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DESCRIPTION.md

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+This simple demo takes advantage of Gradio's HighlightedText, JSON and HTML outputs to create a clear NER segmentation.

README.md

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+
 ---
-title: Text Analysis Main
-emoji: 🚀
-colorFrom: blue
-colorTo: yellow
+title: text_analysis_main 
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
 sdk: gradio
 sdk_version: 3.6
-app_file: app.py
+app_file: run.py
 pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

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+spacyhttps://gradio-main-build.s3.amazonaws.com/c3bec6153737855510542e8154391f328ac72606/gradio-3.6-py3-none-any.whl

run.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 = []
+
+    for token in doc:
+        pos_tokens.extend([(token.text, token.pos_), (" ", None)])
+
+    return pos_tokens, pos_count, 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."],
+    ],
+)
+
+demo.launch()

setup.sh

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+python -m spacy download en_core_web_sm