Add "Auto-detected" as a language.

When the user choose "Auto-detected", the choice remains on the following queries.
The detected language is displayed.

For example "Auto-detected (en)":
* the next query language is going to be auto detected
* for the current query, the detected language is English.

This replace the autodetect_search_language plugin.

searx/utils.py

@@ -53,6 +53,9 @@ _LANG_TO_LC_CACHE: Dict[str, Dict[str, str]] = {}
 _FASTTEXT_MODEL: Optional["fasttext.FastText._FastText"] = None
 """fasttext model to predict laguage of a search term"""
 
+SEARCH_LANGUAGE_CODES = frozenset([searxng_locale[0].split('-')[0] for searxng_locale in language_codes])
+"""Languages supported by most searxng engines (:py:obj:`searx.languages.language_codes`)."""
+
 
 class _NotSetClass:  # pylint: disable=too-few-public-methods
     """Internal class for this module, do not create instance of this class.
@@ -637,11 +640,53 @@ def _get_fasttext_model() -> "fasttext.FastText._FastText":
     return _FASTTEXT_MODEL
 
 
-def detect_language(text: str, threshold: float = 0.3, min_probability: float = 0.5) -> Optional[str]:
-    """https://fasttext.cc/docs/en/language-identification.html"""
+def detect_language(text: str, threshold: float = 0.3, only_search_languages: bool = False) -> Optional[str]:
+    """Detect the language of the text parameter
+
+    Args:
+        * text (str): the string whose language is to be detected.
+        * threshold (float): threshold filters the returned labels by a threshold on probability.
+          A choice of 0.3 will return labels with at least 0.3 probability.
+        * only_search_languages (bool): if True, returns only supported SearXNG search languages.
+          see :py:obj:`searx.languages`
+
+
+    Raises:
+        * ValueError: if text is not a string
+
+    Returns:
+        * result (str, None): the detected language code or None. See below.
+
+    The language detection is done by using `a fork`_ of the fastText_ library (`python
+    fasttext`_). fastText_ distributes the `language identification model`_, for
+    reference:
+
+    - `FastText.zip: Compressing text classification models`_
+    - `Bag of Tricks for Efficient Text Classification`_
+
+    The `language identification model`_ support the language codes (ISO-639-3)::
+    af als am an ar arz as ast av az azb ba bar bcl be bg bh bn bo bpy br bs bxr
+    ca cbk ce ceb ckb co cs cv cy da de diq dsb dty dv el eml en eo es et eu fa
+    fi fr frr fy ga gd gl gn gom gu gv he hi hif hr hsb ht hu hy ia id ie ilo io
+    is it ja jbo jv ka kk km kn ko krc ku kv kw ky la lb lez li lmo lo lrc lt lv
+    mai mg mhr min mk ml mn mr mrj ms mt mwl my myv mzn nah nap nds ne new nl nn
+    no oc or os pa pam pfl pl pms pnb ps pt qu rm ro ru rue sa sah sc scn sco sd
+    sh si sk sl so sq sr su sv sw ta te tg th tk tl tr tt tyv ug uk ur uz vec vep
+    vi vls vo wa war wuu xal xmf yi yo yue zh
+
+    .. _a fork: https://github.com/searxng/fasttext-predict
+    .. _fastText: https://fasttext.cc/
+    .. _python fasttext: https://pypi.org/project/fasttext/
+    .. _language identification model: https://fasttext.cc/docs/en/language-identification.html
+    .. _Bag of Tricks for Efficient Text Classification: https://arxiv.org/abs/1607.01759
+    .. _`FastText.zip: Compressing text classification models`: https://arxiv.org/abs/1612.03651
+    """
     if not isinstance(text, str):
         raise ValueError('text must a str')
     r = _get_fasttext_model().predict(text.replace('\n', ' '), k=1, threshold=threshold)
-    if isinstance(r, tuple) and len(r) == 2 and len(r[0]) > 0 and len(r[1]) > 0 and r[1][0] > min_probability:
-        return r[0][0].split('__label__')[1]
+    if isinstance(r, tuple) and len(r) == 2 and len(r[0]) > 0 and len(r[1]) > 0:
+        language = r[0][0].split('__label__')[1]
+        if only_search_languages and language not in SEARCH_LANGUAGE_CODES:
+            return None
+        return language
     return None