Spaces:
Running on Zero
Running on Zero
| title: Joe | |
| emoji: 🤖 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 6.17.3 | |
| python_version: "3.12" | |
| app_file: app.py | |
| pinned: true | |
| license: mit | |
| short_description: A dramatic AI personality living on a 20x4 LCD screen | |
| tags: | |
| - gradio | |
| - build-small-hackathon | |
| - track:wood | |
| - achievement:offgrid | |
| - badge-tiny-titan | |
| - arduino | |
| - lcd | |
| - local-llm | |
| - minicpm | |
| - cohere | |
| - whisper | |
| - off-brand | |
| - best-agent | |
| - best-demo | |
| - tiny-titan | |
| - sponsor:openbmb | |
| # Joe | |
| A self-aware AI personality living on a 20x4 LCD screen. Joe monitors your computer's CPU, RAM, WiFi, clipboard, active apps, ambient audio, and weather — then reasons about how it feels using a local LLM (MiniCPM5-1B via Ollama) and displays context-aware messages on a physical LCD. | |
| ## Features | |
| - **Real-time monitoring**: CPU, RAM, WiFi signal, clipboard, active apps, ambient audio | |
| - **Context Compiler**: pattern detection, state tracking, event detection | |
| - **Local LLM**: MiniCPM5-1B via Ollama (primary) or HF Inference API (fallback) | |
| - **ASCII Art Dreams**: 100+ LCD-optimized patterns with IDs 0-99 | |
| - **Grid System**: movable `@` character on 20x4 grid with mood faces | |
| - **Gradio Dashboard**: real-time monitoring, API logs, history | |
| ## Hardware (optional) | |
| - Arduino Uno + 20x4 I2C LCD (2004A) | |
| - Works without hardware in demo mode | |
| ## Setup (local) | |
| ```bash | |
| pip install -r requirements.txt | |
| # Install Ollama and pull MiniCPM5-1B | |
| ollama pull openbmb/minicpm5:latest | |
| python app.py | |
| ``` | |
| ## HF Spaces (live demo) | |
| This Space runs **MiniCPM5-1B** directly via HuggingFace transformers — same model as local. | |
| - **First load**: ~30-60s (downloads ~1GB model weights) | |
| - **Inference**: ~2-5s per response on CPU | |
| - **No Ollama needed**: model loads into memory on startup | |
| - **Fallback**: if transformers fails, falls back to HF Inference API (zephyr-7b) | |
| ## HF Build Small Hackathon | |
| This project was built for the [HF Build Small Hackathon](https://huggingface.co/build/small). All models used are ≤32B parameters. | |
| - **Track**: Thousand Token Wood (whimsical / entertainment) — `track:wood` | |
| - **Achievements claimed**: Off-Grid (`achievement:offgrid`, runs a fully local LLM, no cloud API) · Tiny Titan (`badge-tiny-titan`, 1.08B model) | |
| - **Primary LLM**: MiniCPM5-1B (1.08B params, Apache-2.0) | |
| - **Fallback LLM**: zephyr-7b-beta (7B params, MIT) | |
| - **Speech-to-text**: Cohere Transcribe 03 (~2B params, runs in a persistent daemon) with Whisper-tiny fallback | |
| All models run individually well under the 32B cap. | |
| ### Submission links | |
| - **Demo video**: https://youtu.be/eBcLilTYz9Y | |
| - **Social post**: https://x.com/ssaacar/status/2066630310410829835 | |