add scatter tip

app.py

@@ -17,6 +17,8 @@ import pickle
 
 from plotly import graph_objects as go
 
+import numpy as np
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 ATTRIBUTE_MODELS = {
@@ -81,9 +83,9 @@ def main():
     layout = go.Layout({
         "yaxis": {"title": "CAIF step probability"},
         "xaxis": {"title": "Entropy threshold"},
-        "template": "simple_white",
+        "template": "plotly_white",
     })
-    figure = go.Figure(data=[scatter], layout=layout)
+
     language = st.selectbox("Language", ("English", "Russian"))
     cls_model_name = st.selectbox(
         ATTRIBUTE_MODEL_LABEL[language],
@@ -106,8 +108,16 @@ def main():
         target_label_id = 1
     prompt = st.text_input(TEXT_PROMPT_LABEL[language], PROMPT_EXAMPLE[language])
     alpha = st.slider("Alpha", min_value=-10, max_value=10, step=1, value=0)
-    st.plotly_chart(figure)
     entropy_threshold = st.slider("Entropy threshold", min_value=0., max_value=5., step=.1, value=2.)
+    plot_idx = np.argmin(np.abs(entropy_threshold - x_s))
+    scatter_tip = go.Scatter({
+        "x": [x_s[plot_idx]],
+        "y": [y_s[plot_idx]],
+        "mode": "markers"
+    })
+    figure = go.Figure(data=[scatter, scatter_tip], layout=layout)
+    figure.update_layout(paper_bgcolor="#000000")
+    st.plotly_chart(figure)
     auth_token = os.environ.get('TOKEN') or True
     fp16 = st.checkbox("FP16", value=True)
     with st.spinner('Running inference...'):