Update app.py

app.py

@@ -24,14 +24,6 @@ text_analyzer = pipeline(
     model="nlptown/bert-base-multilingual-uncased-sentiment"
 )
 
-def create_interface():
-    with gr.Blocks(theme=gr.themes.Soft()) as app:
-        state = gr.State({
-            "user_name": "",
-            "reflections": [],
-            "voice_analysis": None,
-            "final_prompt": ""
-        })
 def generate_image_from_prompt(prompt):
     """HuggingFace Inference API를 통한 이미지 생성"""
     try:
@@ -45,14 +37,21 @@ def generate_image_from_prompt(prompt):
         })
         
         if response.status_code == 200:
-            return response.content  # 바이너리 이미지 데이터 반환
+            return response.content
         else:
             return None
     except Exception as e:
         print(f"Error generating image: {e}")
         return None
 
-
+def create_interface():
+    with gr.Blocks(theme=gr.themes.Soft()) as app:
+        state = gr.State({
+            "user_name": "",
+            "reflections": [],
+            "voice_analysis": None,
+            "final_prompt": ""
+        })
 
         # 헤더
         header = gr.Markdown("# 디지털 굿판")
@@ -68,7 +67,6 @@ def generate_image_from_prompt(prompt):
             # 청신
             with gr.Tab("청신"):
                 with gr.Row():
-                    # 절대 경로로 변경
                     audio_path = os.path.abspath(os.path.join("assets", "main_music.mp3"))
                     audio = gr.Audio(
                         value=audio_path,
@@ -116,26 +114,20 @@ def generate_image_from_prompt(prompt):
                         )
                         analyze_btn = gr.Button("분석하기")
 
-   # 이벤트 핸들러 추가
-generate_btn.click(
-    fn=generate_image_from_prompt,
-    inputs=[final_prompt],
-    outputs=[result_image]
-)    
-# 송신 탭 부분 수정
-with gr.Tab("송신"):
-    gr.Markdown("## 송신 - 시각화 결과")
-    with gr.Column():
-        final_prompt = gr.Textbox(
-            label="생성된 프롬프트",
-            interactive=False,
-            lines=3
-        )
-        generate_btn = gr.Button("이미지 생성하기")
-        result_image = gr.Image(
-            label="생성된 이미지",
-            type="pil"
-        )
+            # 송신
+            with gr.Tab("송신"):
+                gr.Markdown("## 송신 - 시각화 결과")
+                with gr.Column():
+                    final_prompt = gr.Textbox(
+                        label="생성된 프롬프트",
+                        interactive=False,
+                        lines=3
+                    )
+                    generate_btn = gr.Button("이미지 생성하기")
+                    result_image = gr.Image(
+                        label="생성된 이미지",
+                        type="pil"
+                    )
 
         def clear_voice_input():
             """음성 입력 초기화"""
@@ -147,18 +139,11 @@ with gr.Tab("송신"):
                 return state, "음성을 먼저 녹음해주세요.", "", "", ""
             
             try:
-                # 오디오 로드
                 y, sr = librosa.load(audio_path, sr=16000)
-                
-                # 음성 인식
                 transcription = speech_recognizer(y)
                 text = transcription["text"]
-                
-                # 감정 분석
                 voice_emotions = emotion_classifier(y)
                 text_sentiment = text_analyzer(text)[0]
-
-                # 프롬프트 생성
                 prompt = generate_prompt(text, voice_emotions[0], text_sentiment)
                 
                 return (
@@ -227,7 +212,13 @@ with gr.Tab("송신"):
             outputs=[state, transcribed_text, voice_emotion, text_emotion, final_prompt]
         )
 
-    return app
+        generate_btn.click(
+            fn=generate_image_from_prompt,
+            inputs=[final_prompt],
+            outputs=[result_image]
+        )
+
+        return app
 
 if __name__ == "__main__":
     demo = create_interface()