Add the full Arabic Wiktionary, and answer in Urdu before English

Classical Persian quotes Arabic outright — Hafez opens with a whole hemistich
of it — and none of it resolved before. The full Arabic export brings 36,627
entries and 819,608 new form pairs, and the forms are the point: السّاقی,
الناس, تَلْقَ and تَهْوی are all conjugated or carry the article, so they only
reach a definition through that index. Nine of the ten Arabic words in the
sample now answer where none did.

The cost is real and worth stating: the database goes from 28 MB to 87 MB and
the release APK from 10.6 MB to 29.2 MB, with another 87 MB unpacked on first
run, so about 116 MB installed.

Results are now ordered the way a reader of this app wants them: the Urdu
definition first, because it needs no translating, then Persian, then sources
keyed on another language, with English arriving only through whatever is left.
Arabic sorts last outright — its index is larger than every other source
combined, which makes it the likeliest to match by coincidence.

No Persian-to-Urdu dictionary. Wiktionary's Persian entries carry no
translations at all; the tables live only on English pages, in a 3.3 GB export,
so it would mean pivoting through an English sense. A sample of that file
projects about 6,900 Persian words with any Urdu equivalent, mostly modern
dictionary vocabulary rather than the language of the poems — not worth the
pivot. tools/README.md records why, so the question doesn't get reopened from
scratch.

Verified on an API 36 emulator: عشق returns all five sources with the Urdu
definition at the top.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

tools/README.md

@@ -44,6 +44,25 @@ source here whose definitions are written **in Urdu** — thin (around 3,100 usa
 31,000 pages, many being stubs), but for a word it does carry an Urdu reader is better served by
 it than by a translation into English.
 
+## Arabic
+
+```sh
+curl -L -o ar.jsonl https://kaikki.org/dictionary/Arabic/kaikki.org-dictionary-Arabic.jsonl
+```
+
+521 MB, almost all of it the inflection index, and that index is the point: the Arabic quoted
+inside Persian verse is conjugated, so السّاقی, الناس, تَلْقَ and تَهْوی only reach a definition
+through it. 36,627 entries and 819,608 new form pairs for about 59 MB of database.
+
+## Why there is no Persian-to-Urdu
+
+Wiktionary's Persian entries carry no translations at all — the translation tables live only on
+English pages, in a 3.3 GB export. Going Persian to Urdu would mean pivoting through an English
+sense, and a sample of that file projects only about 6,900 Persian words with any Urdu
+equivalent, most of them modern dictionary vocabulary rather than the language of the poems. The
+definitions written in Urdu therefore come from Urdu Wiktionary directly, and are preferred over
+the English ones wherever they exist.
+
 ## Licences
 
 Each row carries its `source`, so attribution stays accurate and either source can be dropped

tools/build_dictionary.py

@@ -69,6 +69,25 @@ for line in open('ur.jsonl', encoding='utf-8'):
             forms.add((normalise(t), normalise(word)))
 print(f"wiktionary-ur: {len(entries) - n_fa} entries, {len(forms)} forms total")
 
+# Arabic, for the lines classical Persian quotes outright — Hafez opens with one.
+if os.path.exists('ar.jsonl'):
+    n_ar, f_ar = len(entries), len(forms)
+    for line in open('ar.jsonl', encoding='utf-8'):
+        try: e = json.loads(line)
+        except Exception: continue
+        word = e.get('word')
+        if not word: continue
+        gs = [g.strip() for s in e.get('senses', []) for g in (s.get('glosses') or []) if g.strip()]
+        if gs:
+            pos = e.get('pos') or ''
+            gloss = '; '.join(dict.fromkeys(gs))[:600]
+            entries.append((normalise(word), word, f"({pos}) {gloss}" if pos else gloss, 'wiktionary-ar'))
+        for f in e.get('forms', []):
+            t = f.get('form')
+            if t and t != word and not t.startswith('-') and len(t) > 1:
+                forms.add((normalise(t), normalise(word)))
+    print(f"wiktionary-ar: {len(entries) - n_ar} entries, {len(forms) - f_ar} new forms")
+
 tag = re.compile(r'<[^>]+>')
 n0 = len(entries)
 for k, v in MDX('daneshjoo.mdx').items():