fix: token and sim update

.gitignore

@@ -0,0 +1 @@
+venv

app.py

@@ -60,7 +60,7 @@ def token(text, attributes, model):
     return data
 
 
-def vectors(text, model):
+def random_vectors(text, model):
     nlp = spacy.load(model + "_md")
     doc = nlp(text)
     n_chunks = [chunk for chunk in doc.noun_chunks]
@@ -71,6 +71,11 @@ def vectors(text, model):
     return round(choice[0].similarity(choice[1]), 2), choice[0].text, choice[1].text
 
 
+def vectors(input1, input2, model):
+    nlp = spacy.load(model + "_md")
+    return round(nlp(input1).similarity(nlp(input2)), 2)
+
+
 def span(text, span1, span2, label1, label2, model):
     nlp = spacy.load(model + "_sm")
     doc = nlp(text)
@@ -125,9 +130,10 @@ demo = gr.Blocks()
 
 with demo:
     model_input = gr.Dropdown(
-        choices=models, value=DEFAULT_MODEL, interactive=True)
+        choices=models, value=DEFAULT_MODEL, interactive=True, label="Pretrained Pipelines")
     text_button = gr.Button("Get new text")
-    text_input = gr.Textbox(value=DEFAULT_TEXT, interactive=True)
+    text_input = gr.Textbox(
+        value=DEFAULT_TEXT, interactive=True, label="Input Text")
     button = gr.Button("Generate")
     with gr.Tabs():
         with gr.TabItem("Dependency"):
@@ -144,24 +150,28 @@ with demo:
             with gr.Column():
                 tok_input = gr.CheckboxGroup(
                     DEFAULT_TOK_ATTR, value=DEFAULT_TOK_ATTR)
-                tok_output = gr.Dataframe(
-                    headers=DEFAULT_TOK_ATTR, overflow_row_behaviour="paginate")
+                tok_output = gr.Dataframe(overflow_row_behaviour="paginate")
             tok_button = gr.Button("Generate this tab")
         with gr.TabItem("Similarity"):
             with gr.Row():
-                sim_text1 = gr.Textbox(value="David Bowie", label="Chosen")
-                sim_text2 = gr.Textbox(value="the US", label="Chosen")
-            sim_output = gr.Textbox(value="0.09", label="Similarity Score")
-            sim_button = gr.Button("Generate this tab")
+                sim_text1 = gr.Textbox(
+                    value="Apple", label="Chosen", interactive=True,)
+                sim_text2 = gr.Textbox(
+                    value="U.K. startup", label="Chosen", interactive=True,)
+            sim_output = gr.Textbox(label="Similarity Score")
+            sim_random_button = gr.Button("Generate random words")
+            sim_button = gr.Button("Generate inputs")
         with gr.TabItem("Spans"):
             with gr.Column():
                 with gr.Row():
-                    span1 = gr.Textbox(label="Span 1")
-                    label1 = gr.Textbox(value="Label 1",
+                    span1 = gr.Textbox(
+                        label="Span 1", value="U.K. startup", placeholder="Input a part of the sentence")
+                    label1 = gr.Textbox(value="ORG",
                                         label="Label for Span 1")
                 with gr.Row():
-                    span2 = gr.Textbox(label="Span 2")
-                    label2 = gr.Textbox(value="Label 2",
+                    span2 = gr.Textbox(
+                        label="Span 2", value="U.K.", placeholder="Input another part of the sentence")
+                    label2 = gr.Textbox(value="GPE",
                                         label="Label for Span 2")
                 span_output = gr.HTML()
                 gr.Markdown(value="\n\n\n\n")
@@ -174,8 +184,8 @@ with demo:
         entity, inputs=[text_input, entity_input, model_input], outputs=entity_output)
     button.click(
         token, inputs=[text_input, tok_input, model_input], outputs=tok_output)
-    button.click(vectors, inputs=[text_input, model_input], outputs=[
-        sim_output, sim_text1, sim_text2])
+    button.click(vectors, inputs=[sim_text1,
+                 sim_text2, model_input], outputs=sim_output)
     button.click(
         span, inputs=[text_input, span1, span2, label1, label2, model_input], outputs=span_output)
     dep_button.click(dependency, inputs=[
@@ -183,10 +193,11 @@ with demo:
     ent_button.click(
         entity, inputs=[text_input, entity_input, model_input], outputs=entity_output)
     tok_button.click(
-        token, inputs=[text_input, tok_input, model_input], outputs=tok_output)
-    sim_button.click(vectors, inputs=[text_input, model_input], outputs=[
-        sim_output, sim_text1, sim_text2])
+        token, inputs=[text_input, tok_input, model_input], outputs=[tok_output])
+    sim_button.click(vectors, inputs=[
+                     sim_text1, sim_text2, model_input], outputs=sim_output)
     span_button.click(
         span, inputs=[text_input, span1, span2, label1, label2, model_input], outputs=span_output)
-
+    sim_random_button.click(random_vectors, inputs=[text_input, model_input], outputs=[
+                            sim_output, sim_text1, sim_text2])
 demo.launch()