Update app.py

app.py

@@ -65,40 +65,18 @@ with col2:
         st.write(ner_results)
         
 with col3:
-    # สร้าง NER Pipeline
-    ner_pipeline = pipeline("ner", model=model, tokenizer=tokenizer)
+    st.header("Annotation")
     
-    st.title("NER Annotation Tool")
-    st.write("Highlight Named Entities and display them in a structured format.")
-    
-    def annotate_text(text):
-        ner_results = ner_pipeline(text)
-        
-        # สร้าง Annotation Output
-        annotations = []
-        highlighted_text = text
-        
-        for entity in ner_results:
-            word = entity['word']
-            entity_label = entity['entity']
-            score = round(entity['score'], 4)
-            
-            # สร้าง Dictionary ของ Entity
-            annotations.append({"Entity": word, "Label": entity_label, "Score": score})
-            
-            # Highlight คำที่เป็น Entity
-            highlighted_text = highlighted_text.replace(word, f'<mark style="background-color: yellow">{word} ({entity_label})</mark>')
-        
-        return highlighted_text, annotations
-    
-    text = st.text_area("Enter text for NER analysis:", height=200)
-    
-    if st.button("Analyze"):
-        highlighted_text, entities = annotate_text(text)
+    if analyze_button and ner_results:
+        st.write("Edit detected entities:")
         
-        # แสดงผลลัพธ์แบบ HTML
-        st.markdown(highlighted_text, unsafe_allow_html=True)
+        annotated_entities = []
+        for i, entity in enumerate(ner_results):
+            entity_text = st.text_input(f"Entity {i+1}", value=entity['word'])
+            entity_label = st.selectbox(f"Label {i+1}", ["O", "B-SKILL", "I-SKILL", "B-TOOL", "I-TOOL"], index=0)
+            annotated_entities.append({"Entity": entity_text, "Label": entity_label})
         
-        # แสดง Entities เป็น JSON
-        st.json(entities)
+        if st.button("Save Annotation"):
+            st.write("Saved Annotations:")
+            st.json(annotated_entities)