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app.py

@@ -60,7 +60,7 @@ def knn_get_score(knn, k, cat, vec):
     kscores = scores[sortinds][:k]
     if debug: st.write('kscores.shape', kscores.shape)
     # Get actual sorted similiarity scores
-    ksims = cos_sim_table[:, sortinds][:,:k]
+    ksims = cos_sim_table[np.expand_dims(np.arange(sortinds.shape[0]), axis=1), sortinds]
     if debug: st.write('ksims.shape', ksims.shape)
     # Apply normalization after exponential formula
     ksims = softmax(10**ksims)