RAGmortem

RAGmortem is an experimental open-source debugger for Retrieval-Augmented Generation applications. It helps developers investigate whether…

A new way for AI to search for data
View on GitHub
1GitHub stars

Python

What XERJ indexed

Snapshot

Whole repository

The whole repository at commit 0ba2cd1097 (2026-10-15).

Selected work

Devesh Kolte
@deveshkolte

“add 1-line LangChain and LlamaIndex callback hand…”. 3 files, 472 lines in src/ragmortem, tests.

Licence

The repository

Apache-2.0

Checked by a person at the pinned commit.

The XERJ corpus

Apache-2.0, with credit

The author agreed by email on 2026-10-24. Same terms as the repository. Answers name the repo, the commit and the file:line.

in licence reviewnot in the hub yetsuggested use: adapt with attribution

Example questions

The prompt

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

Search the GitHub repository deveshkolte/RAGmortem with XERJ (https://hub.xerj.org/corpus/deveshkolte--ragmortem).
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/deveshkolte/RAGmortem RAGmortem && git -C RAGmortem checkout 0ba2cd109735dd8c6a74c75c7b347546cbd49c85
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./RAGmortem --url http://127.0.0.1:9200 --prefix ragmortem --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: Apache-2.0. Keep the copyright notice and credit the authors.

Related

Selected work and consent: the XERJ registry.