Create app.py

app.py

@@ -0,0 +1,31 @@
+import spacy
+import gradio as gr
+from spacy import displacy
+from pdfminer.high_level import extract_text
+
+nlp = spacy.load("en_cv_info_extr")
+
+colors = {}
+for label in nlp.get_pipe('ner').labels:
+  colors[label] = "linear-gradient(90deg, #aa9cfc, #fc9ce7)"
+
+options = {"ents": list(nlp.get_pipe('ner').labels), "colors": colors}
+
+def resume_ner(file):
+    resume = extract_text(file.name)
+    doc = nlp(resume)
+    html = displacy.render(doc, style="ent", page=True, options=options)
+    html = (
+        "<div style='max-width:100%; max-height:500px; overflow:auto'>"
+        + html
+        + "</div>"
+    )
+    return html
+
+demo = gr.Interface(
+    resume_ner,
+    gr.File(file_types=[".pdf"]),
+    ["html"],
+)
+
+demo.launch()