ml-pipes
Build composable ML pipelines that are explicit, traceable, and optimizable
What XERJ indexed
Selected work

“Move inspection previews to renderer and expand list items”. 5 files, 569 lines in packages/core, examples.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
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
- How does ml-pipes implement composable?
- Where does ml-pipes handle “Move inspection previews to renderer and expand list items”?
- What does packages/core do in ml-pipes?
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
KeivanAI, prompts and agents corporaadalflowcognitaopennyai-legal-nlpMrKyaw/Onnx_Rust_Web_Assembly_Triton_Promethus_GrafanaHAITHM-ALAKHALI/virtual_mouseDeepLearnPhysics/spine
Selected work and consent: the XERJ registry.