AI-powered offline classroom assistant for under-resourced schools. Real-time speech-to-text, textbook parsing, quiz generation, and analytics—all on-device, no internet required. Empowers teachers with personalized insights and students with interactive learning via local WiFi access point.
Python
1
14 commits
updated Jun 26, 2025
SnapClass is an advanced on-device edge AI solution designed for low-connectivity, high-density classroom environments. Powered by Snapdragon’s Hexagon NPU, it runs open-source large language models (LLMs), image captioning, and audio transcription entirely offline. SnapClass automates personalized learning by transcribing lectures, analyzing textbook content, and generating adaptive quizzes—bridging educational gaps in underserved regions where internet access and qualified educators are limited.
We use MyPublicWifi to create a local area dead network
git clone https://github.com/Abbilaash/SnapClass.git
cd SnapClass
pip install -r requirements.txt
Install AnythingLLM and activate AnythingLLM NPU to process LLM models in Qualcomm Hexagon NPU.
Download Phi 3.5 Mini Instruct 4K 2.00GB model.
Get you AnythingLLM Developer API from Settings>Tools>Developer API>Generate New API Key and get you workspace slug.
Replace you API key in server/config.yaml as api_key: <API> and workspace_slug: <my-workspace>
cd server
python app.py
Once started, the server runs locally on port 5000
http://127.0.0.1:5000/admin
Use the IP address shown in MyPublicWifi ad access the students portalhttp://<IP>:5000/test
Replace with the one shown in the MyPublicWifi app after enabling the hotspot
A T Abbilaash - [email protected]
Nivashini N - [email protected]
AI-powered offline classroom assistant for under-resourced schools. Real-time speech-to-text, textbook parsing, quiz generation, and analytics—all on-device, no internet required. Empowers teachers with personalized insights and students with interactive learning via local WiFi access point.
Python
1
14 commits
updated Jun 26, 2025
SnapClass is an advanced on-device edge AI solution designed for low-connectivity, high-density classroom environments. Powered by Snapdragon’s Hexagon NPU, it runs open-source large language models (LLMs), image captioning, and audio transcription entirely offline. SnapClass automates personalized learning by transcribing lectures, analyzing textbook content, and generating adaptive quizzes—bridging educational gaps in underserved regions where internet access and qualified educators are limited.
We use MyPublicWifi to create a local area dead network
git clone https://github.com/Abbilaash/SnapClass.git
cd SnapClass
pip install -r requirements.txt
Install AnythingLLM and activate AnythingLLM NPU to process LLM models in Qualcomm Hexagon NPU.
Download Phi 3.5 Mini Instruct 4K 2.00GB model.
Get you AnythingLLM Developer API from Settings>Tools>Developer API>Generate New API Key and get you workspace slug.
Replace you API key in server/config.yaml as api_key: <API> and workspace_slug: <my-workspace>
cd server
python app.py
Once started, the server runs locally on port 5000
http://127.0.0.1:5000/admin
Use the IP address shown in MyPublicWifi ad access the students portalhttp://<IP>:5000/test
Replace with the one shown in the MyPublicWifi app after enabling the hotspot
A T Abbilaash - [email protected]
Nivashini N - [email protected]