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40 changes: 15 additions & 25 deletions README.md
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Expand Up @@ -20,7 +20,7 @@ text search capabilities, context-sensitive autocompletion of SPARQL queries,
live query analysis, very efficient spatial queries, and the interactive
visualization of very large numbers of geometric objects on a map.

[Here are demos of QLever](http://qlever.cs.uni-freiburg.de) on a variety of
[Here are demos of QLever](http://qlever.dev) on a variety of
large datasets, including the complete Wikidata, Wikimedia Commons,
OpenStreetMap, UniProt, PubChem, and DBLP. Those demos also feature QLever's
context-sensitive autocompletion, which makes SPARQL query construction so much
Expand Down Expand Up @@ -48,27 +48,22 @@ discussion](https://github.com/ad-freiburg/qlever/discussions).

# Quickstart

Use QLever via the `qlever` command-line interface (CLI), which can be
installed via `pip install qlever`. It is self-documenting via `qlever --help`
(for an overview of all commands) and `qlever <command> --help` (for details on
any specific command). For more information and example use cases, see
https://github.com/ad-freiburg/qlever-control .
View the latest documentation at <https://docs.qlever.dev/quickstart>.

You can control everything `qlever` does via a single configuration file, the
so-called `Qleverfile`. You can fetch any of a number of example `Qleverfile`s
(in particular, one for each of the demos mentioned above) via `qlever
setup-config <config-name>`. To write a `Qleverfile` for your own data, pick
one of these configurations as a starting point and edit the `Qleverfile` as
you see fit. Every option from the `Qleverfile` can also be set (and
overridden) via a command-line option with the same name, see `qlever <command>
--help`.
There are native packages available for

- [Debian and Ubuntu](https://docs.qlever.dev/quickstart/#debian-and-ubuntu)
- [macOS](https://docs.qlever.dev/quickstart/#macos-apple-silicon)

On other platforms simply install the `qlever` command-line
[python package using `pipx`/`uv`](https://docs.qlever.dev/quickstart/#others).
Note: QLever will be executed in a container which will come with a performance penalty.

# Using QLever without the `qlever` CLI

This is not recommended but can be useful or necessary in certain (in
particular, non-interactive) environments. QLever's main binaries are called
`IndexBuilderMain` (for loading and indexing data) and `ServerMain` (for
`qlever-index` (for loading and indexing data) and `qlever-server` (for
querying the data). Each of these has a `--help` option that describes the
available options.

Expand All @@ -84,14 +79,9 @@ client-server setup but running it in-process inside your own C++ program.
See https://github.com/ad-freiburg/qlever/pull/2100 for details and a link to a
small example program.

# Wiki and older documentation

The [Qlever Wiki](https://github.com/ad-freiburg/qlever/wiki) provides
high-level descriptions of how Qlever works, as well as performance evaluations,
experiences with some concrete datasets, and further details.
# Documentation

There is quite a bit of additional documentation in the [docs](docs) folder of
this repository. The documents in that folder are not well maintained and may
be outdated. We are currently working on an own `qlever-docs` repository that
will provide extensive documentation and tutorials. However, for the RDF/SPARQL
specialist, the self-documenting `qlever` CLI should be sufficient.
The official documentation is available at <https://docs.qlever.dev>.
Some documentation is also still [Qlever Wiki](https://github.com/ad-freiburg/qlever/wiki).
However, for the RDF/SPARQL specialist, the self-documenting `qlever` CLI
should be sufficient.
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