Correct app.py

app.py

@@ -15,21 +15,22 @@ if 'parser' not in nlp.pipe_names and 'senter' not in nlp.pipe_names:
 
 def get_highlighted_text(doc):
     """
-    Wraps detected ASCs in each sentence with a <span> tag that carries the entity tag as a
-    data attribute. The output HTML is wrapped with a CSS <style> block that applies your desired styling.
+    Wraps detected ASCs in each sentence with a <span> tag that carries the entity tag
+    in the data-entity attribute. The final HTML output is prepended with a CSS block that
+    applies your desired styles.
     """
     highlighted_sentences = []
     for sent in doc.sents:
         text = sent.text
-        # Find all entities that are fully contained within this sentence.
+        # Find all entities completely contained within this sentence.
         ents_in_sent = [ent for ent in doc.ents if ent.start_char >= sent.start_char and ent.end_char <= sent.end_char]
         if ents_in_sent:
-            # Process entities in reverse order so that character offsets remain valid.
+            # Process entities in reverse order to preserve character offsets.
             ents_in_sent = sorted(ents_in_sent, key=lambda x: x.start_char, reverse=True)
             for ent in ents_in_sent:
                 ent_start = ent.start_char - sent.start_char
                 ent_end = ent.end_char - sent.start_char
-                # Wrap the detected entity with a span and include its tag via the data-entity attribute.
+                # Wrap the entity text with a <span> that carries the entity tag via data-entity.
                 text = (
                     text[:ent_start]
                     + f'<span class="entity" data-entity="{ent.label_}">'
@@ -40,7 +41,7 @@ def get_highlighted_text(doc):
         highlighted_sentences.append(text)
     result = "<br><br>".join(highlighted_sentences)
     
-    # Embed the provided CSS for styling.
+    # Embed the CSS that controls the appearance (using your tag style) and increases line spacing.
     style = """
     <style>
         body {
@@ -56,60 +57,7 @@ def get_highlighted_text(doc):
             background-color: white;
             border-radius: 8px;
             box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
-        }
-        h1 {
-            font-size: 2rem;
-            font-weight: 700;
-            margin-bottom: 20px;
-            text-align: center;
-        }
-        p, textarea, input {
-            font-size: 0.9rem;
-            font-weight: 400;
-        }
-        .info {
-            font-size: 0.9rem;
-            color: #333;
-        }
-        .accuracy-highlight {
-            color: #007030;
-            font-weight: bold;
-        }
-        input[type="submit"], input[type="button"] {
-            font-size: 0.9rem;
-        }
-        textarea {
-            width: 95%;
-            max-width: 95%;
-            padding: 20px;
-            margin-bottom: 10px;
-            border: 1px solid #ccc;
-            border-radius: 4px;
-            resize: vertical;
-        }
-        input[type="submit"], input[type="button"] {
-            background-color: #007030;
-            color: white;
-            padding: 10px 20px;
-            border: none;
-            border-radius: 4px;
-            cursor: pointer;
-            margin-right: 10px;
-        }
-        input[type="submit"]:hover, input[type="button"]:hover {
-            background-color: #45a049;
-        }
-        .results {
-            margin-top: 20px;
-            line-height: 2.5;
-        }
-        .tag-counts {
-            margin-top: 2px;
-            text-align: center;
-        }
-        .tag-counts h2 {
-            margin-bottom: 5px;
-            text-align: left;
+            line-height: 2em;  /* Increased line spacing */
         }
         .entity {
             display: inline-block;
@@ -205,7 +153,6 @@ def get_highlighted_text(doc):
     """
     return style + "<div class='container'>" + result + "</div>"
 
-
 def process_text(input_text):
     """
     Process input text to detect and tag ASCs.
@@ -224,24 +171,25 @@ def process_text(input_text):
     
     return get_highlighted_text(doc)
 
-# Define sample text
-sample_text = "Nancy sliced the tire open."
+# Define a simpler sample text.
+sample_text = "Oliver baked magical bread. Lyla enjoyed the treat."
 
 def fill_sample_text():
     return sample_text
 
 # Build the Gradio interface.
 with gr.Blocks() as demo:
-    gr.Markdown("# ASC tagger demo")
-    gr.Markdown("This demo version of the Argument Structure Construction (ASC) tagger processes sentences and identifies nine types of ASCs. The identified ASCs are highlighted in the output text.")
+    gr.Markdown("# ASC Tagger Demo")
+    gr.Markdown("Enter some text to have ASCs tagged. Use the button below to fill in sample text.")
     
-    input_textbox = gr.Textbox(lines=5, label="Input text", placeholder="Enter text here...")
-    output_html = gr.HTML(label="Tagged text")
-    fill_btn = gr.Button("Fill sample sentence")
+    # The input textbox is not modified by submission.
+    input_textbox = gr.Textbox(lines=5, label="Input Text", placeholder="Enter text here...")
+    output_html = gr.HTML(label="Tagged Text")
+    fill_btn = gr.Button("Fill Sample Text")
     tag_btn = gr.Button("Tag ASCs")
     
     fill_btn.click(fn=fill_sample_text, inputs=[], outputs=input_textbox)
     tag_btn.click(fn=process_text, inputs=input_textbox, outputs=output_html)
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch()