| --- |
| title: FrogQuest |
| emoji: 🐸 |
| colorFrom: green |
| colorTo: yellow |
| sdk: gradio |
| sdk_version: 6.17.3 |
| python_version: '3.12' |
| app_file: app.py |
| pinned: true |
| license: apache-2.0 |
| short_description: A text-image based RPG built to help fight procrastination |
| --- |
| |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
|
|
| ## FrogQuest |
|
|
| Turn your real to-do list into an 8-bit pixel-art text-adventure quest log where **you** are the |
| hero. Named for the "Eat That Frog" method: your hardest/most important task is the **frog** — the |
| boss quest you face first. |
|
|
| - **Nemotron Nano 4B** (text only, via llama.cpp on ZeroGPU) writes the quest JSON — Eat That Frog |
| prioritization, linked sub-task chains, and optional self-care bonus quests. |
| - A fixed pixel-art frontend (`gr.Server` custom UI) renders that JSON as the quest log. |
| - **FLUX.2 [klein] 4B** (diffusers) generates each quest's image using your uploaded photo as a |
| reference, then edits that same image into success / "retreat to fight another day" states. |
|
|
| Your photo and quest state live **only in your browser** (localStorage); the photo is sent to the |
| GPU transiently for generation and is never stored server-side. |
|
|
| ### GPU backend (ZeroGPU or Modal) |
|
|
| The GPU work (quest JSON + images) runs through a pluggable backend chosen by the |
| `FROGQUEST_BACKEND` env var. The frontend, signatures, and behavior are identical either way. |
|
|
| **`zerogpu` (default).** Everything runs in-Space on ZeroGPU. |
| - Set the Space hardware to **ZeroGPU**. |
| - First quest generation cold-downloads the models, then runs fast. |
| - Subject to ZeroGPU daily quotas (anon 2 min, free 5 min, PRO 40 min per day). |
|
|
| **`modal` (opt-in).** The Space runs on CPU-basic and offloads GPU work to [Modal](https://modal.com) |
| (dedicated GPU, pay-per-second, no quota). Switching is **two steps** — the env var alone does NOT |
| change hardware: |
| 1. Set the Space hardware to **CPU basic**. |
| 2. Add a Space **variable** `FROGQUEST_BACKEND=modal`. |
|
|
| One-time Modal setup: |
| 1. `pip install modal` and `modal token new` (authenticate). |
| 2. `modal deploy modal_app.py` (deploys the `frogquest` app: an `LLM` class + a `Flux` class). |
| 3. Add `MODAL_TOKEN_ID` and `MODAL_TOKEN_SECRET` as Space **secrets** so the Space can call Modal. |
| 4. Optional: set `FROGQUEST_MODAL_FLUX_GPU` before `modal deploy` to pick the image GPU |
| (default `A10G`; `L4` cheaper; `L40S`/`A100-40GB` if it OOMs). |
|
|
| Optional: rename `requirements-modal.txt` → `requirements.txt` on the Space to skip installing the |
| heavy GPU libs (torch/diffusers/llama-cpp) and speed up CPU-basic builds. |
|
|
|
|
