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Deploy hyper3labs/HyperView-ABO-Catalog from Hyper3Labs/hyperview-spaces@67594d4
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---
title: HyperView ABO Catalog
emoji: 🛒
colorFrom: gray
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
---
# HyperView - ABO Catalog Model Comparison
This demo builds a small Amazon Berkeley Objects product-catalog subset and opens
HyperView with two pinned scatter panels plus a comparison readout:
- CLIP ViT-B/32 in a Euclidean 2D layout
- Hyper3-CLIP `hyper3-clip-v0.5` from `hyper-models` in a Poincare 2D layout
The right-side panel uses fixed product examples to compare nearest-neighbor
behavior for the same query under each model.
The demo loads the full ABO metadata mirror from
`hyper3labs/amazon-berkeley-objects`, then deterministically selects a balanced
subset for the live comparison and always includes the fixed walkthrough query
samples. Local `demo_data` is only a runtime cache for downloaded images,
HyperView dataset state, embeddings, and layouts.
Run locally from the HyperView repo:
```bash
uv run python hyperview-spaces/spaces/abo-catalog-clip-hycoclip/demo.py
```
Useful overrides:
```bash
HYPERVIEW_PORT=6263 ABO_MAX_PRODUCT_TYPES=12 ABO_SAMPLES_PER_PRODUCT_TYPE=20 \
uv run python hyperview-spaces/spaces/abo-catalog-clip-hycoclip/demo.py
```
## Swap the comparison model
The model choices live in the `MODEL_SPECS` block near the top of
[demo.py](demo.py). To swap the candidate model, update these environment
variables or edit the second entry in `MODEL_SPECS`:
```bash
ABO_CANDIDATE_DISPLAY_NAME="New Model" \
ABO_CANDIDATE_PROVIDER="hyper-models" \
ABO_CANDIDATE_MODEL="new-model-id" \
ABO_CANDIDATE_LAYOUT="poincare:2d" \
ABO_CANDIDATE_GEOMETRY="poincare" \
python demo.py
```
The panel reads model labels, layout keys, and fixed examples from props passed
by `demo.py`, so model swaps should not require editing the extension
JavaScript.
## Deploy source
This folder is intended to deploy to `hyper3labs/HyperView-ABO-Catalog` from
the `hyperview-spaces` deployment repository.
The Dockerfile installs `hyperview==0.6.2` and `hyper-models[ml]==0.3.0` from
PyPI. The released HyperView wheel includes the built frontend assets, so this
Space does not carry a local `static/` bundle or copy frontend files into the
installed package.
Hyper3-CLIP weights are loaded through the `hyper-models` catalog entry for the
gated `hyper3labs/hyper3-clip-v0.5` model repository at runtime. The Space needs
an `HF_TOKEN` secret with access to that model.