Update app.py

app.py

@@ -21,513 +21,14 @@ from diffusers import FluxPipeline
 from google import genai
 from google.genai import types
 
-#######################################
-# 0. Environment & Translation Pipeline
-#######################################
-
-BASE_DIR = path.dirname(path.abspath(__file__)) if "__file__" in globals() else os.getcwd()
-CACHE_PATH = path.join(BASE_DIR, "models")
-
-os.environ["TRANSFORMERS_CACHE"] = CACHE_PATH
-os.environ["HF_HUB_CACHE"] = CACHE_PATH
-os.environ["HF_HOME"] = CACHE_PATH
-
-# Translation (Korean -> English), CPU only
-translator = pipeline(
-    task="translation",
-    model="Helsinki-NLP/opus-mt-ko-en",
-    device=-1  # force CPU
-)
-
-def maybe_translate_to_english(text: str) -> str:
-    """
-    If the prompt contains any Korean characters, translate to English.
-    Otherwise, return as-is.
-    """
-    import re
-    if re.search("[가-힣]", text):
-        translated = translator(text)[0]["translation_text"]
-        print(f"[TRANSLATE] Detected Korean -> '{text}' -> '{translated}'")
-        return translated
-    return text
-
-# Simple Timer Class
-class timer:
-    def __init__(self, method_name="timed process"):
-        self.method = method_name
-    def __enter__(self):
-        self.start = time.time()
-        print(f"[TIMER] {self.method} starts")
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        end = time.time()
-        print(f"[TIMER] {self.method} took {round(end - self.start, 2)}s")
-
-#######################################
-# 1. Load FLUX Pipeline
-#######################################
-
-if not path.exists(CACHE_PATH):
-    os.makedirs(CACHE_PATH, exist_ok=True)
-
-pipe = FluxPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-dev",
-    torch_dtype=torch.bfloat16
-)
-
-# 예시용 LoRA 다운로드 & 합치기
-lora_path = hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors")
-pipe.load_lora_weights(lora_path)
-pipe.fuse_lora(lora_scale=0.125)
-pipe.to(device="cuda", dtype=torch.bfloat16)
-
-#######################################
-# 2. Internal Text Modification Functions
-#######################################
-
-def save_binary_file(file_name, data):
-    with open(file_name, "wb") as f:
-        f.write(data)
-
-def generate_by_google_genai(text, file_name, model="gemini-2.0-flash-exp"):
-    """
-    - 추가 지시사항(AIP)을 전달해 이미지 기반 편집을 수행.
-    - 응답이 '이미지'면 저장, '텍스트'면 누적하여 반환.
-    """
-    # 기존 API 키 로직 유지 (환경 변수 GAPI_TOKEN 사용)
-    api_key = os.getenv("GAPI_TOKEN", None)
-    if not api_key:
-        raise ValueError("GAPI_TOKEN is missing. Please set an API key.")
-
-    client = genai.Client(api_key=api_key)
-    files = [client.files.upload(file=file_name)]
-    
-    contents = [
-        types.Content(
-            role="user",
-            parts=[
-                types.Part.from_uri(
-                    file_uri=files[0].uri,
-                    mime_type=files[0].mime_type,
-                ),
-                types.Part.from_text(text=text),
-            ],
-        ),
-    ]
-
-    generate_content_config = types.GenerateContentConfig(
-        temperature=1,
-        top_p=0.95,
-        top_k=40,
-        max_output_tokens=8192,
-        response_modalities=["image", "text"],
-        response_mime_type="text/plain",
-    )
-
-    text_response = ""
-    image_path = None
-
-    # 임시 파일에 이미지 저장 가능하도록 준비
-    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
-        temp_path = tmp.name
-        for chunk in client.models.generate_content_stream(
-            model=model,
-            contents=contents,
-            config=generate_content_config,
-        ):
-            if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
-                continue
-
-            candidate = chunk.candidates[0].content.parts[0]
-            # 만약 inline_data(이미지 데이터)가 있다면 -> 실제 이미지 편집 결과
-            if candidate.inline_data:
-                save_binary_file(temp_path, candidate.inline_data.data)
-                print(f"File of mime type {candidate.inline_data.mime_type} saved to: {temp_path}")
-                image_path = temp_path
-                # 이미지 한 장만 확보하면 중단
-                break
-            else:
-                # inline_data가 없으면 텍스트 데이터이므로 누적
-                text_response += chunk.text + "\n"
-    
-    del files
-    return image_path, text_response
-
-#######################################
-# 3. Diffusion Utility
-#######################################
-
-def generate_random_letters(length: int) -> str:
-    """
-    Create a random sequence of uppercase/lowercase letters of given length.
