# System Requirements Hardware, software, and network requirements for deploying Take-Away Order Accuracy. --- ## Hardware Requirements ### Development / Single Station | Component | Specification | | ----------- | -------------------------------------------------------------------------- | | **CPU** | 8+ cores | | **RAM** | 16 GB min; 64 GB recommended for production / heavy model export workloads | | **GPU** | Intel® Arc™ A770 (16 GB) or equivalent Intel GPU | | **Storage** | 50 GB SSD | ### Production / Multi-Station | Component | Specification | | ----------- | --------------------------------------------------------------- | | **CPU** | 16+ cores | | **RAM** | 64 GB | | **GPU** | Intel® Data Center GPU Max (48 GB) — for 4+ concurrent stations | | **Storage** | 200 GB NVMe SSD | **GPU VRAM guidance:** The Qwen2.5-VL-7B INT8 model requires ~8 GB of VRAM. The default `cache_size=4` reserves an additional 4 GB VRAM for the KV cache. Total VRAM needed is around 12 GB, which fits in an Intel® Arc™ A770 16 GB. On **integrated GPU** (iGPU) platforms such as Wildcat Lake and Meteor Lake, the KV cache is drawn from **system RAM** instead of dedicated VRAM; in such a case, use a smaller value (e.g. `CACHE_SIZE=2`) to avoid exhausting system RAM. Set `export CACHE_SIZE=` before running `setup_models.sh`. For a full per-platform sizing table and step-by-step instructions see [ovms-service/README.md — Tuning the KV Cache Size](https://github.com/intel-retail/order-accuracy/blob/main/ovms-service/README.md#tuning-the-kv-cache-size). > **Model Export RAM Note:** 16 GB system RAM is sufficient for **inference-only** > deployments. For first-time model export (`setup_models.sh` INT8 quantization), a > higher-memory host (48–64 GB recommended) avoids potential OOM and corrupt IR files — export > once there and copy `ovms-service/models/` to the target system. If you must export on 16 GB, > set `export CACHE_SIZE=2` first. See [ovms-service/README.md — Tuning the KV Cache Size](https://github.com/intel-retail/order-accuracy/blob/main/ovms-service/README.md#tuning-the-kv-cache-size) for details. --- ## Software Requirements ### Operating System Ubuntu 22.04 LTS is the validated platform (matches the `intel/dlstreamer:2025.2.0-ubuntu22` base image). ### Container Runtime | Software | Minimum Version | | -------------- | --------------- | | Docker Engine | 24.0 | | Docker Compose | V2 (2.20+) | ### GPU Drivers Intel GPU drivers must be installed from [packages.intel.com](https://packages.intel.com). Verify the GPU is accessible to Docker: ```bash ls /dev/dri/ docker run --rm --device /dev/dri intel/openvino_dev:latest python3 -c \ "from openvino.runtime import Core; print(Core().available_devices)" ``` Expected output includes `GPU`. --- ## Network Requirements ### Port Configuration | Service | Port | Purpose | | ------------------ | ---- | ------------------------------- | | Order Accuracy API | 8000 | REST API | | OVMS VLM | 8001 | Model inference | | Gradio UI | 7860 | Web interface | | MinIO API | 9000 | S3-compatible storage | | MinIO Console | 9001 | Storage admin UI | | Semantic Service | 8080 | Semantic matching | | RTSP Streamer | 8554 | Video streaming (parallel mode) | ### RTSP Requirements (Parallel Mode) | Requirement | Specification | | ----------- | ----------------- | | Protocol | RTSP/RTP over TCP | | Codec | H.264 | | Resolution | 720p–1080p | | Frame Rate | 15–30 FPS | --- ## Pre-Deployment Checklist - [ ] Docker and Docker Compose installed and working - [ ] Intel GPU drivers installed and GPU visible to Docker - [ ] Required ports available (8000, 7860, 8001, 9000, 9001, 8080) - [ ] At least 50 GB free disk space - [ ] **16 GB+ RAM available** (sufficient for inference; for first-time model export 48–64 GB recommended — export on a high-RAM host and copy `ovms-service/models/` to the target system) - [ ] VLM model downloaded (`setup_models.sh` completed) - [ ] `.env` file configured - [ ] Camera RTSP URLs accessible from host (parallel mode) ## Next Steps - [Get Started](../get-started.md) - Set up and run the application - [API Reference](../api-reference.md) - REST endpoint documentation - [How to Build](./build-from-source.md) - Build from source code