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Raspberry Pi 5📖
00.Quick Start (Must See)
  • 1.Quick Start (Must See)
  • 2.TF card expand capacity
  • 3.Raspberry Pi 5 - 1GB Version Must - See Before Use
01.Introduction to Raspberry PI 5
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Installation and introduction of shell and active radiator
  • 6. GPIO and 40-pin pins
  • 7. Tips for using Raspberry PI 5
  • 8. Raspberry PI PCIe connector
  • 9. MIPI CSI DSI connector
  • 10. UART connector
  • 11. Real-time clock
  • 12. Power over Ethernet (PoE) connector
02.Introduction to common mirror systems
  • 1. Official Raspberry PI system
  • 2. Ubuntu
03.Basic settings of Raspberry Pi
  • 1. Update and upgrade operating system
  • 2.Introduction to raspi-config tool
  • 3.config.txt file description
  • 4.Network Configuration
  • 5.remote access
  • 6.Transfer files remotely
  • 7.Set display resolution and rotation
  • 8.Set screen to sleep
  • 9.Get real-time temperature of Raspberry Pi
  • 10.Play audio and video
  • 11.Using USB camera
  • 12.Using MIPI camera
04.Basic programming course
1. C language programming
  • 1. C language environment construction
  • 2. Print Hello World
2. Python programming
  • 1.Python usage
  • 2.Use APT to install Python packages
  • 3.Python virtual environment
  • 4.GPIO Zero
  • 5.Pin output high and low levels
  • 6.Pin reads high and low levels
  • 7.Pin output PWM
3.Jupyter lab programming
  • 1.Jupyter Lab environment construction
  • 2.Basic use of Jupyter Lab
  • 3.Jupyter Lab plug-in installation
  • 4.Basic use of Jupyter Widgets
05.Advanced AI course
5.Advanced AI gameplay
  • 1. Human pose estimation
  • 2. target detection
  • 3.yolov5
  • 4. Camera display
  • 5. QR code
  • 6. face detection
  • 7. Color recognition
2.Getting started with Open Source CV
  • 1. Introduction to Open Source CV
  • 2. Read and display Open Source CV images
  • 3. Open Source CV image writing
  • 4. Open Source CV image quality
  • 5.Open Source CV pixel operation
3.Open Source CV Geometric Transformations
  • 1. Image resizing
  • 2. Cut the image
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine transformation
  • 6. Rotate the image
  • 7. Perspective transformation
4.Text Picture Drawing Open Source CV image processing and drawing text line segments
  • 1、Grey Processing
  • 2、image binaryzation
  • 3、edge detection
  • 4、Line segment drawing
  • 5、Rectangle and circle drawing
  • 6、Text image drawing
1.Open Source CV environment setup
  • Open Source CV environment setup
6.YOLOv11 development
  • 1. YOLOv11 environment construction
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model conversion
  • 9. Dataset Annotation
  • 10. Model training_conversion
  • 11. Model prediction
7.YOLO26 development
  • 01.YOLO26 environment
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented bounding box object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training - conversion
  • 11.Model prediction
06.Mediapipe course
  • 1. Face special effects
  • 2. Face detection
  • 3. Three-dimensional object recognition
  • 4. Paintbrush
  • 5. Finger control
  • 6. Gesture recognition
07.Docker Tutorial
  • 1.Overview and installation
  • 2.Common commands
  • 3.Understand and publish images
  • 4.Hardware interaction data processing
  • 5.Enter docker container
  • 6.Update docker images
  • 7. docker container to install ROS using accessories
08.ROS1 advanced tutorial
1.ROS1 basic course
  • 1.ROS introduction
  • 2.ROS installation
  • 3.ROS common command tools
  • 4.ROS workspace
  • 5.ROS function package
  • 6.ROS node
  • 7.ROS topic publisher
  • 8.ROS topic subscribers
  • 9.ROS service client
  • 10.ROS service server
  • 11.ROS action client
  • 12.ROS action server
  • 13.ROS custom message reception
  • 14.ROS-launch file
  • 15.ROS-TF transformation
  • 16.ROS parameter service
  • 17.ROS-rviz use
  • 18.ROS-rqt tool usage
  • 19.Topic message recording and playback
  • 20.urdf model introduction
  • 21.gazebo introduction
  • 22.ROS distributed communication
2.ROS1 vision application
  • 0.Precautions
  • 1.AR vision
  • 2.AR QR code
  • 3.ROS+Opencv basics
  • 4.Face recognition
  • 5.harris corner detection
  • 6.Target tracking algorithm
  • 7.Contour moment
  • 8.Polygon outline
  • 9.Discrete fourier transform algorithm
  • 10.Edge detection algorithm
  • 11.Face detection algorithm
