Create new file

app.py

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+import gradio as gr
+import os
+os.system('python -m spacy download en_core_web_sm')
+import spacy
+from spacy import displacy
+
+nlp = spacy.load("en_core_web_sm")
+
+def text_analysis(text):
+    doc = nlp(text)
+    html = displacy.render(doc, style="dep", page=True)
+    html = (
+        "<div style='max-width:100%; max-height:360px; overflow:auto'>"
+        + html
+        + "</div>"
+    )
+    pos_count = {
+        "char_count": len(text),
+        "token_count": 0,
+    }
+    pos_tokens = []
+  
+    rows = []
+    for token in doc:
+    rows.append((token.text, token.lemma_, token.pos_, token.tag_, token.dep_,
+            token.shape_, token.is_alpha, token.is_stop))
+  
+    table = pd.DataFrame(rows, columns = ["TEXT", "LEMMA","POS","TAG","DEP","SHAPE","ALPHA","STOP"])
+
+    return table, html
+
+demo = gr.Interface(
+    text_analysis,
+    gr.Textbox(placeholder="Enter sentence here..."),
+    [gr.Dataframe(), "html"],
+    examples=[
+        ["Data Science Dojo is the leading platform providing training in data science, data analytics, and machine learning."],
+        ["It's the best time to execute the plan."],
+    ],
+)
+
+demo.launch()