fixes

app.py

@@ -10,13 +10,12 @@ DEFAULT_TEXT = "Apple is looking at buying U.K. startup for $1 billion."
 DEFAULT_TOK_ATTR = ['idx', 'text', 'pos_', 'lemma_', 'shape_', 'dep_']
 DEFAULT_ENTS = ['CARDINAL', 'DATE', 'EVENT', 'FAC', 'GPE', 'LANGUAGE', 'LAW', 'LOC', 'MONEY',
                 'NORP', 'ORDINAL', 'ORG', 'PERCENT', 'PERSON', 'PRODUCT', 'QUANTITY', 'TIME', 'WORK_OF_ART']
-
+DEFAULT_COLOR = "linear-gradient(90deg, #FFCA74, #7AECEC)"
 texts = {"en": DEFAULT_TEXT, "ca": "Apple està buscant comprar una startup del Regne Unit per mil milions de dòlars", "da": "Apple overvejer at købe et britisk startup for 1 milliard dollar.", "de": "Die ganze Stadt ist ein Startup: Shenzhen ist das Silicon Valley für Hardware-Firmen",
          "el": "Η άνιση κατανομή του πλούτου και του εισοδήματος, η οποία έχει λάβει τρομερές διαστάσεις, δεν δείχνει τάσεις βελτίωσης.", "es": "Apple está buscando comprar una startup del Reino Unido por mil millones de dólares.", "fi": "Itseajavat autot siirtävät vakuutusvastuun autojen valmistajille", "fr": "Apple cherche à acheter une start-up anglaise pour 1 milliard de dollars", "it": "Apple vuole comprare una startup del Regno Unito per un miliardo di dollari",
          "ja": "アップルがイギリスの新興企業を１０億ドルで購入を検討", "ko": "애플이 영국의 스타트업을 10억 달러에 인수하는 것을 알아보고 있다.", "lt": "Jaunikis pirmąją vestuvinę naktį iškeitė į areštinės gultą", "nb": "Apple vurderer å kjøpe britisk oppstartfirma for en milliard dollar.", "nl": "Apple overweegt om voor 1 miljard een U.K. startup te kopen",
          "pl": "Poczuł przyjemną woń mocnej kawy.", "pt": "Apple está querendo comprar uma startup do Reino Unido por 100 milhões de dólares", "ro": "Apple plănuiește să cumpere o companie britanică pentru un miliard de dolari", "ru": "Apple рассматривает возможность покупки стартапа из Соединённого Королевства за $1 млрд", "sv": "Apple överväger att köpa brittisk startup för 1 miljard dollar.", "zh": "作为语言而言，为世界使用人数最多的语言，目前世界有五分之一人口做为母语。"}
 
-
 def get_all_models():
     with open("requirements.txt") as f:
         content = f.readlines()
@@ -32,11 +31,11 @@ def get_all_models():
 models = get_all_models()
 
 
-def dependency(text, col_punct, col_phrase, compact, model):
+def dependency(text, col_punct, col_phrase, compact, bg, font, model):
     nlp = spacy.load(model + "_sm")
     doc = nlp(text)
     options = {"compact": compact, "collapse_phrases": col_phrase,
-               "collapse_punct": col_punct}
+               "collapse_punct": col_punct, "bg": bg, "color":font}
     html = displacy.render(doc, style="dep", options=options)
     return html
 
@@ -150,13 +149,13 @@ with demo:
                     model_input = gr.Dropdown(
                         choices=models, value=DEFAULT_MODEL, interactive=True, label="Pretrained Pipelines")
                 with gr.Column():
-                    gr.Markdown("")
+                    text_button = gr.Button("Get text in model language")
                 with gr.Column():
                     gr.Markdown("")
                 with gr.Column():
                     gr.Markdown("")
             
-            text_button = gr.Button("Get text in model language")
+            
             with gr.Row():
                 with gr.Column():
                     text_input = gr.Textbox(
@@ -168,21 +167,30 @@ with demo:
         with gr.Tabs():
             with gr.TabItem(""):
                 with gr.Column():
-                    gr.Markdown("### Dependency Parser")
-                    col_punct = gr.Checkbox(label="Collapse Punctuation", value=True)
-                    col_phrase = gr.Checkbox(label="Collapse Phrases", value=True)
-                    compact = gr.Checkbox(label="Compact", value=False)
-                    depen_output = gr.HTML(value=dependency(DEFAULT_TEXT, True, True, False, DEFAULT_MODEL))
+                    gr.Markdown("## [Dependency Parser](https://spacy.io/usage/visualizers#dep)")
+                    with gr.Row():
+                        with gr.Column():
+                            col_punct = gr.Checkbox(label="Collapse Punctuation", value=True)
+                            col_phrase = gr.Checkbox(label="Collapse Phrases", value=True)
+                            compact = gr.Checkbox(label="Compact", value=False)
+                        with gr.Column():
+                            bg = gr.Textbox(label="Background Color", value=DEFAULT_COLOR)
+                        with gr.Column():
+                            text = gr.Textbox(label="Text Color", value="black")
+                        with gr.Column():
+                            gr.Markdown("")
+                    depen_output = gr.HTML(value=dependency(DEFAULT_TEXT, True, True, False, DEFAULT_COLOR, "black", DEFAULT_MODEL))
                     dep_button = gr.Button("Generate Dependency Parser")
+                    gr.Markdown("\n\n\n")
         with gr.Box():
             with gr.Column():
-                gr.Markdown("### Entity Recognizer")
+                gr.Markdown("## [Entity Recognizer](https://spacy.io/usage/visualizers#ent)")
                 entity_input = gr.CheckboxGroup(DEFAULT_ENTS, value=DEFAULT_ENTS)
                 entity_output = gr.HTML(value=entity(DEFAULT_TEXT, DEFAULT_ENTS, DEFAULT_MODEL))
                 ent_button = gr.Button("Generate Entity Recognizer")
         with gr.Box():
             with gr.Column():
-                gr.Markdown("### Token Properties")
+                gr.Markdown("## [Token Properties](https://spacy.io/usage/linguistic-features)")
                 with gr.Column():
                     tok_input = gr.CheckboxGroup(
                         DEFAULT_TOK_ATTR, value=DEFAULT_TOK_ATTR)
@@ -190,7 +198,7 @@ with demo:
                 tok_button = gr.Button("Generate Token Properties")
         with gr.Box():
             with gr.Column():
-                gr.Markdown("### Word and Phrase Similarity")
+                gr.Markdown("## [Word and Phrase Similarity](https://spacy.io/usage/linguistic-features#vectors-similarity)")
                 with gr.Row():
                     sim_text1 = gr.Textbox(
                         value="Apple", label="Word 1", interactive=True,)
@@ -201,7 +209,7 @@ with demo:
                 sim_button = gr.Button("Generate similarity")
         with gr.Box():
             with gr.Column():
-                gr.Markdown("### Spans")
+                gr.Markdown("## [Spans](https://spacy.io/usage/visualizers#span)")
                 with gr.Column():
                     with gr.Row():
                         span1 = gr.Textbox(
@@ -220,7 +228,7 @@ with demo:
     
     text_button.click(get_text, inputs=[model_input], outputs=text_input)
     button.click(dependency, inputs=[
-        text_input, col_punct, col_phrase, compact, model_input], outputs=depen_output)
+        text_input, col_punct, col_phrase, compact, bg, text, model_input], outputs=depen_output)
     button.click(
         entity, inputs=[text_input, entity_input, model_input], outputs=entity_output)
     button.click(
@@ -230,7 +238,7 @@ with demo:
     button.click(
         span, inputs=[text_input, span1, span2, label1, label2, model_input], outputs=span_output)
     dep_button.click(dependency, inputs=[
-        text_input, col_punct, col_phrase, compact, model_input], outputs=depen_output)
+        text_input, col_punct, col_phrase, compact, bg, text, model_input], outputs=depen_output)
     ent_button.click(
         entity, inputs=[text_input, entity_input, model_input], outputs=entity_output)
     tok_button.click(