Survival LLM
A free AI assistant and survival library (1.5 million offline articles) that runs on your own computer, with no internet. Shows the source of every answer. Mac and Windows.
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正在載入完整 README。
檢視完整 README ↗An interactive map and database cataloguing U.S. long-term environmental observatories across seven interlocking spheres:
The site uses the long-term threshold from Peters et al. 2013 (≥10 years of record) as the default inclusion gate.
The catalogue is national, but the site opens on New Mexico and the Southwest
drylands and carries a layer for the University of New Mexico's
ARID Institute — its partner centers, projects and people —
plus an index of every layer in EnviroData-NM, the
state's environmental data portal. The EnviroData-NM records are pointers: metadata
and links back to the portal's own download and OGC endpoints, with no data copied.
The Arizona Water Observatory's OGC API
collections are indexed the same way.
Switch the Scope filter to All U.S. for the whole catalogue. See
docs/arid.md.
This repo is a two-stack project (forked-and-adapted from
tyson-swetnam/cod-kmap):
scripts/, schema/, data/) — research subagents
(agents/R*-*.md) emit JSON facility records; scripts/ingest.py and the
load_*.py loaders write them into a local DuckLake
store of record (DuckDB 2.0, SQLite catalog at db/lto_catalog.sqlite, data
files in db/lake/, both gitignored); scripts/export_parquet.py writes
Parquet + GeoJSON to public/. The committed public/parquet/ is the canonical
copy of the data, and a fresh clone rebuilds the lake from it.index.html, src/, public/) —
published to GitHub Pages with no build step.Source repository for the engine: https://github.com/tyson-swetnam/cod-kmap
(MIT). Coastal/ocean facilities present in this database originate from cod-kmap;
terrestrial, atmospheric, cryospheric, agricultural, and freshwater coverage is
new in lto.
Reference framing for site selection and long-term thresholds:
Python 3.11 or newer (DuckDB 2.0).
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
python scripts/rebuild_lake_from_parquet.py # public/parquet/ → db/lto_catalog.sqlite + db/lake/
python scripts/ingest.py # data/raw/R*/*.json → upsert into the lake; reloads schema/vocab/*.csv
python scripts/qa.py # data-quality + schema-constraint gate
python scripts/export_parquet.py # lake → public/parquet/ + public/facilities.geojson
python scripts/export_view_caches.py
python -m http.server 5173 # then open http://localhost:5173/
To look at the site only, skip the Python steps: python -m http.server 5173
serves the committed public/ data as is.
MIT — see LICENSE.