init

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-from sentence_transformers import SentenceTransformer, util
+from sentence_transformers import SentenceTransformer, torch_util
 
 def app():
     # 创建Streamlit应用程序
@@ -31,6 +31,7 @@ def app():
             st.session_state.inputs_index += 1
     
     button_generate = st.button("计算")
+    button_clear = st.button("清空")
 
     def transformer(sentences):
         model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2', device="cpu")
@@ -40,7 +41,7 @@ def app():
 
         for sent in sentences:
             sent_emb = model.encode(sent, convert_to_tensor=True)
-            cosine_scores = util.cosine_similarity(source_emb, sent_emb)
+            cosine_scores = torch_util.pairwise_cosine_similarity(source_emb, sent_emb)
             cosin_dict[sent] = cosine_scores
         
         sorted_dict = dict(sorted(cosin_dict.items(), key=lambda item: item[1],reverse = True))
@@ -55,6 +56,13 @@ def app():
         st.write(embeddings)
         #output_text.success(generated_text)
 
+    if button_clear:
+        for i in st.session_state.inputs:
+            del st.session_state.inputs[i]
+        st.session_state.inputs.clear()
+        del(st.session_state, "inputs")
+        st.session_state.inputs_index = 0
+
 if __name__ == "__main__":
     # 运行应用程序
     app()