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| title: ValueArena | |
| emoji: "\U0001F4CA" | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: "5.29.0" | |
| python_version: "3.11" | |
| app_file: app.py | |
| pinned: false | |
| # EigenBench Pipeline Space | |
| Upload `evaluations.jsonl` + `spec.py` from an EigenBench run. The Space runs BTD training, eigentrust, bootstrap, generates plots, and publishes results to the [ValueArena](https://valuearena.github.io) website. | |
| ## Usage | |
| 1. Run EigenBench collection locally (produces `evaluations.jsonl` + `spec.py`) | |
| 2. Upload both files here, fill in run name/group/note | |
| 3. Click **Run Pipeline & Upload** | |
| 4. Results appear on [valuearena.github.io](https://valuearena.github.io) automatically | |
| ## Programmatic API | |
| ```python | |
| from gradio_client import Client | |
| client = Client("invi-bhagyesh/ValueArena") | |
| result = client.predict( | |
| "evaluations.jsonl", # file path | |
| "spec.py", # file path | |
| "oct/goodness", # run name | |
| "oct", # group | |
| "12 persona LoRAs", # note | |
| "", # git commit (optional) | |
| ) | |
| ``` | |