Vinay Ramaj

Corpus Hub contributor since 2026-10-24

Vinay Ramaj'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

29files

3,680lines

★ 1GitHub stars on repo

Totals across every corpus @VinayRamaj 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 IntelliPDF corpus

VinayRamaj/IntelliPDF: AI-powered PDF Assistant built with React, FastAPI, and Google Gemini

Look up how IntelliPDF implements artificial-intelligence, fastapi, gemini-ai, with answers cited to file and line.
Reuse a worked example: the commit “upgrade to v2.0 with split-screen viewer, interactive quiz, fla…” (29 files · TypeScript, Python).
Answer from IntelliPDF's real TypeScript source instead of memory (Web and frontend platform).

Example questions

How does IntelliPDF implement artificial-intelligence?
What does frontend do in IntelliPDF?

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

Search the GitHub repository VinayRamaj/IntelliPDF with XERJ (https://hub.xerj.org/corpus/vinayramaj--intellipdf).
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/VinayRamaj/IntelliPDF IntelliPDF && git -C IntelliPDF checkout a0d9047d7e3e2c4a6b43be64bc0ae3320d015de1
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./IntelliPDF --url http://127.0.0.1:9200 --prefix intellipdf --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 vinayramaj--intellipdf · Web and frontend platform
Related corpora: esbuild, cognita, vahapogut/AI-fire-detection, albidev/hermes-mission-control
Case study: reference coding for agents

Selected work

GitHub ★ 1

VinayRamaj/IntelliPDF

a0d9047d7e feat: upgrade to v2.0 with split-screen viewer, interactive quiz, fla…

selected commit: 29 files · 3,680 lines · TypeScript, Python · frontend, backend

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

selected · in licence reviewcorpus vinayramaj--intellipdfWEBMITartificial-intelligencefastapigemini-aipdfpythonreact agreed 2026-10-24

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/VinayRamaj/badge.svg)](https://hub.xerj.org/contributors/VinayRamaj)

Included with the author's permission (email, 2026-10-24), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.