System Requirements#
Hardware#
CPU: x86_64. Intel Core Ultra (Meteor Lake) or newer is recommended. Older Intel Core / Xeon processors will run the stack but may be slower on OpenVINO inference paths.
Memory: 32 GB RAM minimum. 64 GB recommended when running the LLM, reranker, ASR, and TTS together with a warm cache.
Disk: 60 GB free SSD space recommended for model assets, the Hugging Face cache, vector storage, generated audio, and per-session storage. NVMe is preferred for faster first-run model export.
GPU (optional): Intel integrated GPU (Meteor Lake or newer iGPU) or a supported discrete GPU exposed via
/dev/dri. The RAG LLM and reranker benefit most fromGPU;audio-analyzerandtext-to-speechcan also be pinned toGPUfor higher throughput.Microphone: Not required on the host — audio is captured by the browser via the Web Audio API and uploaded to
kiosk-core.
Operating System#
Ubuntu 22.04 LTS (validated) or a compatible Linux distribution with a recent kernel.
Docker Engine and Docker Compose v2 for container deployment.
For GPU acceleration on Linux: Intel/OpenVINO host GPU runtime (e.g.
intel-opencl-icd,level-zero) installed on the host.
Host Packages (Standalone Run Only)#
When running kiosk-core and the Gradio UI directly on the host:
sudo apt-get update
sudo apt-get install -y ffmpeg alsa-utils libsndfile1
audio-analyzer, text-to-speech, and rag-service are still recommended
to run in containers even in this mode.
Python (Standalone Run Only)#
Python 3.10 or newer.
Dependencies installed from
requirements.txt.
Network#
Outbound internet access on first run to download model assets from Hugging Face, unless models are pre-staged under the per-service
models/and.cache/directories.Inbound access on the host for the published TCP ports:
7860,8010,8011,8012,8020.
Browser#
Any modern Chromium-based browser or Firefox with permission to use the microphone for
http://127.0.0.1:7860.The browser must be able to reach
kiosk-core(http://127.0.0.1:8012) from the same machine, or a routable address ifkiosk-uiis exposed beyond localhost.