Update app.py

app.py

@@ -9,6 +9,10 @@ import random
 import os
 from huggingface_hub import InferenceClient
 from fpdf import FPDF
+from transformers import pipeline
+import torch
+from diffusers import StableDiffusionXLPipeline
+import uuid
 
 def setup_session():
     try:
@@ -506,6 +510,63 @@ def update_prompts_and_description(category, style):
     style_description = get_style_description(style)
     return style_description
 
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "SG161222/RealVisXL_V4.0",
+    torch_dtype=torch.float16,
+    use_safetensors=True,
+    add_watermarker=False,
+    variant="fp16"
+).to(device)
+
+def generate_image(prompt: str):
+    # 한글 입력 감지 및 번역
+    if any('\uac00' <= char <= '\ud7a3' for char in prompt):
+        translated = translator(prompt, max_length=512)
+        prompt = translated[0]['translation_text']
+    
+    # Hi-res와 3840x2160 스타일 적용
+    prompt = f"hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic"
+    
+    # 고정된 설정값
+    negative_prompt = "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly, (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, disgusting, amputation"
+    width = 1024
+    height = 1024
+    guidance_scale = 6
+    num_inference_steps = 100
+    seed = random.randint(0, 2**32 - 1)
+    generator = torch.Generator().manual_seed(seed)
+    
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        width=width,
+        height=height,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
+        generator=generator,
+    ).images[0]
+    
+    unique_name = str(uuid.uuid4()) + ".png"
+    image.save(unique_name)
+    return unique_name
+
+def generate_images(blog_post):
+    images = []
+    lines = blog_post.split('\n')
+    for i in range(5):
+        if i < len(lines):
+            prompt = lines[i]
+        else:
+            prompt = random.choice(lines)
+        image_path = generate_image(prompt)
+        images.append(image_path)
+    return images
+
+
 with gr.Blocks() as demo:
     gr.Markdown(f"# {title}")
     
@@ -566,4 +627,22 @@ with gr.Blocks() as demo:
     category.change(fn=update_prompts_and_description, inputs=[category, style], outputs=[style_description])
     style.change(fn=update_prompts_and_description, inputs=[category, style], outputs=[style_description])    
 
+    # 이미지 생성 버튼 및 출력 추가
+    generate_images_btn = gr.Button("이미지 생성하기")
+    image_outputs = [gr.Image(label=f"생성된 이미지 {i+1}") for i in range(5)]
+
+    generate_images_btn.click(
+        fn=generate_images,
+        inputs=[output],
+        outputs=image_outputs
+    )
+
+    save_pdf_btn = gr.Button("PDF로 저장하기")
+    pdf_output = gr.File(label="생성된 PDF 파일")
+
+    save_pdf_btn.click(fn=save_content_to_pdf, inputs=[output], outputs=[pdf_output])
+
+    category.change(fn=update_prompts_and_description, inputs=[category, style], outputs=[style_description])
+    style.change(fn=update_prompts_and_description, inputs=[category, style], outputs=[style_description])    
+
 demo.launch()