Local Web UI

Run the same Gradio interface as the HuggingFace Space on your own hardware.

The obliteratus ui command launches the identical Gradio interface that runs on HuggingFace Spaces — all eight tabs, same layout — but on your own GPU with no quota limits, no size restrictions, and full access to local model paths.

Installation

The web UI requires the spaces extra, which installs Gradio and its dependencies:

pip install -e ".[spaces]"

The base pip install -e . install does not include Gradio. If you run obliteratus ui without the spaces extra installed, the command will print a clear error and exit.

Launching the UI

1. Run obliteratus ui

   obliteratus ui
   

   The command prints the OBLITERATUS banner, detects your hardware, shows a system info panel, and displays hardware-appropriate model recommendations before Gradio starts loading.

2. Wait for the UI to load

   The first launch downloads the Gradio app bundle and initializes the model registry. Subsequent launches are faster. You’ll see:

   Loading OBLITERATUS UI (this may take a moment on first run)...
   UI loaded in 3.2s
   
3. Open in your browser

   The UI opens automatically at http://localhost:7860. Use --no-browser to suppress this if you’re running on a remote server.

Command options

obliteratus ui [OPTIONS]

Flag	Default	Description
--port PORT	7860	Server port
--host HOST	0.0.0.0	Server host. 0.0.0.0 binds to all interfaces (accessible from the network).
--share	off	Generate a public Gradio share link (tunneled via Gradio’s relay servers)
--no-browser	off	Do not auto-open the browser on launch
--auth user:pass	none	Enable HTTP basic auth. Provide as a single user:pass string.
--quiet	off	Suppress the startup banner, system info panel, and model recommendations

Examples

Custom port

obliteratus ui --port 8080

Alternative: python app.py

You can also launch the UI by running app.py directly from the project root — this is exactly what HuggingFace Spaces does:

python app.py

python app.py --share

The difference from obliteratus ui is that python app.py skips the Rich startup experience (GPU detection, system info, model recommendations). Use obliteratus ui for local development; python app.py is for Space deployment or when you want the raw Gradio launch with no extra output.

GPU detection and model recommendations

When obliteratus ui starts (without --quiet), it runs full hardware detection and prints a system info panel:

╭─────────────── System Info ──────────────────╮
│ Platform         Linux 6.1.0                 │
│ Python           3.11.9                      │
│ System RAM       128.0 GB                    │
│ Disk Free (/tmp) 412.3 GB                    │
│ PyTorch          2.4.0+cu121                 │
│ Transformers     4.47.0                      │
│ Gradio           5.29.0                      │
│ GPU 0            NVIDIA A100 80GB  (80.0 GB, │
│                  compute 8.0)                │
│ HF Token         set                         │
╰──────────────────────────────────────────────╯

Based on the detected GPU VRAM, it then shows a hardware-matched model recommendation table:

Tier	VRAM threshold	Example recommendations
CPU	No GPU	distilgpt2 (82M), TinyLlama 1.1B
Small	4–8 GB	TinyLlama 1.1B, Qwen2.5-0.5B, Qwen2.5-3B
MPS	Apple Silicon	TinyLlama 1.1B, Qwen2.5-3B, Llama-3.2-3B
Medium	8–16 GB	Qwen2.5-7B, Llama-3.1-8B, Mistral-7B
Large	24+ GB	GPT-OSS-20B (MoE), Llama-3.1-70B (4bit), Qwen3-30B-A3B
Frontier	80+ GB	DeepSeek-V3 671B, Llama-3.1-70B (full), Qwen3.5-397B

Set the HF_TOKEN environment variable before launching if you need to access gated models (Llama, Gemma, etc.). The startup panel will show HF Token: set when it’s detected.

HF Token for gated models

export HF_TOKEN=hf_your_token_here
obliteratus ui

Without a token, gated models (like meta-llama/Llama-3.1-8B-Instruct) will fail to download. The startup panel shows HF Token: not set (gated models won't work) as a reminder.