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
What XERJ indexed
Selected work

Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
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
Tuhin ChakrabartyNetworking, protocols and serialisation corpora
Stats: GitHub API, fetched 2026-10-29. Selected work and consent: the XERJ registry.