Update app.py

app.py

@@ -2,14 +2,18 @@ import gradio as gr
 import numpy as np
 import librosa
 from transformers import pipeline
-import torch
 from datetime import datetime
 import os
 import requests
 
+# 환경변수에서 토큰 가져오기
+HF_API_TOKEN = os.getenv("HF_API_TOKEN")
+if not HF_API_TOKEN:
+    raise ValueError("HF_API_TOKEN not found in environment variables")
+
 # Inference API 설정
 API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
-headers = {"Authorization": "Bearer hf_..."}  # 여기에 HuggingFace 토큰 입력
+headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
 
 # AI 모델 초기화
 speech_recognizer = pipeline(
@@ -26,27 +30,40 @@ text_analyzer = pipeline(
 )
 korean_sentiment = pipeline(
     "text-classification",
-    model="searle-j/korean_sentiment_analysis"  # 한국어 감정 분석 모델
+    model="searle-j/korean_sentiment_analysis"
 )
 
 def generate_image_from_prompt(prompt):
-    """HuggingFace Inference API를 통한 이미지 생성"""
+    """이미지 생성 함수"""
+    print(f"Generating image with prompt: {prompt}")  # 디버깅용
     try:
-        response = requests.post(API_URL, headers=headers, json={
-            "inputs": prompt,
-            "parameters": {
-                "negative_prompt": "ugly, blurry, poor quality, distorted",
-                "num_inference_steps": 30,
-                "guidance_scale": 7.5
+        if not prompt:
+            print("No prompt provided")
+            return None
+            
+        response = requests.post(
+            API_URL,
+            headers=headers,
+            json={
+                "inputs": prompt,
+                "parameters": {
+                    "negative_prompt": "ugly, blurry, poor quality, distorted",
+                    "num_inference_steps": 30,
+                    "guidance_scale": 7.5
+                }
             }
-        })
+        )
         
         if response.status_code == 200:
+            print("Image generated successfully")
             return response.content
         else:
+            print(f"Error: {response.status_code}")
+            print(f"Response: {response.text}")
             return None
+            
     except Exception as e:
-        print(f"Error generating image: {e}")
+        print(f"Error generating image: {str(e)}")
         return None
 
 def create_interface():
@@ -283,11 +300,12 @@ def generate_detailed_prompt(text, voice_emotion, text_sentiment, acoustic_featu
         generate_btn.click(
             fn=generate_image_from_prompt,
             inputs=[final_prompt],
-            outputs=[result_image]
+            outputs=[result_image],
+            api_name="generate_image"  # API 이름 지정
         )
 
         return app
 
 if __name__ == "__main__":
     demo = create_interface()
-    demo.launch()
+    demo.launch(debug=True)  # 디버그 모드 활성화