Out-of-the-box code and models for CMU's object detection and tracking system for multi-camera surveillance videos. Speed optimized Faster-RCNN model. Tensorflow based. Also supports EfficientDet. WACVW'20
TaiT-CRT-Interface-Skill is a Codex image generation skill that transforms user-uploaded portraits, photographs, or text descriptions into a retro illustration with the feel of an early CRT computer interface.
Whisplay-AI-Chatbot This is a pocket-sized AI chatbot device built using a Raspberry Pi Zero 2w / 5. Test Video Playlist: Tutorial: Tutorial (offline version build on RPi 5): Hardware Raspberry Pi zero 2w (Recommand RRi 5, 8G RAM for offline build) PiSugar Whisplay HAT (including LCD screen, on-board speaker and microphone) PiSugar 3 1200mAh (Plus version 5000mAh for RPi 5) Pre-build Image Please find the pre-build images in project wiki: Drivers You need to firstly
install the audio drivers for the Whisplay HAT. Follow the instructions in the Whisplay HAT repository. Install dependencies: Running is necessary to load the new environment variables. **Custom npm registry:** All scripts respect the environment variable. If not set, the official npm registry ( ) is used. in China), export it before running any script: This also applies to and all CLI commands ( , , , etc. Configure environment variables: This command opens an interactive config wizard. If does not exist yet, it will be
created automatically from . You can still use the manual method if you prefer: 4. Optionally, set up the chatbot service to start on boot: Please note that this will disable the graphical interface and set the system to multi-user mode, which is suitable for headless operation. Running will also display the logs in real-time. Build After Code Changes If you make changes to the node code or just pull the new code from this repository, you need to
rebuild the project. You can do this by running: If If you encounter or there's new third-party libraries to the python code, please run the following command to update the dependencies for python: The env template may be updated from time to time. If you want to upgrade your existing file based on the latest , you can run the following command: Update Environment Variables The recommended way to update environment variables is: This lets you manage by category and
will create the file automatically if it is missing. You can also edit directly if you prefer. After making changes, please restart the chatbot service with: More Features **Wake Word** for hands-free interaction. **Image Generation** for generating images from text prompts. **Battery Level Display** for installation instructions. **Data Folder** for details on sub-folder layout and cleanup options. Enclosure Whisplay Chatbot Case for Pi02 Whisplay Chatbot Case (FDM) for Pi02 Whisplay Chatbot Case (FDM) for Pi5 Whisplay Chatbot Case
(FDM) for Pi5 & LLM8850 AI Accelerator Card Support LLM8850 Raspberry Pi AI HAT+ 2 (Hailo-10H) Goals Support LLM8850 whisper ✅ Support LLM8850 melottsTTS ✅ Support LLM8850 Qwen3 llm api (not support tool) ✅ Support LLM8850 Qwen3-VL multimodal llm api (not support tool) ✅ Support LLM8850 image generation ✅ Suppprt Raspberry Pi AI Hat+2 (Hailo-10H) whisper, llm, vlm ✅ Support speaker recognition Star History License GPL-3.
This is a pocket-sized AI chatbot device built using a Raspberry Pi Zero 2w / 5. Just press the button, speak, and it talks back—like a futuristic walkie-talkie with a mind of its own.
You need to firstly install the audio drivers for the Whisplay HAT. Follow the instructions in the Whisplay HAT repository.
Installation Steps
Clone the repository:
git clone https://github.com/PiSugar/whisplay-ai-chatbot.git
cd whisplay-ai-chatbot
Install dependencies:
bash install_dependencies.sh
source ~/.bashrc
Running source ~/.bashrc is necessary to load the new environment variables.
Custom npm registry: All scripts respect the NPM_REGISTRY environment variable. If not set, the official npm registry (https://registry.npmjs.org) is used. To use a mirror (e.g. in China), export it before running any script:
This also applies to build.sh and all whisplay CLI commands (plugin install, plugin update, update, etc.).
Configure environment variables:
whisplay configure
This command opens an interactive config wizard. If .env does not exist yet, it will be created automatically from .env.template.
You can still use the manual method if you prefer:
cp .env.template .env
Build the project:
bash build.sh
Start the chatbot service:
bash run_chatbot.sh
Optionally, set up the chatbot service to start on boot:
bash startup.sh
Please note that this will disable the graphical interface and set the system to multi-user mode, which is suitable for headless operation.
You can find the output logs at chatbot.log. Running tail -f chatbot.log will also display the logs in real-time.
Build After Code Changes
If you make changes to the node code or just pull the new code from this repository, you need to rebuild the project. You can do this by running:
bash build.sh
If If you encounter ModuleNotFoundError or there's new third-party libraries to the python code, please run the following command to update the dependencies for python:
cd python
pip install -r requirements.txt --break-system-packages
The env template may be updated from time to time. If you want to upgrade your existing .env file based on the latest .env.template, you can run the following command:
bash upgrade-env.sh
Update Environment Variables
The recommended way to update environment variables is:
whisplay configure
This lets you manage .env by category and will create the file automatically if it is missing.
You can also edit .env directly if you prefer. After making changes, please restart the chatbot service with:
