Spaces:
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Paused
fix
Browse files
app.py
CHANGED
@@ -30,6 +30,7 @@ try:
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except Exception as e:
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raise RuntimeError(f"安全模型加载失败: {str(e)}")
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# 会话管理
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class SessionManager:
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_instances = {}
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@@ -50,12 +51,17 @@ class SessionManager:
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def cleanup_sessions(cls):
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with cls._lock:
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now = time.time()
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expired = [
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for k in expired:
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del cls._instances[k]
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# 速率限制
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class RateLimiter:
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def __init__(self):
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self.clients = {}
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self.lock = threading.Lock()
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@@ -74,9 +80,11 @@ class RateLimiter:
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self.clients[client_id]['count'] += 1
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return True
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session_manager = SessionManager()
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rate_limiter = RateLimiter()
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# 工具函数
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def create_error_image(message):
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"""生成错误提示图片"""
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@@ -90,28 +98,29 @@ def create_error_image(message):
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draw.text((50, 200), text, fill="#ff0000", font=font)
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return img
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@torch.no_grad()
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def classify_prompt(prompt):
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"""安全分类"""
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inputs = tokenizer(prompt,
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outputs = model(**inputs)
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return torch.argmax(outputs.logits).item()
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def image_to_base64(file_path):
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"""将图片转换为Base64格式"""
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with open(file_path, "rb") as f:
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file_ext = Path(file_path).suffix.lower()[1:]
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mime_type = f"image/{file_ext}" if file_ext in ["jpeg", "jpg", "png"
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return f"data:{mime_type};base64,{base64.b64encode(f.read()).decode()}"
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# 核心生成逻辑
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def generate_image(
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image_file,
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prompt,
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seed,
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session_id,
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enable_safety=True
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):
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try:
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# 安全检查
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if enable_safety:
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@@ -123,7 +132,8 @@ def generate_image(
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# 速率限制
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if not rate_limiter.check(session_id):
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error_img = create_error_image(
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yield "❌ 请求过于频繁,请稍后再试", error_img, ""
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return
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@@ -173,8 +183,7 @@ def generate_image(
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"https://api.wavespeed.ai/api/v2/wavespeed-ai/hidream-e1-full",
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headers=headers,
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json=payload,
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timeout=30
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)
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response.raise_for_status()
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# 处理响应
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@@ -208,83 +217,90 @@ def generate_image(
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error_img = create_error_image(str(e))
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yield f"❌ 生成失败: {str(e)}", error_img, ""
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# 后台清理任务
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def cleanup_task():
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while True:
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session_manager.cleanup_sessions()
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time.sleep(3600)
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# 界面构建
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with gr.Blocks(
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css="""
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.status-box { padding: 10px; border-radius: 5px; margin: 5px; }
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.safe { background: #e8f5e9; border: 1px solid #a5d6a7; }
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.warning { background: #fff3e0; border: 1px solid #ffcc80; }
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.error { background: #ffebee; border: 1px solid #ef9a9a; }
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"""
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session_id = gr.State(str(uuid.uuid4()))
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gr.Markdown("# 🖼️Hidream-E1-Full Live On Wavespeed Ai")
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gr.Markdown("HiDream-E1 is an image editing model built on HiDream-I1.")
