Update app.py

app.py

@@ -122,51 +122,32 @@ if 'first_load' not in st.session_state:
 # After
 st.subheader("Analyzed")
 with st.spinner("Analyzing..."):
-    if button or st.session_state.first_load:
-        st_analyze_results = analyze(
-            text=st_text,
-            entities=st_entities,
-            language="en",
-            score_threshold=st_threshold,
-            return_decision_process=st_return_decision_process,
-        )
-        annotated_tokens = annotate(st_text, st_analyze_results, st_entities)
-        # annotated_tokens
-        annotated_text(*annotated_tokens)
+    st_analyze_results = analyze(
+        text=st_text,
+        entities=st_entities,
+        language="en",
+        score_threshold=st_threshold,
+        return_decision_process=st_return_decision_process,
+    )
+    annotated_tokens = annotate(st_text, st_analyze_results, st_entities)
+    # annotated_tokens
+    annotated_text(*annotated_tokens)
+
 # vertical space
 st.text("")
     
 st.subheader("Anonymized")
 
 with st.spinner("Anonymizing..."):
-    if button or st.session_state.first_load:
-        st_anonymize_results = anonymize(st_text, st_analyze_results)
-        st_anonymize_results
+    st_anonymize_results = anonymize(st_text, st_analyze_results)
+    st_anonymize_results
 
 
-# table result
-st.subheader("Detailed Findings")
-if st_analyze_results:
-    res_dicts = [r.to_dict() for r in st_analyze_results]
-    for d in res_dicts:
-        d['Value'] = st_text[d['start']:d['end']]
-    df = pd.DataFrame.from_records(res_dicts)
-    df = df[["entity_type", "Value", "score", "start", "end"]].rename(
-        {
-            "entity_type": "Entity type",
-            "start": "Start",
-            "end": "End",
-            "score": "Confidence",
-        },
-        axis=1,
-    )
 
-    st.dataframe(df, width=1000)
+# table result
 else:
     st.text("No findings")
 
-st.session_state['first_load'] = True
-
 # json result
 class ToDictListEncoder(JSONEncoder):
     """Encode dict to json."""