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RDK S100(P) Board📖
0. RDK S100(P) Developer Kit
  • 1. RDK S100(P) Official Tutorial
1. Introduction to RDK S100(P) Development Board
  • 1.1 Introduction to the RDK S100(P) Development Board
  • 1.2 Install Operating System
  • 1.3 Interface Descriptions
  • 1.4 Accessory installation
  • 1.5 Camera Expansion Board
  • 1.6 MCU Port Expansion Board
  • 1.7 Precautions for using 15.6-inch screens
2. Basic Settings Course
  • 2.1 Network Configuration
  • 2.2 Remote Login
  • 2.3 System Update
  • 2.4 Boot Auto-Start Configuration
  • 2.5 RDK Exclusive Command Usage
  • 2.6 Linux Command Usage
  • 2.7 Example of GPIO read and write operations
  • 2.8 Using USB Camera
  • 2.9 Using MIPI Camera
  • 2.10 SSD mounting
  • 2.11 Binocular camera depth algorithm
3. TogetheROS.Bot Vision Applications
  • 1. About TogetheROS. Bot
  • 2. System Installation
  • 3. Object Detection(YOLO)
  • 4. Image Classification(mobilenetv2)
  • 5. Image Segmentation(mobilenet_unet)
  • 6. Perception Algorithm(BEV)
  • 7. Human Detection and Tracking (Ultralytics YOLO Pose)
4.Offline AI model course
Offline large model (Text Interaction)
  • 1. AI large model environment deployment
  • 2. Install large model dialogue platform
  • 3. Meta AI Llama 3.2 model
  • 4. Alibaba Cloud Qwen3 model
  • 5. Microsoft Phi-4 mini model
  • 6. DeepSeek - DeepSeek-R1 model
  • 7. Alibaba Cloud Qwen2.5vl 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 to image application
  • 13. Multimodal visual localization application
  • 14. Multimodal table scanning application
  • 15. Multimodal Autonomous Agent Applications
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 voice interaction
  • 5. Multimodal Text-to-Image application
  • 6. Multimodal video analytics application
  • 7. Multimodal visual localization application
  • 8. Multimodal table scanning application
  • 9. Multimodal autonomous agent application
  • 10. AI Large Model Offline Voice Assistant
5.Online AI model course
Online large model (Text Interaction)
  • 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 agent 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.Multimodal visual localization application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model online voice assistant
6.YOLO26 tutorials
  • 01.YOLO26 environment
  • 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
7.OpenClaw Advanced Development
  • 1.OpenClaw Deployment
  • 2.OpenClaw WhatsApp Plugin Application
  • 3.OpenClaw WebChat Interaction
  • 4.OpenClaw TUI Interaction
  • 5.OpenClaw Tools Introduction
  • 6.OpenClawGate Gateway User Manual
  • 7.OpenClaw Features Overview
  • 8.OpenClawClawHub Introduction (Skill Installation)
  • 9.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
  • 15.OpenClaw Web Search Capability Configuration
8.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
Download
  • Annex_File
  • Code
Download ZIP

Welcome to RDK S100(P) Board repository

1.OpenRouter large model API aggregation platform

4. OpenRouter Large Model API Aggregation Platform Text Interaction Tutorial

4. OpenRouter Large Model API Aggregation Platform Text Interaction TutorialConcept Introduction1.1 What is "OpenRouter"?2. Practical Operations2.1 Obtain API Credentials2.2 Graphical Process2.3 Configuration File Modification

Concept Introduction

1.1 What is "OpenRouter"?

OpenRouter is a large model API aggregation platform. You can think of it as a "universal remote control for large models". Normally, if you want to use OpenAI's GPT-4, Anthropic's Claude-3, and Google's Gemini, you need to register accounts on three platforms separately, obtain three sets of API Keys, and write three different sets of calling code for their respective API formats.

However, OpenRouter solves this problem. It provides a unified API interface (compatible with OpenAI's API format), where you only need one OpenRouter API Key to call all the above models and hundreds of other open-source and closed-source models through this single entry point.

The core advantages of integrating OpenRouter in the largemodel project are:

  • Ultimate Flexibility: You can seamlessly switch between GPT, Claude, Llama, and any other models by simply modifying a model name in the configuration file, without changing any code.
  • Cost-effectiveness: OpenRouter provides clear pricing for each model, allowing you to easily compare and select the most cost-effective model to perform specific tasks.
  • Explore Cutting-edge Models: Many new and excellent open-source models are included on OpenRouter as soon as they are released, allowing developers to quickly try them out.

In the largemodel project, you can enable this powerful aggregation platform by configuring the llm_platform parameter to openrouter.

2. Practical Operations

2.1 Obtain API Credentials

  1. Register for OpenRouter: Visit OpenRouter.ai and register an account using Google or email. If the link is not working, you need to search for "OpenRouter" platform yourself.
  2. Top Up: OpenRouter uses a prepayment model. You need to top up a small amount (e.g., $5) on the "Credits" page before you can start using it. Alternatively, you can use the free models they provide, but there are rate limits.
  3. Create API Key: On the "Keys" page, click "Create Key" to generate a new API Key and immediately copy and save it.

2.2 Graphical Process

  1. First, visit the following website. If the link is not working, you need to search for "OpenRouter" platform yourself, then look for large model keywords.

OpenRouter

image-20250801163705985

  1. Register and log in to your account
  2. After registering your account, click to enter the model marketplace

image-20250801165400079

  1. You can type "free" in the search bar to find models that can be called for free.

image-20250807175353717

  1. Hover your mouse over the clipboard icon next to the model to see the name used when calling the model, click once to copy it.

image-20250807175436229

 

  1. Move your mouse to the top right corner next to the avatar, it will expand, you can click Keys to go in and create a key.

image-20250807180439598

  1. Click to apply for API key

image-20250807180556227

  1. After applying, you will get a string of API key

image-20250801171806192

2.3 Configuration File Modification

  1. Open large_model_interface.yaml:

    # Open configuration file
    vim ~/yahboom_ws/src/largemodel/config/large_model_interface.yaml

    Then change sk-xxxxxxxxxx in openrouter_api_key to the API key you just copied.

    openrouter_model is used to configure the large model for conversation.

    xxxxxxxxxx
    # OpenRouter platform configuration
    openrouter_api_key: "sk-xxxxxxxxxxxxxxxxxxx"
    openrouter_model: "moonshotai/kimi-k2:free" # Model to use, for example "google/gemini-pro-vision"
  2. Open yahboom.yaml:

    xxxxxxxxxx
    # Open yahboom configuration file
    vim ~/yahboom_ws/src/largemodel/config/yahboom.yaml
  3. Switch Platform: Modify the llm_platform parameter to openrouter.

    xxxxxxxxxx
    # Set large model platform to openrouter
    llm_platform: 'openrouter'

After switching the platform parameters, return to the workspace and recompile to take effect.

AI Large Model Offline Voice Assistant
Multimodal visual understand application

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