  • 12.Optical flow detection algorithm
  • 13.Contour detection
  • 14.General contour detection
  • 15.Feature point tracking
  • 16.HLS color filtering
  • 17.Hough circle detection
  • 18.Hough linear detection
  • 19.HSV color filtering
  • 20.LK optical flow algorithm
  • 21.detection algorithm
  • 22.Phase dependent displacement detection
  • 23.Image pyramid sampling algorithm
  • 24.RGB color filtering
  • 25.Clear background detection algorithm
  • 26.Simplified optical flow algorithm
  • 27.Simple filter
  • 28.Threshold image processing
  • 29.Watershed segmentation algorithm
09.ROS2 advanced tutorial
1.ROS2 basic course
  • 1. Introduction to ROS2
  • 2.ROS2 install Humble
  • 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 application
  • 0.Precautions
  • 1.Opencv basic course
  • 2.ROS+opencv application
  • 3.QR code creation and recognition
  • 4.AR vision
  • 5.Interesting gameplay of mediapipe
10.Offline AI model coursenew
Offline large model (Text Interaction)
  • 0. AI large model image description
  • 1. Deployment of large AI model environments
  • 2. Switch Chinese input method
  • 3. Installation of large model dialogue platform
  • 4. Meta AI Llama 3.2 model
  • 5. Alibaba Cloud Qwen3 Model
  • 6. Microsoft Phi-4-mini model
  • 7. DeepSeek DeepSeek-R1 model
  • 8. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 9. Google Gemma3 Visual Multimodal Large Model
  • 10. Llava Visual Multimodal Large Model
  • 11.MiniCPM-V Visual Multimodal Large Model
  • 12. Multimodal Visual Understanding Applications
  • 13. Multimodal Text-Based Image Application
  • 14. Multimodal Video Analysis Application
  • 15. Multimodal visual positioning applications
  • 16. Multimodal table scanning application
  • 17. Multimodal Autonomous Agent Application
Offline large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Offline speech-to-text (ASR)
  • 2. Offline Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual understanding and voice interaction
  • 5. Multimodal Text-Based Image Application
  • 6. Multimodal Video Analysis Application
  • 7. Multimodal visual positioning applications
  • 8. Multimodal table scanning application
  • 9. Multimodal Autonomous Agent Applications
  • 10. AI large model offline voice assistant
11.Online AI model coursenew
Online large model (text interaction)
  • 1.OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Applications
  • 3. Multimodal visual positioning applications
  • 4. Multimodal table scanning application
  • 5. Multimodal Autonomous Agent Applications
Online large model (voice interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Online speech-to-text (ASR)
  • 2. Online Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual and voice interaction
  • 5. Multimodal visual positioning applications
  • 6. Multimodal table scanning application
  • 7. Multimodal Autonomous Agent Applications
  • 8. AI large model online voice assistant
12.OpenClaw Deployment and Basic Usagenew
  • 01. OpenClaw Deployment
  • 02. OpenClaw WhatsApp Plugin Application
  • 03. OpenClaw WebChat Interaction
  • 04. OpenClaw TUI Interaction
  • 05. OpenClaw Tools Introduction
  • 06. OpenClawGate Gateway User Manual
  • 07. OpenClaw Features Overview
  • 08. OpenClawHub Introduction (Skill Installation)
  • 09. OpenClaw Application - File Management
  • 10. OpenClaw Application - Camera
  • 11. OpenClaw Application - Browser Control
  • 12. OpenClaw Application - Script Execution
  • 13. OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 14. OpenClaw Application - Dedicated AI Assistant
13.OpenClaw Advanced Developmentnew
1.Preparation Before Use
  • 01. Peripheral Hardware Configuration
  • 02. OpenClaw API-KEY Configuration
  • 03. OpenClaw Model Switching
  • 04. OpenClaw Prompts
  • 05. AI Voice Interaction Configuration
  • 06. 3D Configuration Tests
2.OpenClaw AI Programming Peripheral Control
  • 1. Servo Control
  • 2. RGB Strip
  • 3. OLED Display
  • 4. Temperature and Humidity Sensor
  • 5. Camera Application
  • 6. AI Script Peripheral Control
3.OpenClaw Peripheral Integration Applications
  • 1. Plant Care Assistant
  • 2. AI Calorie Estimation
  • 3. AI Rock Paper Scissors Game
  • 4. AI Pet
  • 5. AI Weather Station
  • 6. Temperature and Humidity Dashboard
  • 7. Scheduled Tasks
Download
  • SystemFile
  • Code
  • SoftWare
  • 3D_Model_File
  • GuideManual
Download ZIP

