Create app.py

app.py

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+import gradio as gr
+from sentence_transformers import SentenceTransformer, util
+from transformers import BertTokenizer, BertModel
+import torch
+from sklearn.metrics.pairwise import cosine_similarity
+
+# Load models for different methods
+st_model = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2')
+bert_model_name = "bert-base-chinese"
+tokenizer = BertTokenizer.from_pretrained(bert_model_name)
+bert_model = BertModel.from_pretrained(bert_model_name)
+
+def calculate_similarity(method, sentence1, sentence2):
+    if method == "Sentence Transformers":
+        embedding1 = st_model.encode(sentence1, convert_to_tensor=True)
+        embedding2 = st_model.encode(sentence2, convert_to_tensor=True)
+        similarity = util.cos_sim(embedding1, embedding2).item()
+    elif method == "BERT CLS":
+        inputs1 = tokenizer(sentence1, return_tensors="pt", truncation=True, padding=True)
+        inputs2 = tokenizer(sentence2, return_tensors="pt", truncation=True, padding=True)
+        with torch.no_grad():
+            outputs1 = bert_model(**inputs1)
+            outputs2 = bert_model(**inputs2)
+        cls_embedding1 = outputs1.last_hidden_state[:, 0, :].numpy()
+        cls_embedding2 = outputs2.last_hidden_state[:, 0, :].numpy()
+        similarity = cosine_similarity(cls_embedding1, cls_embedding2)[0][0]
+    else:
+        similarity = "未選擇演算法"
+    return similarity
+
+def load_example():
+    return "今天的天氣真好", "今天天氣非常晴朗"
+
+# Gradio UI
+def build_ui():
+    with gr.Blocks() as demo:
+        gr.Markdown("## 中文句子相似度計算 Demo")
+        
+        with gr.Row():
+            sentence1_input = gr.Textbox(label="句子 1", placeholder="輸入第一個句子")
+            sentence2_input = gr.Textbox(label="句子 2", placeholder="輸入第二個句子")
+        
+        method_selector = gr.Radio(choices=["Sentence Transformers", "BERT CLS"], label="選擇演算法")
+        
+        similarity_output = gr.Textbox(label="相似度結果", interactive=False)
+        
+        with gr.Row():
+            calculate_button = gr.Button("計算相似度")
+            example_button = gr.Button("填入預設句子")
+        
+        calculate_button.click(calculate_similarity, 
+                               inputs=[method_selector, sentence1_input, sentence2_input], 
+                               outputs=similarity_output)
+        
+        example_button.click(load_example, 
+                             inputs=[], 
+                             outputs=[sentence1_input, sentence2_input])
+        
+    return demo
+
+# Launch the app
+demo = build_ui()
+demo.launch()