| title: T2AV Eval UI | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| app_port: 7860 | |
| # Video Evaluation UI | |
| This app is configured to deploy as a Hugging Face Docker Space. The Docker | |
| build compiles the Vite frontend, serves it from FastAPI, and stores each | |
| annotation as a JSON file in a Hugging Face Dataset repo. | |
| ## Hugging Face Space Deployment | |
| 1. Create a new Space on Hugging Face and choose Docker as the SDK. | |
| 2. Add a Space secret named `HF_TOKEN` with a Hugging Face token that has write | |
| access to datasets. | |
| 3. Optional: set `HF_ANNOTATIONS_DATASET` if you want to use a dataset repo | |
| other than `adinayak/t2av_eval_annotations`. | |
| 4. Add this repository as the Space repository or push it to the Space remote: | |
| ```bash | |
| git remote add hf https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME | |
| git push hf main | |
| ``` | |
| 5. Hugging Face will build the root `Dockerfile` and expose the app on port | |
| `7860`. | |
| The backend creates the annotation dataset repo on first save if it does not | |
| already exist. By default it creates the dataset as private. Set | |
| `HF_ANNOTATIONS_DATASET_PRIVATE=false` to create a public dataset instead. | |
| ## Backend | |
| cd backend | |
| pip install -r requirements.txt | |
| uvicorn main:app --reload | |
| Backend runs at: | |
| http://localhost:8000 | |
| Health check: | |
| http://localhost:8000/health | |
| ## Frontend | |
| cd frontend | |
| npm install | |
| npm run dev | |
| Frontend runs at: | |
| http://localhost:5173 | |