Rework app.py

app.py

@@ -1,8 +1,16 @@
-from typing import Dict, List
+from typing import Dict, List, Union
 
 import gradio as gr
 from lexenlem.preprocessing.adhoc import AdHocLemmatizer
 
+title = "Lexicon-enhanced lemmatization for Estonian"
+
+with open("./article.md") as file:
+    article: str = file.read()
+
+with open("./description.txt") as file:
+    description: str = file.read()
+
 models: Dict[str, AdHocLemmatizer] = {
     "Lemmatize": AdHocLemmatizer(path="vb_stanza_no_compound_no_deriv.pt", use_stanza=True),
     "Lemmatize with special symbols": AdHocLemmatizer(
@@ -10,71 +18,38 @@ models: Dict[str, AdHocLemmatizer] = {
     )
 }
 
+examples: List[List[Union[str, bool]]] = []
+with open("examples.tsv") as file:
+    for line in file:
+        ex, flag = line.split("\t")
+        flag = bool(int(flag))
+        examples.append(
+            [ex, flag]
+        )
 
-def predict(text: str, model_name: str) -> List[str]:
-    if model_name not in models:
-        raise RuntimeError("Unknown model")
-    return models[model_name](text)
 
+def predict(text: str, output_special_symbols: bool) -> List[str]:
+    if output_special_symbols:
+        return models["Lemmatize with special symbols"](text)
+    else:
+        return models["Lemmatize"](text)
 
-gradio_ui = gr.Interface(
+
+demo = gr.Interface(
     fn=predict,
-    title="Lexicon-enhanced lemmatization for Estonian",
-    description="The purpose of this demo is to demonstrate the results of"
-                " Lexicon-Enhanced Neural Lemmatization for Estonian developed by TartuNLP research group."
-                " The idea is to utilize the input of an external resource"
-                " (a `lexicon` — Vabamorf morphological analyzer in this particular case)"
-                " as an additional input to improve the results of a neural lemmatizer model. Said additional input"
-                " is a concatenation of one or more lemma candidates provided by Vabamorf. Morphological features and"
-                " the part of speech are provided by Stanza in this demo, although it's possible to use native Vabamorf"
-                " features as well (the results, however, are going to be slightly worse).\n\n"
-                " The lexicon-enhanced lemmatizer itself is based on an older version of Stanza. The models were"
-                " trained on the Estonian Dependency Treebank version 2.7.\n\n"
-                " Two variants of lemmatization are provided in the demo: regular lemmatization and lemmatization with"
-                " special symbols, which are `=` and `_`, denoting morphological derivation and separating parts of"
-                " compound words respectively. The latter was trained on the original data with Vabamorf set to output"
-                " these special symbols, while the latter was trained with `=` and `_` removed from the data and"
-                " vabamorf output.",
+    title=title,
+    description=description,
+    article=article,
     inputs=[
         gr.inputs.Textbox(lines=7, label="Input text in the box below", placeholder="Text to lemmatize"),
-        gr.inputs.Radio(list(models.keys()), label="Lemmatization type")
+        gr.inputs.Checkbox(label="Output special symbols")
     ],
     outputs=[
         gr.outputs.Textbox()
     ],
-    examples=[
-        [
-            "Ekspositsioonid võiksid alata juba kunstihotellide fuajeedest.",
-            "Lemmatize"
-        ],
-        [
-            "Ekspositsioonid võiksid alata juba kunstihotellide fuajeedest.",
-            "Lemmatize with special symbols"
-        ],
-        [
-            "Kõik uuritavad võeti vastu TÜ üld- ja molekulaarpatoloogia instituudis inimesegeneetika uurimisrühmas.",
-            "Lemmatize with special symbols"
-        ],
-        [
-            "Peamiselt viimasele toetub ka järgnev artikkel.",
-            "Lemmatize"
-        ],
-        [
-            "Arutletakse selle üle, mida ülearuse rahaga peale hakata.",
-            "Lemmatize"
-        ],
-        [
-            "Väikesele poisile tuuakse apteegist söögiisu tõstmiseks kalamaksaõli.",
-            "Lemmatize"
-        ],
-        [
-            "Tulevased beebid olid justkui peegeldusena pilgu beebisinas ja veel mingi ähmane lubadus.",
-            "Lemmatize"
-        ],
-    ],
+    examples=examples,
     allow_screenshot=False,
     allow_flagging="never",
 )
 
-
-gradio_ui.launch(debug=False, enable_queue=True)
+demo.launch(debug=False, enable_queue=True, cache_examples=True)