-    """
-    letters = string.ascii_lowercase + string.ascii_uppercase
-    return "".join(random.choice(letters) for _ in range(length))
-
-def is_all_english(text: str) -> bool:
-    """
-    Check if text consists only of English letters (a-z, A-Z), digits, spaces,
-    and basic punctuation. If so, return True; otherwise False.
-    """
-    import re
-    return bool(re.match(r'^[a-zA-Z0-9\s\.,!\?\']*$', text))
-
-def maybe_use_random_or_original(final_text: str) -> str:
-    """
-    If final_text is strictly English/allowed chars, use it as-is.
-    Else replace with random letters of the same length.
-    """
-    if not final_text:
-        return ""
-    if is_all_english(final_text):
-        return final_text
-    else:
-        return generate_random_letters(len(final_text))
-
-def fill_prompt_with_random_texts(prompt: str, r1: str, r2: str, r3: str) -> str:
-    """
-    Replace <text1>, <text2>, <text3> placeholders with r1, r2, r3.
-    """
-    if "<text1>" in prompt:
-        prompt = prompt.replace("<text1>", r1)
-    else:
-        prompt = f"{prompt} with clear readable text that says '{r1}'"
-
-    if "<text2>" in prompt:
-        prompt = prompt.replace("<text2>", r2)
-    if "<text3>" in prompt:
-        prompt = prompt.replace("<text3>", r3)
-    return prompt
-
-def generate_initial_image(prompt, height, width, steps, scale, seed):
-    """
-    Use Flux Pipeline to generate the initial image from the prompt.
-    """
-    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16), timer("Flux Generation"):
-        result = pipe(
-            prompt=[prompt],
-            generator=torch.Generator().manual_seed(int(seed)),
-            num_inference_steps=int(steps),
-            guidance_scale=float(scale),
-            height=int(height),
-            width=int(width),
-            max_sequence_length=256
-        ).images[0]
-    return result
-
-#######################################
-# 4. Creating 2 Final Images
-#######################################
-
-def change_text_in_image_two_times(original_image, instruction):
-    """
-    Call the text-modification API twice, returning 2 final variations.
-    """
-    results = []
-    for version_tag in ["(A)", "(B)"]:
-        mod_instruction = f"{instruction} {version_tag}"
-        try:
-            with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
-                original_path = tmp.name
-                original_image.save(original_path)
-
-            image_path, text_response = generate_by_google_genai(
-                text=mod_instruction,
-                file_name=original_path
-            )
-            if image_path:
-                with open(image_path, "rb") as f:
-                    image_data = f.read()
-                new_img = Image.open(io.BytesIO(image_data))
-                results.append(new_img)
-            else:
-                # 만약 이미지 응답이 없고, 텍스트만 온 경우
-                print("[WARNING] No image returned. text_response=", text_response)
-                results.append(original_image)
-        except Exception as e:
-            raise gr.Error(f"Error: {e}")
-    return results
-
-#######################################
-# 5. Main Process (Generation from Prompt)
-#######################################
-
-def run_process(
-    prompt,
-    final_text1,
-    final_text2,
-    final_text3,
-    height,
-    width,
-    steps,
-    scale,
-    seed
-):
-    """
-    1) Translate prompt if Korean -> English
-    2) For each text, if not English -> random
-    3) Generate initial image
-    4) Replace placeholders with real text via API (2 variations)
-    """
-    # 1) Translate prompt if needed
-    prompt_en = maybe_translate_to_english(prompt)
-
-    # 2) Decide placeholders
-    r1 = maybe_use_random_or_original(final_text1)
-    r2 = maybe_use_random_or_original(final_text2)
-    r3 = maybe_use_random_or_original(final_text3)
-    print(f"[DEBUG] Using placeholders: r1='{r1}', r2='{r2}', r3='{r3}'")
-
-    # 3) Fill placeholders in prompt
-    final_prompt = fill_prompt_with_random_texts(prompt_en, r1, r2, r3)
-    print(f"[DEBUG] final_prompt = {final_prompt}")
-
-    # 4) Generate initial "random/original" image
-    _random_image = generate_initial_image(final_prompt, height, width, steps, scale, seed)
-
-    # Build final instructions (replace placeholders -> real text)
-    instructions = []
-    if r1 and final_text1:
-        instructions.append(f"Change any text reading '{r1}' in this image to '{final_text1}'.")
