Charlene393/web-tutoria

Web Tutoria is an AI learning system for Kenyan Sign Language (KSL). # Web Tutoria Web Tutoria is an AI learning system for Kenyan Sign Language (KSL). The project is being built around three core flows: - speech -> text -> KSL lesson or sign playback - text -> speech + KSL lesson playback - signer video or webcam -> text -> speech - photo upload -> explanation -> matching KSL lesson ## Project structure ```text backend/ api/ FastAPI backend scripts/ dataset cleanup and analysis scripts frontend/ web/ frontend app shell KSL-Dataset/ Pose Data/ local pose and landmark dataset ``` ## Prerequisites Install these before setup: - Python `3.11` or `3.12` - Git Frontend tooling can be added later when the web app is bootstrapped. ## Clone and setup If you only want the backend running, use this full copy-paste flow: ```bash git clone cd web-tutoria cd backend/api bash setup-venv.sh cp .env.example .env bash start-dev.sh ``` Use that flow exactly if you are setting the project up for the first time. After the backend starts, use backend/api/DEMO_CHECKLIST.md to verify every stable endpoint in the right order. When you need concrete frontend-facing payload examples, use backend/api/DEMO_RESPONSES.md. ### 1. Clone the repository ```bash git clone cd web-tutoria ``` ### 2. Create and activate the backend virtual environment ```bash cd backend/api bash setup-venv.sh ``` ### 3. Install backend dependencies This is handled by `setup-venv.sh`. ### 4. Create backend environment variables ```bash cp .env.example .env ``` ### 5. Start the FastAPI backend Run this from `backend/api`: ```bash bash start-dev.sh ``` This is the recommended startup command because it: - uses `backend/api/.venv` - runs from the correct backend folder - reloads only when files in `app/` change - avoids watching `.venv` Then open: - `127.0.0.1` - `127.0.0.1` Before testing the backend flows, you can quickly check readiness with: ```bash curl 0.0.0.1 …