Welcome to Raspberry Pi 5 repository

02. OpenClaw API-KEY Configuration

OpenClaw API-KEY Configuration

OpenClaw API-KEY Configuration1. Course Overview1.1 Course Content2. API-KEY Application2.1 Recommended Model Service Providers3. Configure OpenClaw API-KEY3.1 Configuration Method3.2 Quick Configuration3.2.1 Configure baseUrl3.2.2 Fill in apiKey and baseUrl4. View Connected Model Status4.1 View Configured Model List4.2 Verify Configuration Success5. Other Access Methods (Advanced)5.1 CLI Command Configuration API-KEY (Suitable for Beginners)5.2 Modify Configuration File (Recommended Method)Configuration File LocationEdit Configuration File6. Common Problems and Solutions6.1 API-KEY Invalid or Error6.2 Cannot Access Model Service7. Course Summary

1. Course Overview

This course will introduce in detail how to configure API-KEY for AI model services for OpenClaw, including the API-KEY application process, two configuration methods (CLI command configuration and configuration file modification), and how to verify if the configuration is successful. After completing this course, you will be able to successfully connect and use various AI major model service providers.

1.1 Course Content

  • Understand the types of model service providers supported by OpenClaw
  • Master the API-KEY application method
  • Learn how to view and verify the status of connected models

2. API-KEY Application

2.1 Recommended Model Service Providers

  • OpenClaw supports many model service providers, including:

    • OpenAI - GPT series (API + Codex)
    • Anthropic - Claude series (API + Claude Code)
    • Google - Gemini series
    • Alibaba Cloud - Qwen Cloud, Tongyi Qianwen
    • DeepSeek - DeepSeek models
    • Zhipu AI - GLM models
    • Moonshot - Kimi + Kimi Coding
    • Ollama - Local models (cloud + local)
    • And many other service providers
  • You can freely choose a model service provider based on your actual needs and network policies in your region, and register and apply for API-KEY on the corresponding official website

3. Configure OpenClaw API-KEY

3.1 Configuration Method

OpenClaw provides two methods to configure API-KEY:

  1. CLI command configuration (suitable for beginners)

  2. Directly modify configuration file (suitable for developers)

    • Configuration file path: $HOME/.openclaw/openclaw.json

3.2 Quick Configuration

  • The factory preset configuration file has already configured Bailian model parameters; Simply fill in your API-KEY and baseUrl to start using it directly.
  • Open the OpenClaw configuration file:
xxxxxxxxxx
nano $HOME/.openclaw/openclaw.json

3.2.1 Configure baseUrl

  • Users need to configure the tongyi_base_url corresponding to their account. Go to the Model Service Platform Bailian Console to apply for an API key. Copy the API key and OpenAI-compatible address (Base URL), then fill them into the corresponding fields.

image-20260529165252065

image-2026081016526666

3.2.2 Fill in apiKey and baseUrl

image-20260427175701480

  • After filling in, press Ctrl+X, then press Y to confirm save, and press Enter to exit

4. View Connected Model Status

4.1 View Configured Model List

After configuration, you can use the following command to view the connected models:

xxxxxxxxxx
openclaw models list

image-20260429144931444

4.2 Verify Configuration Success

  1. Test conversation

    xxxxxxxxxx
    openclaw tui

    Start the TUI interface, send a test message (such as "May I have your name?"), and confirm the model can respond normally.

image-20260429145018638

5. Other Access Methods (Advanced)

  • If you have your own model provider or need to access other model providers later, refer to the following tutorials

5.1 CLI Command Configuration API-KEY (Suitable for Beginners)

  1. Start configuration wizard

    xxxxxxxxxx
    openclaw onboard
  • Select 【Yes】 and press Enter

image-20260427171151912

  • Select QuickStart for configuration mode, press Enter

image-20260427171417315

  1. Select model service provider

    • Use up and down arrows to select the service provider you have applied for API-KEY, press Enter to confirm. Here we take the Alibaba Cloud Bailian model provider as an example. The configuration method for other model providers is the same.
    • Here select custom provider 【Custom Provider】

