clean up sentences section

app.py

@@ -22,16 +22,21 @@ min_value = st.slider('Select minimum selfcheck score', 0.0, maximum_score, 0.1,
 
 ds = load_data(min_score=min_value, exclude_stories=exclude_stories)
 index = st.number_input(f'Found {len(ds)} samples, choose one', min_value=0, max_value=len(ds)-1, value=0, step=1)
+min_score = st.number_input(f'Choose threshold for diplayed inconsistent sentences', min_value=0.2, max_value=1.0, value=0.4, step=0.1)
 
 # Load data based on slider values and checkbox status
 sample = ds[index]
 st.markdown(f"**Passage Score:** {sample['passage_score']:.2f}, **seed data**: {sample['seed_data']}, **format**: {sample['format']}.")
 st.markdown("---")
+st.subheader("📕 Generated text")
 st.markdown(sample['original_text'])
 
 # get inconsistent sentences
-st.subheader("🤔 Sentences with a high inconsistency score")
+st.subheader("🤔 Sentences with a high inconsistency score (> 0.5)")
 sentences = sample["sentences_and_scores"]
 sentences = [e for e in sentences if e["score"] > 0.5]
-for s in sentences:
-    st.markdown(s['sentence'])
+sentences = sorted(sentences, key=lambda d: d['score'], reverse=True)
+
+for i, s in enumerate(sentences):
+    st.markdown(f"**Sentence {i}** with score {s['score']:.2f}:\n{s['sentence']}")
+    st.markdown("---")