Spaces:
Running
Running
File size: 1,331 Bytes
aa0efbd deefdbe aa0efbd deefdbe cbf8784 aa0efbd deefdbe cbf8784 deefdbe cbf8784 deefdbe 174b6c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ---
title: pid-parser
emoji: 🛠️
colorFrom: green
colorTo: gray
sdk: static
pinned: false
license: cc-by-sa-4.0
short_description: "Your P&ID drawing, now data you can ask"
---
# pid-parser showcase
Turn a P&ID drawing into data you can ask: SQL tables and a graph that people and AI agents can query. A vision model finds the symbols, and traditional computer vision (thresholding and connected-component labeling) finds the connections.
Precomputed results of [pid-parser](https://github.com/dzakybd/pid-parser) on one very dense P&ID sheet (190 symbols, 732 connected pairs), run two ways, the skill on Claude Sonnet 5.5 and the Deep Agents runner on gpt-6-luna. Each run shows the drawing with the symbols found, the graph, the tables, and the SQL, CSV, GraphML and Cypher exports. The page calls no model.
Two versions: a skill for coding agents (`npx skills add dzakybd/pid-parser`) and a LangChain Deep Agents version for your own agent workflow. How it works, step by step: [the write-up](https://dzaky.ai.id/en/blog/pid-parser-pid-to-graph).
Drawing: sheet 269 of the "Dataset PID" part of [PID2Graph](https://zenodo.org/records/14803338) ([paper](https://arxiv.org/abs/2411.13929)), CC BY-SA 4.0. The drawings and the outputs derived from them are shared under CC BY-SA 4.0. The pid-parser code is MIT licensed.
|