add opencc

app.py

@@ -3,6 +3,10 @@ import gradio as gr
 from gradio import update
 from functools import lru_cache
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from opencc import OpenCC  # 用於簡體轉繁體
+
+# 初始化簡體到繁體轉換器
+cc = OpenCC('s2t')
 
 # 可選模型列表
 MODEL_LIST = [
@@ -23,14 +27,16 @@ MODEL_LIST = [
 @lru_cache(maxsize=None)
 def get_pipeline(model_name):
     tok = AutoTokenizer.from_pretrained(model_name)
-    mdl = AutoModelForCausalLM.from_pretrained(model_name, weights_only=False, trust_remote_code=True)
+    mdl = AutoModelForCausalLM.from_pretrained(
+        model_name, weights_only=False, trust_remote_code=True
+    )
     mdl.to("cuda")
     return pipeline("text-generation", model=mdl, tokenizer=tok, device=0)
 
 @spaces.GPU
 def suggest_next(text, model_name, k, m):
     """
-    使用 Beam Search 產生 M 條最可能的下段建議，並一次更新候選列表。
+    使用 Beam Search 產生 M 條最可能的下段建議，並一次更新候選列表，最後將簡體字轉為繁體字。
     """
     gen_pipe = get_pipeline(model_name)
     outs = gen_pipe(
@@ -41,10 +47,12 @@ def suggest_next(text, model_name, k, m):
         do_sample=False,
         early_stopping=True
     )
+    # 提取並清理生成內容
     suggestions = [out["generated_text"][len(text):].strip() for out in outs]
     suggestions = [s for s in suggestions if s]
+    # 簡體轉繁體
+    suggestions = [cc.convert(s) for s in suggestions]
 
-    # 更新候選條
     return update(choices=suggestions, value=None)
 
 def append_suggestion(current, choice):
@@ -53,7 +61,7 @@ def append_suggestion(current, choice):
     # 模擬輸入法候選選中
     return current + choice
 
-# 自定義 CSS：模擬經典中文輸入法候選欄樣式
+# 自訂 CSS：模擬經典中文輸入法候選欄樣式
 custom_css = """
 #suggestions-bar .candidate-list {
     display: flex;
@@ -83,7 +91,7 @@ custom_css = """
 with gr.Blocks(css=custom_css) as demo:
     # 標題和說明
     gr.Markdown(
-        "## 🇹🇼 台灣中文輸入法加速器  \n"
+        "## 🇹🇼 繁體中文輸入法加速器  \n"        
         "結合小型語言模型與 ZeroGPU，即時 IME 風格候選條。"
     )
 

requirements.txt

@@ -2,4 +2,5 @@ gradio>=5.0.0
 torch>=2.1.2,<2.6.0
 transformers>=4.30.0
 accelerate
-sentencepiece
+sentencepiece
+opencc-python-reimplemented