Update app.py

app.py

@@ -1,6 +1,6 @@
 import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor
+from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
+from transformers import pipeline
 from datasets import load_dataset
 import spacy
 import gradio as gr
@@ -26,6 +26,8 @@ whisper_pipe = pipeline(
 )
 
 # DeepSeek-V3 模型初始化（文本生成）
+deepseek_pipe = None  # 預設值，以防模型加載失敗
+
 try:
     deepseek_pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-V3", trust_remote_code=True)
 except Exception as e:
@@ -34,13 +36,12 @@ except Exception as e:
 # spaCy 初始化（文本分類與標籤）
 nlp = spacy.load("en_core_web_sm")
 
-# 定義處理函數
 def process_audio(audio_file):
     # 語音轉文字
     result = whisper_pipe(audio_file)["text"]
     
     # 使用 DeepSeek 生成回應（如果成功加載模型）
-    try:
+    if deepseek_pipe is not None:
         messages = [{"role": "user", "content": result}]
         deepseek_response = deepseek_pipe(messages)[0]["generated_text"]
         
@@ -48,24 +49,10 @@ def process_audio(audio_file):
         doc = nlp(deepseek_response)
         entities = [(ent.text, ent.label_) for ent in doc.ents]
         
-        return result, deepseek_response, entities
-    
-    except Exception as e:
-        return result, f"錯誤：無法生成回應 - {e}", []
-
-# Gradio 界面設計
-def interface(audio_file):
-    transcription_result_list  # 將結果包裝為字典以適應 Gradio 輸出格式
-    
-    try:
-        transcription_result_list  # 這裡需要修改以適應新的返回格式
-        
-        transcription_result_dict  # 這裡需要修改以適應新的返回格式
-        
         return {
-            "Transcription (Whisper)": transcription_result_dict["Transcription (Whisper)"],
-            "AI Response (DeepSeek)": transcription_result_dict["AI Response (DeepSeek)"],
-            "Extracted Entities (spaCy)": transcription_result_dict["Extracted Entities (spaCy)"],
+            "Transcription (Whisper)": result,
+            "AI Response (DeepSeek)": deepseek_response,
+            "Extracted Entities (spaCy)": entities,
             
             }
     
@@ -90,9 +77,4 @@ with gr.Blocks() as app:
        audio_input=gr.Audio(source="microphone", type="filepath", label="上傳語音")
        output_text=gr.JSON(label="結果")
        
-   submit_button=gr.Button("提交") 
-   submit_button.click(fn=lambda x: process_audio(x), inputs=[audio_input], outputs=[output_text])
-   
-
-if __name__ == "__main__":
-     app.launch()
+   submit_button=gr.Button("