Sovereign HSE for Oil and Gas in Pakistan
Collection
Reference architecture and open-weight models for a sovereign, air-gapped HSE platform in Pakistan, by CodeNinja. • 8 items • Updated
choice stringlengths 8 58 | picked stringlengths 17 81 | why stringlengths 41 129 |
|---|---|---|
Frontier reasoning model | GLM 5.3 open weights at FP8, self-hosted | Strongest open agentic model; the bespoke license exempts purely internal use from the model-as-a-service security-review trigger |
Detector | RF-DETR, Apache-2.0 Nano to Large checkpoints, BF16 | The practical sovereign answer to the AGPL gate; Plus XL and 2XL excluded from the serving path |
Forecaster | Chronos-2, Apache-2.0, about 0.48 GB at 32 bit | Zero-shot multivariate forecasting with no field-of-use restriction; weights may be held, fine tuned and redistributed |
Embeddings | BGE-M3, MIT, FP16 | Dense plus sparse plus multi-vector retrieval in one pass with an 8,192-token window |
Document parsing | PaddleOCR-VL 1.6, Apache-2.0, about 0.9B parameters, BF16 | Strong on degraded multilingual scans; no user or revenue threshold; fine tuning permitted |
Tracking | Roboflow trackers, Apache-2.0 | Stable identity across frames without reintroducing copyleft after an Apache detector |
Frontier node class | One node of 8 x 141 GB HBM GPUs (H200 class) | 1,128 GB holds the 904 GB FP8 footprint with KV cache headroom |
Edge compute class | The operator's NPU/GPU accelerators, sized from measured stream and decode load | Sizing is stated as a requirement and verified at the phase-one survey |
Cameras reused subject to ONVIF reuse gates | The existing Vision AI IP camera estate, stream evidence, with gaps priced as new | Reuse on measured density, angle and class purchases |
Time synchronization holdover, driving linuxptp and chrony | OCP Time Card GNSS grandmaster with cameras and process tags | One defensible chronology across detectors, |
Edge orchestration disconnected install | Red Hat OpenShift AI self-managed, model serving, registry, pipelines and | Documented disconnected procedure for workbenches |
Serving runtimes node | KServe at the edge, vLLM on the central | Model serving matched to each tier's load |
Sovereign HSE ontology and model register for oil and gas in Pakistan
The object model and the model and equipment register from Sovereign HSE Watch, an open reference architecture for predictive health, safety and environment (HSE) intelligence at an oil and gas operator in Pakistan, by CodeNinja.
- Read the paper: https://codeatoms.ai/sovereign-hse-pakistan/
- DOI: https://doi.org/10.5281/zenodo.23119714
- Source files and PDF: https://github.com/muhammadumar89/codeninja-research
- Live view: https://huggingface.co/spaces/CodeNinjatools/sovereign-hse-pakistan
- The models: https://huggingface.co/collections/CodeNinjatools/sovereign-hse-for-oil-and-gas-in-pakistan-6ac09cb4ba7bf169f73aa765
Files
| File | What it holds |
|---|---|
objects.json |
12 typed HSE objects (site, equipment, incident, near miss, corrective action, inspection, document, sensor reading, anomaly event, agent recommendation, person, role), each with its anchor system, properties, status vocabulary and 14 typed links. Format hyper-ontology/1: designed with Praxis, implemented with Hyper Ontology. |
models.csv |
The model and equipment register: GLM 5.3 at FP8 on one node of eight 141 GB GPUs, RF-DETR, Chronos-2, BGE-M3, PaddleOCR-VL 1.6, the GPU class and the node count rule, with the reason for each choice. |
How to use it
Load the ontology to stand up the object model in a graph store or an ontology platform, map each anchored_in system to a read-only adapter, and keep every agent recommendation behind a named approver, as the paper describes.
import json
from huggingface_hub import hf_hub_download
p = hf_hub_download("CodeNinjatools/sovereign-hse-pakistan-ontology", "objects.json", repo_type="dataset")
objects = json.load(open(p))["objects"]
print([o["label"] for o in objects])
Made with
Reasoned on Praxis, CodeNinja's platform for designing physical AI systems. The object model imports into Hyper Ontology, which turns it into a living system. Both in beta; access by request. Load it with the hyper-ontology loader.
Citation
CodeNinja Engineering Team and Umar Bilal. 2026. Sovereign HSE Watch: A Reference Architecture for Predictive Health, Safety and Environment Intelligence in Pakistan's Oil and Gas Operations. CodeNinja. https://doi.org/10.5281/zenodo.23119714. CC BY 4.0.
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