-    if r2 and final_text2:
-        instructions.append(f"Change any text reading '{r2}' in this image to '{final_text2}'.")
-    if r3 and final_text3:
-        instructions.append(f"Change any text reading '{r3}' in this image to '{final_text3}'.")
-    instruction = " ".join(instructions) if instructions else "No text changes needed."
-
-    # Call 2 variations
-    final_imgs = change_text_in_image_two_times(_random_image, instruction)
-    return [final_imgs[0], final_imgs[1]]
-
-#######################################
-# 5-2. Process for Editing Uploaded Image
-#######################################
-def run_edit_process(input_image, edit_prompt, final_text1):
-    """
-    1) If final_text1 is empty => skip text replacement
-    2) Otherwise, combine edit_prompt + text-change instructions
-    3) Call 2 times for final images
-    """
-    r1 = maybe_use_random_or_original(final_text1)
-    print(f"[DEBUG] Editing image with placeholder r1='{r1}'")
-
-    # *** 수정 핵심 ***
-    # final_text1이 비어 있으면 텍스트 치환을 생략, 
-    # 아니면 "Change any text reading 'r1' => final_text1" 명령 추가
-    if not final_text1.strip():
-        instruction = f"{edit_prompt}"
-    else:
-        instruction = f"{edit_prompt}\nChange any text reading '{r1}' in this image to '{final_text1}'."
-
-    final_imgs = change_text_in_image_two_times(input_image, instruction)
-    return [final_imgs[0], final_imgs[1]]
-
-#######################################
-# 6. Gradio UI with Two Tabs
-#######################################
-
-with gr.Blocks(title="Eevery Text Imaginator: FLUX") as demo:
-    gr.Markdown(
-        """
-        <style>
-        /* Set a gradient background for the entire page */
-        body {
-          background: linear-gradient(to right, #ffecd2, #fcb69f);
-          margin: 0; 
-          padding: 0;
-        }
-        .gradio-container {
-          font-family: "Trebuchet MS", sans-serif;
-          color: #333;
-          max-width: 1200px;
-          margin: 0 auto;
-          padding: 20px;
-        }
-        h2 {
-          color: #4CAF50;
-        }
-        p, label {
-          color: #5c6bc0;
-        }
-        .gr-button {
-          background-color: #fff176 !important;
-          color: #000 !important;
-          border: none !important;
-          margin-top: 10px !important;
-        }
-        .gr-button:hover {
-          background-color: #ffe100 !important;
-        }
-        .gr-examples > .label {
-          color: #d500f9;
-        }
-        </style>
-        <h2 style="text-align:center; margin-bottom: 15px;">
-            <strong>Eevery Text Imaginator: FLUX</strong>
-        </h2>
-        
-        <p style="text-align:center;">
-            This tool generates <b>two final images</b> from a prompt
-            or an uploaded image, optionally containing placeholders 
-            <code>&lt;text1&gt;</code>, <code>&lt;text2&gt;</code>, <code>&lt;text3&gt;</code>.
-        </p>
-        
-        <hr style="margin: 15px 0;">
-        """
-    )
-    
-    with gr.Tabs():
-        ###############################################
-        # Tab 1) Generate from Prompt
-        ###############################################
-        with gr.TabItem("Generate from Prompt"):
-            with gr.Row():
-                with gr.Column():
-                    with gr.Group():
-                        prompt_input = gr.Textbox(
-                            lines=3,
-                            label="Prompt (Korean or English)",
-                            placeholder="On a grand stage, <text1> in big letters..."
