判定部分のUIモデルから呼び出すようにし、関連パッケージを設定

app.py

@@ -1,8 +1,6 @@
-import random
-
-import numpy as np
 import streamlit as st
 
+from inference import classify_ma, get_word_attn, infer_topic
 from visualization import heatmap, html_hext
 
 ID2CAT = {
@@ -35,13 +33,17 @@ if st.button("判定", key="run"):
     else:
         st.markdown(attention_text)
         st.divider()
-        random_id = random.randint(0, 1)  # TODO: make dummy data
-        st.markdown(f"判定結果: **{ID2CAT[random_id]}**")
-        if random_id == 1:
-            rng = np.random.default_rng()  # TODO: make dummy data
-            html_hext_result = html_hext(((f"単語{i}", rng.random()) for i in range(7)))  # TODO: make dummy data
+
+        pred_class, input_ids, attention_list = classify_ma(user_input)
+        st.markdown(f"判定結果: **{ID2CAT[pred_class]}**")
+        if pred_class == 1:
+            topic_dist, ll = infer_topic(user_input)
+            
+            words_atten = get_word_attn(input_ids, attention_list)
+            html_hext_result = html_hext(((word, attn) for word, attn in words_atten)) 
             st.markdown(html_hext_result, unsafe_allow_html=True)
-            data = rng.random((10, 1)).reshape(-1, 1)  # TODO: make dummy data
+
+            data = topic_dist.reshape(-1, 1)
             st.plotly_chart(heatmap(data), use_container_width=True)
 
 

requirements.txt

@@ -2,3 +2,13 @@ streamlit
 numpy
 pandas
 plotly
+transformers
+scipy
+torch
+fugashi
+unidic-lite
+sudachipy
+sudachidict_full
+sudachidict_core
+tomotopy
+