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app.py

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+# URL: https://huggingface.co/spaces/gradio/text_analysis
+# imports
+import gradio as gr
+import spacy
+from spacy import displacy
+
+# load the model
+nlp = spacy.load("en_core_web_sm")
+
+# define the core function
+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 = []
+
+    for token in doc:
+        pos_tokens.extend([(token.text, token.pos_), (" ", None)])
+
+    return pos_tokens, pos_count, html
+
+# define the interface, with a textbox input, and three outputs: HighlightedText, JSON, and HTML
+demo = gr.Interface(
+    text_analysis,
+    gr.Textbox(placeholder="Enter sentence here..."),
+    ["highlight", "json", "html"],
+    examples=[
+        ["What a beautiful morning for a walk!"],
+        ["It was the best of times, it was the worst of times."],
+    ],
+)
+
+# launch
+demo.launch()