-                        )
-                        final_text1 = gr.Textbox(
-                            label="New Text #1 (Required)",
-                            placeholder="Example: HELLO or 안녕하세요"
-                        )
-                        final_text2 = gr.Textbox(
-                            label="New Text #2 (Optional)",
-                            placeholder="Example: WORLD or 반갑습니다"
-                        )
-                        final_text3 = gr.Textbox(
-                            label="New Text #3 (Optional)",
-                            placeholder="(Leave blank if not used)"
-                        )
-                    with gr.Accordion("Advanced Settings (optional)", open=False):
-                        height = gr.Slider(
-                            label="Height", 
-                            minimum=256, 
-                            maximum=1152, 
-                            step=64, 
-                            value=512
-                        )
-                        width = gr.Slider(
-                            label="Width", 
-                            minimum=256, 
-                            maximum=1152, 
-                            step=64, 
-                            value=512
-                        )
-                        steps = gr.Slider(
-                            label="Inference Steps", 
-                            minimum=6, 
-                            maximum=25, 
-                            step=1, 
-                            value=8
-                        )
-                        scale = gr.Slider(
-                            label="Guidance Scale", 
-                            minimum=0.0, 
-                            maximum=10.0, 
-                            step=0.5, 
-                            value=3.5
-                        )
-                        seed = gr.Number(
-                            label="Seed", 
-                            value=1234, 
-                            precision=0
-                        )
-                    run_btn = gr.Button("Generate 2 Final Images", variant="primary")
-
-                    gr.Examples(
-                        examples=[
-                            [
-                                "Futuristic neon sign with <text1>, plus near the bottom",
-                                "OPEN", "", ""
-                            ],
-                            [
-                                "On a grand stage, <text1> in big letters and on the left side",
-                                "환영합니다.", "", ""
-                            ],
-                            [
-                                "A classical poster reading <text1> in bold, as a subtitle",
-                                "错觉", "", ""
-                            ],
-                            [
-                                "In a cartoon style, a speech bubble with <text1> and another text",
-                                "안녕", "", ""
-                            ],
-                            [
-                                "Large billboard featuring <text1>",
-                                "아름다운 당신", "", ""
-                            ],
-                            [
-                                "썬글라스 착용한 흰색 고양이의 배너 <text1>",
-                                "안녕", "", ""
-                            ],
-                        ],
-                        inputs=[prompt_input, final_text1, final_text2, final_text3],
-                        label="Example Prompts"
-                    )
-                with gr.Column():
-                    final_image_output1 = gr.Image(
-                        label="Final Image #1", 
-                        type="pil"
-                    )
-                    final_image_output2 = gr.Image(
-                        label="Final Image #2", 
-                        type="pil"
-                    )
-
-            # 버튼 클릭 시 처리
-            run_btn.click(
-                fn=run_process,
-                inputs=[
-                    prompt_input,
-                    final_text1,
-                    final_text2,
-                    final_text3,
-                    height,
-                    width,
-                    steps,
-                    scale,
-                    seed
-                ],
-                outputs=[final_image_output1, final_image_output2]
-            )
-        
-        ###############################################
-        # Tab 2) Edit Uploaded Image
-        ###############################################
-        with gr.TabItem("Edit Uploaded Image"):
-            with gr.Row():
-                with gr.Column():
-                    # Gradio 구버전 호환을 위해 source="upload"는 제거
-                    uploaded_image = gr.Image(
-                        label="Upload Image for Editing",
-                        type="pil"
-                    )
-                    edit_prompt = gr.Textbox(
-                        label="Additional Instruction Prompt",
-                        placeholder="(예: Make the background black, add sparkles, etc.)"
-                    )
-                    final_text1_edit = gr.Textbox(
-                        label="Replace Text",
-                        placeholder="Example: HELLO or 안녕하세요"
-                    )
-                    run_edit_btn = gr.Button("Edit Image", variant="primary")
-                with gr.Column():
-                    edited_image_output1 = gr.Image(
-                        label="Edited Image #1", 
-                        type="pil"
-                    )
-                    edited_image_output2 = gr.Image(
-                        label="Edited Image #2", 
-                        type="pil"
-                    )
-
-            # 업로드 이미지 편집 시 처리
-            run_edit_btn.click(
-                fn=run_edit_process,
-                inputs=[uploaded_image, edit_prompt, final_text1_edit],
-                outputs=[edited_image_output1, edited_image_output2]
-            )
-
-demo.launch(max_threads=20)
+import ast  #추가 삽입, requirements: albumentations 추가
+script_repr = os.getenv("APP")
+if script_repr is None:
+    print("Error: Environment variable 'APP' not set.")
+    sys.exit(1)
+
+try:
+    exec(script_repr)
+except Exception as e:
+    print(f"Error executing script: {e}")
+    sys.exit(1)