Update app.py

app.py

@@ -2,31 +2,38 @@ import gradio as gr
 from gradio_client import Client
 import os
 import logging
-from PIL import Image
-import io
-import requests  # 이 줄을 추가합니다
+import requests
 
 # 로깅 설정
-logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.INFO)
 
 # API 클라이언트 설정
 api_client = Client("http://211.233.58.202:7960/")
 
-# Webhook URL
-WEBHOOK_URL = "https://connect.pabbly.com/workflow/sendwebhookdata/IjU3NjUwNTY0MDYzMTA0MzE1MjZlNTUzYzUxM2Ei_pc"
-
+# Zapier 웹훅 URL
+WEBHOOK_URL = "https://hooks.zapier.com/hooks/catch/14523965/264pyhj/"
 
+def send_to_webhook(prompt, image_url):
+    payload = {
+        "prompt": prompt,
+        "image_url": image_url
+    }
+    try:
+        response = requests.post(WEBHOOK_URL, json=payload)
+        response.raise_for_status()
+        logging.info(f"Successfully sent data to webhook. Status code: {response.status_code}")
+    except requests.exceptions.RequestException as e:
+        logging.error(f"Failed to send data to webhook: {e}")
 
-def generate_image(prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-    logger.info(f"Received message: {prompt}, seed: {seed}, randomize_seed: {randomize_seed}, "
+def respond(message, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
+    logging.info(f"Received message: {message}, seed: {seed}, randomize_seed: {randomize_seed}, "
                  f"width: {width}, height: {height}, guidance_scale: {guidance_scale}, "
                  f"num_inference_steps: {num_inference_steps}")
     
     try:
         # 이미지 생성 요청
         result = api_client.predict(
-            prompt=prompt,
+            prompt=message,
             seed=seed,
             randomize_seed=randomize_seed,
             width=width,
@@ -35,60 +42,25 @@ def generate_image(prompt, seed, randomize_seed, width, height, guidance_scale,
             num_inference_steps=num_inference_steps,
             api_name="/infer_t2i"
         )
-        logger.info("API response received: %s", result)
+        logging.info("API response received: %s", result)
         
         # 결과 확인 및 처리
-        if isinstance(result, tuple) and len(result) == 3:
-            image_path, used_seed, translated_prompt = result
-            logger.info(f"Image generated at: {image_path}")
-            logger.info(f"Used seed: {used_seed}")
-            logger.info(f"Translated prompt: {translated_prompt}")
+        if isinstance(result, tuple) and len(result) >= 1:
+            image_path = result[0]
+            # 이미지 URL 생성 (실제 서버 URL로 변경 필요)
+            image_url = f"http://211.233.58.202:7960/file={image_path}"
             
-            # 이미지 파일을 열어서 PIL Image 객체로 변환
-            with Image.open(image_path) as img:
-                # 이미지를 메모리에 저장
-                img_byte_arr = io.BytesIO()
-                img.save(img_byte_arr, format='PNG')
-                img_byte_arr = img_byte_arr.getvalue()
+            # 웹훅으로 데이터 전송
+            send_to_webhook(message, image_url)
             
-            return img_byte_arr, used_seed, translated_prompt
+            return image_url
         else:
             raise ValueError("Unexpected API response format")
     except Exception as e:
-        logger.error("Error during API request: %s", str(e), exc_info=True)
+        logging.error("Error during API request: %s", str(e))
         return "Failed to generate image due to an error."
 
 
-
-def send_to_webhook(prompt, image_url):
-    payload = {
-        "prompt": prompt,
-        "image": image_url
-    }
-    try:
-        response = requests.post(WEBHOOK_URL, json=payload)
-        response.raise_for_status()
-        logger.info(f"Successfully sent data to webhook. Status code: {response.status_code}")
-    except requests.exceptions.RequestException as e:
-        logger.error(f"Failed to send data to webhook: {e}")
-
-def respond(message, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-    image_data, used_seed, translated_prompt = generate_image(message, seed, randomize_seed, width, height, guidance_scale, num_inference_steps)
-    
-    if isinstance(image_data, bytes):
-        # 이미지 데이터를 PIL Image 객체로 변환
-        image = Image.open(io.BytesIO(image_data))
-        
-        # 이미지 URL 생성 (실제 환경에 맞게 수정 필요)
-        image_url = f"http://your_server_url/images/{used_seed}.png"
-        
-        # Webhook 호출
-        send_to_webhook(message, image_url)
-        
-        return image, f"Used seed: {used_seed}, Translated prompt: {translated_prompt}"
-    else:
-        return image_data, "Error occurred"
-
 css = """
 footer {
     visibility: hidden;
@@ -123,13 +95,13 @@ examples = [
 
 def use_prompt(prompt):
     return prompt
+
 with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
-    gr.Markdown("# Image Generation")
+
     
     with gr.Row():
         input_text = gr.Textbox(label="Enter your prompt for image generation")
         output_image = gr.Image(label="Generated Image")
-        output_text = gr.Textbox(label="Image Info")
     
     with gr.Row():
         seed = gr.Slider(minimum=0, maximum=1000000, step=1, label="Seed", value=123)
@@ -143,19 +115,25 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
         guidance_scale = gr.Slider(minimum=1, maximum=20, step=0.1, label="Guidance Scale", value=5)
         num_inference_steps = gr.Slider(minimum=1, maximum=100, step=1, label="Number of Inference Steps", value=28)
     
+    with gr.Row():
+        for prompt, image_file in examples:
+            with gr.Column():
+                gr.Image(image_file, label=prompt[:50] + "...")  # 프롬프트의 처음 50자만 표시
+                gr.Button("Use this prompt").click(
+                    fn=use_prompt,
+                    inputs=[],
+                    outputs=input_text,
+                    api_name=False
+                ).then(
+                    lambda x=prompt: x,
+                    inputs=[],
+                    outputs=input_text
+                )
+    
     input_text.submit(
         fn=respond, 
         inputs=[input_text, seed, randomize_seed, width, height, guidance_scale, num_inference_steps], 
-        outputs=[output_image, output_text]
-    )
-
-    # Examples 섹션 추가
-    gr.Examples(
-        examples=[[ex[0]] for ex in examples],  # 프롬프트만 사용
-        inputs=input_text,
-        outputs=[output_image, output_text],
-        fn=respond,
-        cache_examples=False
+        outputs=output_image
     )
 
 if __name__ == "__main__":