "Misunderstanding You," or Seems Distracted by History6.3 Responses Are Becoming Increasingly Slow

The TUI (Text User Interface) serves as OpenClaw's "command-line chat window." When it is inconvenient to access the web console on your Jetson device—or if you are connected remotely via SSH—the TUI allows you to perform most daily interactions directly within your terminal: engaging in dialogue, switching models, checking status, managing sessions, invoking skills, and more.

OpenClaw TUI Interface (Replace with your own screenshot)

 

1. How to Access the TUI

Execute the following command in your terminal:

xxxxxxxxxx
openclaw tui

Note: The openclaw gateway does not require manual startup; it launches automatically upon system boot.

 

2. What is the TUI Interface?

You can think of the TUI as a "chat box with built-in commands":

  • Upper Section: Dialogue History (messages you sent, model responses, and tool/skill outputs)
  • Lower Section: Input Field (where you type questions or send slash commands)
  • Sending Messages: Type your input and press Enter to send.

For your first visit, we recommend doing two things right away:

xxxxxxxxxx
/status

3. Slash Commands

Slash commands must generally be sent as standalone messages beginning with a /. They are used to control the current session and execute specific operations.

CommandFunctionWhen to UseExample
/helpView help and command listWhen you don't know what commands are available/help
/statusCheck current statusIf you suspect a connection issue or want to check context usage/status
/newStart a new conversation thread (New Session)To switch topics or avoid context interference/new
/resetReset the session (Equivalent to starting over; has the same effect as /new)If the conversation has gone off track or you want to clear the context/reset
/model / /models listView/Switch modelsWhen you want to switch to a faster or more powerful model/models list
/think mediumSet the "thinking depth"For daily use, low or off is recommended/think medium
/stopAbort the current taskIf the system gets stuck or you want to stop immediately/stop
/context detailView the currently injected contextTo troubleshoot "why it remembers/forgets certain details"/context detail
/compactCompress older history into a summaryWhen the conversation is too long or the context buffer is nearly full/compact
/skill <name>Run a specific skillWhen you know the skill name and want to execute it directly/skill web_search

Two additional tips for a smoother "daily workflow":

  • It is safest to include only one slash command per message.
  • To quickly browse through all available commands, use /help or /commands.

4. Sessions and Memory

In OpenClaw, the roles of these two concepts are clearly defined:

  • Session: Manages "where the current conversation stands." When you use /new or /reset within the TUI, you are essentially switching to—or restarting—a session.
  • Memory: Manages "content that should be retained long-term, even across different sessions." This data is written to disk (in Markdown format) and can be retrieved back into the current session whenever needed. ### 4.1 Where Are Session Files Located?

Sessions are persisted to disk in JSONL format. Common locations include (subject to your actual installation path):

  • Index: ~/.openclaw/agents/<agentId>/sessions/sessions.json
  • Transcripts: ~/.openclaw/agents/<agentId>/sessions/<SessionId>.jsonl

For troubleshooting purposes, a more convenient approach is to first execute:

xxxxxxxxxx
openclaw status

This command typically displays the storage path as well as information regarding recent sessions. ### 4.2 How to "Put Memory to Use"

You can think of Memory as "having the bot take notes":

  • memory/YYYY-MM-DD.md: A daily process log, suitable for recording progress and ad-hoc decisions.
  • MEMORY.md: Long-term, stable information (preferences, fixed rules, project constraints, etc.).

Practical Tips:

  • To make a specific conclusion accessible across multiple sessions: Simply tell the bot, "Write this into MEMORY.md."
  • When preparing to switch to a new topic using /new: First use /compact—or write key decisions into Memory—before switching sessions.

5. Quick Start Workflow

  1. Enter the TUI: openclaw tui
  2. Check Status: /status
  3. Select a Model: /models list → /model <Number or Name>
  4. Daily Conversation: Simply type your question and press Enter.
  5. Switch Topics: /new
  6. Context Too Long: /compact
  7. Preserve Key Conclusions Long-Term: Ask the bot to write them into Memory.

6. Troubleshooting Common Issues

6.1 Commands Are Unresponsive

  • Ensure the command is sent on a separate line (do not mix it with regular text).
  • Use /help first to check which commands are supported in your current version.

6.2 The Bot Starts "Rambling" or "Misunderstanding You," or Seems Distracted by History

  • Start a new session: /new or /reset
  • Check what context is currently being injected: /context detail

6.3 Responses Are Becoming Increasingly Slow

  • Reduce "thinking depth": /think low or /think minimal
  • Compress conversation history: /compact
OpenClaw Local Model Deployment
OpenClaw WebChat Interaction

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