BinkRead

A modern Flask web application that uses Facebook's BART model to automatically summarize PDF documents. Perfect for researchers, students, and professionals who need quick insights from lengthy documents

A new way for AI to search for data
View on GitHub
2GitHub stars
8commits on main
0forks

HTML 49.9%, Python 45.3%, Batchfile 4.8% · created 2025-10-22 · last push 2025-10-22

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit cbce4a9861. It is the newest commit on main.

Selected work

Tuhin Chakrabarty
@Tuhin-SnapD

Licence

The repository

NONE

LICENSE file checked at the pinned commit; the author agreed to inclusion.

The XERJ corpus

NONE, with credit

The owner added it on hub.xerj.org after signing in with GitHub, on 2026-10-29. Same terms as the repository. Answers name the repo, the commit and the file:line.

selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution

The prompt

Paste it into your AI agent. It clones Tuhin-SnapD/BinkRead at the pinned commit and indexes it on your machine.

Search the GitHub repository Tuhin-SnapD/BinkRead with XERJ (https://hub.xerj.org/corpus/tuhin-snapd--binkread).
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/Tuhin-SnapD/BinkRead BinkRead && git -C BinkRead checkout cbce4a9861fb94a8dfaab90f1ddb6ea6a8afb155
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./BinkRead --url http://127.0.0.1:9200 --prefix binkread --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: check the LICENSE file. Keep the copyright notice and credit the authors.

Related

Stats: GitHub API, fetched 2026-10-29. Selected work and consent: the XERJ registry.