EPS Astro Extractor v1.1.0
Description
Part of the EPS Research multi‑epoch kinematic platform: Full datasets, cross‑epoch corpora, executable examples, and the Astro‑Extractor are available at https://github.com/eps-research/rag-corpus-series
EPS Astro Extractor is a portable Streamlit application for extracting structured data from astronomical databases using a local large language model via LM Studio. No API key required. Runs entirely on local hardware.
The tool crawls any publicly accessible URL, feeds the content to a local LLM, and returns structured JSON with parameters, table data, and export options.
v1.1.0 adds:
- Windows one-click launcher (
run_extractor.bat) — double-click to install and launch, no command line required - EPS Corpora section in the sidebar with direct links to all five RAG corpora (v7/SPARC, Dwarf, GC, Z1, IntZ)
- Auto-extract mode — leave the target blank to extract all structured data from the page
- Suitable for high school students on Windows with no prior setup knowledge
Eleven quick targets are pre-configured across three categories: astronomical databases (SPARC, VizieR/CDS, NED, HyperLeda), HI survey catalogues (THINGS, LITTLE THINGS, WHISP, LVHIS), and EPS RAG Corpora (v7/SPARC, Dwarf, GC, Z1, IntZ).
Developed in support of the EPS Research RAG Corpus Series (github.com/eps-research/rag-corpus-series).
Full Platform: This record is part of the EPS Research multi‑epoch kinematic platform (SPARC + THINGS + LITTLE THINGS + WALLABY DR2 + Milky Way GC corpus + z≥6). All corpora, executable notebooks, the Astro‑Extractor, and the unified schema are available at: https://github.com/eps-research/rag-corpus-series
Files
eps_astro_extractor_banner.png
Files
(74.5 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:49a584def450e5de97e8f3f7f8ea9c47
|
63.3 kB | Preview Download |
|
md5:ff619cd5d841984275d60dc3f12eca3b
|
11.2 kB | Preview Download |
Additional details
Related works
- Is part of
- Dataset: 10.5281/zenodo.20398430 (DOI)
- Is supplement to
- Journal: 10.3389/fspas.2025.1680387 (DOI)
- Preprint: 10.5281/zenodo.19563417 (DOI)
Software
- Repository URL
- https://github.com/eps-research/rag-corpus-series