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update docs: theme, text embeddings, used-by #447

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merged 9 commits into from
Nov 28, 2023
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update docs: theme, text embeddings, used-by #447

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302bc26
update epsilla tutorial
tonyyanga Nov 25, 2023
7e61c84
fit in the content section
tonyyanga Nov 25, 2023
516938c
update language
tonyyanga Nov 25, 2023
0289a0f
attempt to rerun CI
tonyyanga Nov 25, 2023
0a91583
update htmldate version and tests
tonyyanga Nov 26, 2023
b8c0219
fix comparison
tonyyanga Nov 26, 2023
679b40e
fix typos
tonyyanga Nov 27, 2023
f123228
Merge branch 'master' into master
adbar Nov 28, 2023
1c9a1b8
fix title, update requirements and used-by
adbar Nov 28, 2023
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12 changes: 10 additions & 2 deletions docs/tutorial-epsilla.rst
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@@ -1,4 +1,4 @@
Text embedding
Tutorial: Text embedding
===============
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.. meta::
Expand Down Expand Up @@ -28,7 +28,11 @@ In this tutorial, we will show you how to perform text embedding on results from
Setup Epsilla
------------------------------------------------

In this tutorial, we will run an Epsilla databse server. You can start one locally with a `Docker <https://docs.docker.com/get-started/>`_ image.
In this tutorial, we will need an Epsilla databse server. There are two ways to get one: use the free cloud version or start one locally.

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Epsill has a `cloud version <https://cloud.epsilla.com//?ref=trafilatura>`_ with a free tier. You can sign up and get a server running in a few steps.

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Alternatively, you can start one locally with a `Docker <https://docs.docker.com/get-started/>`_ image.

.. code-block:: bash

Expand All @@ -37,6 +41,8 @@ In this tutorial, we will run an Epsilla databse server. You can start one local

See `Epsilla documentation <https://epsilla-inc.gitbook.io/epsilladb/quick-start>`_ for a full quick start guide.

The rest of this guide assumes you are running a local Epsilla server on port 8888. If you are using the cloud version, replace the host and port with the cloud server address.

We need to install the database client. You can do this with pip:

.. code-block:: bash
Expand Down Expand Up @@ -145,5 +151,7 @@ We can now perform a vector search to find the most relevant project based on a

You will see the returned response is React! That is the correct answer. React is a modern frontend library, but PyTorch and Tensorflow are not.

.. image:: https://static.scarf.sh/a.png?x-pxid=51f549d1-aabf-473c-b971-f8d9c3ac8ac5
:alt:
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4 changes: 2 additions & 2 deletions setup.py
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Expand Up @@ -31,7 +31,7 @@ def get_long_description():
"brotli",
"cchardet >= 2.1.7; python_version < '3.11'", # build issue
"faust-cchardet >= 2.1.18; python_version >= '3.11'", # fix for build
"htmldate[speed] >= 1.5.1",
"htmldate[speed] >= 1.6.0",
"py3langid >= 0.2.2",
"pycurl >= 7.45.2",
],
Expand Down Expand Up @@ -112,7 +112,7 @@ def get_long_description():
"charset_normalizer >= 3.0.1; python_version < '3.7'",
"charset_normalizer >= 3.2.0; python_version >= '3.7'",
"courlan >= 0.9.4",
"htmldate >= 1.5.1",
"htmldate >= 1.6.0",
"justext >= 3.0.0",
"lxml >= 4.9.3 ; platform_system != 'Darwin'",
"lxml == 4.9.2 ; platform_system == 'Darwin'",
Expand Down
3 changes: 2 additions & 1 deletion tests/metadata_tests.py
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Expand Up @@ -192,8 +192,9 @@ def test_dates():
mystring = '<html><body><p>Veröffentlicht am 1.9.17</p></body></html>'
metadata = extract_metadata(mystring, fastmode=False)
assert metadata.date == '2017-09-01'
# behavior for fastmode=True changed in htmldate==1.6.0. On 1.5.2 and earlier, result was None
metadata = extract_metadata(mystring, fastmode=True)
assert metadata.date is None
assert metadata.date == '2017-09-01'


def test_sitename():
Expand Down
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