    image-20260427171711888

    • Fill in the base_url of the model provider

image-20260427172302299

  1. Input API-KEY
  • After selecting the service provider, the system will prompt you to enter the corresponding API-KEY

image-20260427172456361

  • Paste or enter your applied API-KEY and press Enter to confirm

image-20260427172816515

  • Select OpenAI-compatible for the interface protocol

image-20260427172908400

  1. Fill in the model name, here we take MiniMax as an example

image-20260427173143879

  • Endpoint ID is the model provider identifier, you can fill in freely

image-20260427173335228

  • Model alias (optional) can be left blank

image-20260427173502891

  1. Other configurations
  • For other configuration items, select skip as shown in the figure below, no configuration needed

image-20260427173738590

image-20260427173805504

image-20260427173838434

  • Press space to select Skip for now for Enable Hooks

image-20260427173915965

  • Select Restart to restart the gateway to take effect

image-20260427174010877

5.2 Modify Configuration File (Recommended Method)

Configuration File Location

The configuration file is located at: $HOME/.openclaw/openclaw.json

Edit Configuration File

  1. Open the configuration file

    xxxxxxxxxx
    nano $HOME/.openclaw/openclaw.json
    # Or use your favorite editor, such as vim, code, etc.
  2. Add model provider configuration

    Add or modify the models.providers section in the configuration file:

    xxxxxxxxxx
    {
      "models": {
        "providers": {
          "openai": {
            "apiKey": "OPENAI_API_KEY"
          },
          "anthropic": {
            "apiKey": "ANTHROPIC_API_KEY"
          },
          "google": {
            "apiKey": "GOOGLE_API_KEY"
          }
        }
      },
      "agents": {
        "defaults": {
          "model": {
            "primary": "openai/gpt-4"
          }
        }
      }
    }
  3. Configuration Description

    • models.providers: Configure API-KEY for each model service provider

      • openai.apiKey: OpenAI's API-KEY
      • anthropic.apiKey: Anthropic's API-KEY
      • google.apiKey: Google's API-KEY
    • agents.defaults.model.primary: Set the default model to use

      • Format is service provider/model name, such as openai/gpt-4, anthropic/claude-3, google/gemini-pro
  4. Save and Exit

  • Press Ctrl+O to save, Ctrl+X to exit (nano editor)
  1. Factory Default Bailian Configuration (can be directly modified or referenced)
xxxxxxxxxx
"models": {
    "mode": "merge",
    "providers": {
    "bailian": {
      "baseUrl": "https://dashscope.aliyuncs.com/compatible-mode/v1",
      "apiKey": "sk-a98b519b6bab4e35a7b82b4a95b8a4f6",
      "api": "openai-completions",
      "models": [
        {
          "id": "qwen3.5-plus",
          "name": "qwen3.5-plus",
          "reasoning": false,
          "input": [
            "text",
            "image"
          ],
          "contextWindow": 1000000,
          "maxTokens": 65536,
          "cost": {
            "input": 0,
            "output": 0,
            "cacheRead": 0,
            "cacheWrite": 0
          }
        },
        {
          "id": "MiniMax-M2.5",
          "name": "MiniMax-M2.5",
          "reasoning": false,
          "input": [
            "text"
          ],
          "cost": {
            "input": 0,
            "output": 0,
            "cacheRead": 0,
            "cacheWrite": 0
          },
          "contextWindow": 196608,
          "maxTokens": 32768
        },
        {
          "id": "glm-4.7",
          "name": "glm-4.7",
          "reasoning": false,
          "input": [
            "text"
          ],
          "cost": {
            "input": 0,
            "output": 0,
            "cacheRead": 0,
            "cacheWrite": 0
          },
          "contextWindow": 202752,
          "maxTokens": 16384,
          "compat": {
            "thinkingFormat": "qwen"
          }
          }
        ]
      }

6. Common Problems and Solutions

6.1 API-KEY Invalid or Error

Problem: After configuration, it shows API-KEY invalid or authentication failed

Solution:

  1. Confirm whether the API-KEY is correct (note no extra spaces)
  2. Check if the API-KEY has expired or been disabled
  3. Confirm whether the account balance is sufficient (some service providers require pre-charging)

6.2 Cannot Access Model Service

Problem: Configuration is correct but cannot connect to model service

Solution:

  1. Check if the network connection is normal
  2. Confirm whether the network in your region can access the service provider (some services may require special network configuration)
  3. Try changing to another model service provider for testing

7. Course Summary

Through this course, you have mastered:

✅ Types of model service providers supported by OpenClaw ✅ API-KEY application method and precautions ✅ CLI command configuration method (suitable for beginners) ✅ Configuration file modification method (suitable for developers) ✅ How to view and verify model configuration status ✅ Troubleshooting and solutions for common problems

Peripheral Hardware Configuration
OpenClaw Model Switching

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