ml-pipes

Build composable ML pipelines that are explicit, traceable, and optimizable

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 29682ab3d4 (2026-10-29).

Selected work

Keivan
@Tenkei

“Move inspection previews to renderer and expand list items”. 5 files, 569 lines in packages/core, examples.

Licence

The repository

Apache-2.0

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

The XERJ corpus

Apache-2.0, with credit

The author agreed by email on 2026-11-01. 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

composablecomputer-visioninferencemachine-learningpipelinevisionml-pipelineharness-engineering

Example questions

The prompt

Paste it into your AI agent. It clones trained-by-humans/ml-pipes at the pinned commit and indexes it on your machine.

Search the GitHub repository trained-by-humans/ml-pipes with XERJ (https://hub.xerj.org/corpus/trained-by-humans--ml-pipes).
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/trained-by-humans/ml-pipes ml-pipes && git -C ml-pipes checkout 29682ab3d4aa5800ebdfa297ad89907f97a0e527
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./ml-pipes --url http://127.0.0.1:9200 --prefix ml-pipes --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.