ai-image-aura
Local-first AI image studio with OpenAI, Google, and local models. Batch generation, Autopilot prompt refinement, layered editing, cost tracking, and a replayable image archive
What XERJ indexed
Snapshot
The whole repository at commit efb38afcaf (2026-10-24). main is 8 commits ahead.
Selected work
“preserve image work and replay across failures”. 27 files, 1,185 lines in e2e, src/archive, src/lineage.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The author agreed by email on 2026-10-25. 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
image-generationreacttypescriptviteai-image-generationfluxgenerative-aigoogle-gemini
Example questions
- How does ai-image-aura implement image-generation?
- Where does ai-image-aura handle “preserve image work and replay across failures”?
- What does e2e do in ai-image-aura?
Inside the indexed corpus
- Languages by size: TypeScript 88.4%, JavaScript 6.2%, CSS 4.4%, Shell 1%, HTML 0.1%.
- On GitHub since 2025-12-22, last push 2026-10-26, 251 commits on main.
- The pin is 8 commits behind main; the corpus answers from the pinned code, not the newest.
Licence on GitHub and in the corpus
GitHub reported MIT for rupertgermann/ai-image-aura on 2026-10-29, and the LICENSE file at commit efb38afcaf was reviewed as MIT. They match, so answers from this corpus carry the same terms as the live repository.
Contributors
Rupert Germann (@rupertgermann) has 1 selected repository on the hub.
Using XERJ with ai-image-aura
- RAG without a vector database: one hybrid index The hub files it under AI, prompts and agents.
- Ask questions about a GitHub repo without cloning it
- Index a reference library for a coding agent
- ripgrep vs a code index for coding agents: 30 tasks
The prompt
Paste it into your AI agent. It clones rupertgermann/ai-image-aura at the pinned commit and indexes it on your machine.
Search the GitHub repository rupertgermann/ai-image-aura with XERJ (https://hub.xerj.org/corpus/rupertgermann--ai-image-aura). 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/rupertgermann/ai-image-aura ai-image-aura && git -C ai-image-aura checkout efb38afcafc4ae4c5e5e0c888672785748abeaa6 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./ai-image-aura --url http://127.0.0.1:9200 --prefix ai-image-aura --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: MIT. Keep the copyright notice and credit the authors.
Related
Rupert GermannAI, prompts and agents corporaprompt-engineering-guideasyncapi-studioreact-spectrumfazal305/devspacefazal305/ai-research-notebookfazal305/devflow
Stats: GitHub API, fetched 2026-10-29. Selected work and consent: the XERJ registry.