add both skill and knowledge extractor

app.py

@@ -1,7 +1,9 @@
 import gradio as gr
 from transformers import pipeline
 
-token_classifier = pipeline(model="jjzha/jobbert_skill_extraction", aggregation_strategy="simple")
+token_skill_classifier = pipeline(model="jjzha/jobbert_skill_extraction")
+token_knowledge_classifier = pipeline(model="jjzha/jobbert_knowledge_extraction")
+
 
 examples = [
         "Knowing Python is a plus.",
@@ -9,13 +11,26 @@ examples = [
 
 
 def ner(text):
-    output = token_classifier(text)
+    output_skills = token_skill_classifier(text)
+    for result in output_skills:
+        if result.get("entity"):
+            tag = results["entity"]
+            results["entity"] = tag + "skill"
+
+    output_knowledge = token_skill_classifier(text)
+    for result in output_knowledge:
+        if result.get("entity"):
+            tag = results["entity"]
+            results["entity"] = tag + "knowledge"
+
+    output = output_skills + output_knowledge
+
     return {"text": text, "entities": output}
 
 
-demo = gr.Interface(ner,
-                    gr.Textbox(placeholder="Enter sentence here..."),
-                    gr.HighlightedText(),
+demo = gr.Interface(fn=ner,
+                    inputs=gr.Textbox(placeholder="Enter sentence here..."),
+                    outputs=gr.HighlightedText(),
                     examples=examples)
 
 demo.launch()