Abdulvahap Ogut

Corpus Hub contributor since 2026-10-17

Abdulvahap Ogut's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

17files

2,868lines

★ 4GitHub stars on repo

Totals across every corpus @vahapogut appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the AI-fire-detection corpus

vahapogut/AI-fire-detection: Advanced Real-Time Fire & Smoke Detection System using YOLOv8 AI, Python (FastAPI), and Next.js. Features multi-camera support, instant…

Look up how AI-fire-detection implements artificial-intelligence, computer-vision, fastapi, with answers cited to file and line.
Reuse a worked example: the commit “Add detection regions, image analysis and searchable event history” (17 files · TypeScript, Python).
Answer from AI-fire-detection's real TypeScript source instead of memory (Web and frontend platform).

Example questions

Where does AI-fire-detection handle “Add detection regions, image analysis and searchable event history”?
How does AI-fire-detection implement artificial-intelligence?
What does frontend do in AI-fire-detection?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository vahapogut/AI-fire-detection with XERJ (https://hub.xerj.org/corpus/vahapogut--ai-fire-detection).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/vahapogut/AI-fire-detection AI-fire-detection && git -C AI-fire-detection checkout 8a0249bb96181920a2be9c34577874b4e7ce4b0e
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./AI-fire-detection --url http://127.0.0.1:9200 --prefix ai-fire-detection --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus vahapogut--ai-fire-detection · Web and frontend platform
Related corpora: react-spectrum, carbon, VinayRamaj/IntelliPDF, BaghdasaryanNarek/appflow-profiler
Case study: reference coding for agents

Selected work

GitHub ★ 4

vahapogut/AI-fire-detection

8a0249bb96 Add detection regions, image analysis and searchable event history

selected commit: 17 files · 2,868 lines · TypeScript, Python · frontend, backend, the project root

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus vahapogut--ai-fire-detectionWEBMITartificial-intelligencecomputer-visionfastapifire-detectiongoruntu-islemenextjs agreed 2026-10-17

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/vahapogut/badge.svg)](https://hub.xerj.org/contributors/vahapogut)

Included with the author's permission (email, 2026-10-17), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.