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with gr.Row():
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with gr.Column(scale=1):
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image_file = gr.Image(label="Upload Image",
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random_btn = gr.Button("random🎲seed", variant="secondary")
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enable_safety = gr.Checkbox(label="🔒 Enable Safety Checker",
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with gr.Column(scale=1):
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output_image = gr.Image(label="Generated Result")
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output_url = gr.Textbox(label="image url",
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status = gr.Textbox(label="Status", elem_classes=["status-box"])
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submit_btn = gr.Button("开始生成", variant="primary")
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gr.Examples(
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examples=[
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[
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"
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"https://
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],
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[
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"
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"https://
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],
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[
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"
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"https://
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],
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[
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'
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"https://
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],
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[
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'
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"https://
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]
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],
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)
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random_btn.click(
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fn=lambda: random.randint(0, 999999),
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outputs=seed
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)
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submit_btn.click(
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generate_image,
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inputs=[image_file, prompt, seed, session_id, enable_safety],
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outputs=[status, output_image, output_url]
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)
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if __name__ == "__main__":
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threading.Thread(target=cleanup_task, daemon=True).start()
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app.queue(max_size=4).launch(
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share=False
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)
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except Exception as e:
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raise RuntimeError(f"安全模型加载失败: {str(e)}")
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+
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# 会话管理
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class SessionManager:
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_instances = {}
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def cleanup_sessions(cls):
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with cls._lock:
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now = time.time()
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expired = [
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k for k, v in cls._instances.items()
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if now - v['last_active'] > 3600
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]
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for k in expired:
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del cls._instances[k]
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+
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# 速率限制
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class RateLimiter:
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def __init__(self):
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self.clients = {}
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self.lock = threading.Lock()
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self.clients[client_id]['count'] += 1
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return True
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+
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session_manager = SessionManager()
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rate_limiter = RateLimiter()
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# 工具函数
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def create_error_image(message):
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"""生成错误提示图片"""
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draw.text((50, 200), text, fill="#ff0000", font=font)
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return img
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+
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@torch.no_grad()
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def classify_prompt(prompt):
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"""安全分类"""
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inputs = tokenizer(prompt,
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return_tensors="pt",
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truncation=True,
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max_length=512)
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outputs = model(**inputs)
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return torch.argmax(outputs.logits).item()
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+
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def image_to_base64(file_path):
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"""将图片转换为Base64格式"""
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with open(file_path, "rb") as f:
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file_ext = Path(file_path).suffix.lower()[1:]
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mime_type = f"image/{file_ext}" if file_ext in ["jpeg", "jpg", "png"
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] else "image/jpeg"
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return f"data:{mime_type};base64,{base64.b64encode(f.read()).decode()}"
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# 核心生成逻辑
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def generate_image(image_file, prompt, seed, session_id, enable_safety=True):
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try:
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# 安全检查
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if enable_safety:
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# 速率限制
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if not rate_limiter.check(session_id):
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error_img = create_error_image(
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"Hourly limit exceeded (20 requests)")
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yield "❌ 请求过于频繁,请稍后再试", error_img, ""
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return
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"https://api.wavespeed.ai/api/v2/wavespeed-ai/hidream-e1-full",
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headers=headers,
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json=payload,
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timeout=30)
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response.raise_for_status()
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# 处理响应
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error_img = create_error_image(str(e))
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yield f"❌ 生成失败: {str(e)}", error_img, ""
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+
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# 后台清理任务
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def cleanup_task():
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while True:
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session_manager.cleanup_sessions()
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time.sleep(3600)
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+
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# 界面构建
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with gr.Blocks(theme=gr.themes.Soft(),
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css="""
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.status-box { padding: 10px; border-radius: 5px; margin: 5px; }
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.safe { background: #e8f5e9; border: 1px solid #a5d6a7; }
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.warning { background: #fff3e0; border: 1px solid #ffcc80; }
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.error { background: #ffebee; border: 1px solid #ef9a9a; }
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""") as app:
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session_id = gr.State(str(uuid.uuid4()))
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gr.Markdown("# 🖼️Hidream-E1-Full Live On Wavespeed Ai")
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gr.Markdown("HiDream-E1 is an image editing model built on HiDream-I1.")
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with gr.Row():
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with gr.Column(scale=1):
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image_file = gr.Image(label="Upload Image",
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type="filepath",
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sources=["upload"],
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interactive=True,
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image_mode="RGB")
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prompt = gr.Textbox(
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label="prompt",
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placeholder="Please enter an English prompt...",
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lines=3)
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seed = gr.Number(label="seed",
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value=-1,
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minimum=-1,
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maximum=999999,
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step=1)
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random_btn = gr.Button("random🎲seed", variant="secondary")
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enable_safety = gr.Checkbox(label="🔒 Enable Safety Checker",
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value=True,
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interactive=False)
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with gr.Column(scale=1):
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output_image = gr.Image(label="Generated Result")
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output_url = gr.Textbox(label="image url",
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interactive=True,
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visible=False)
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status = gr.Textbox(label="Status", elem_classes=["status-box"])
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submit_btn = gr.Button("开始生成", variant="primary")
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gr.Examples(examples=[
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[
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"Convert the image into Claymation style.",
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"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/penguin.png"
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],
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[
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"Convert the image into a Ghibli style.",
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"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/flux_ip_adapter_input.jpg"
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],
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[
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"Add sunglasses to the face of the girl.",
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"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/ip_mask_girl2.png"
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],
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[
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'Convert the image into an ink sketch style.',
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"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg"
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],
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[
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'Add a butterfly to the scene.',
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"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/controlnet_depth_result.png"
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]
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],
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inputs=[prompt, image_file],
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label="Examples")
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random_btn.click(fn=lambda: random.randint(0, 999999), outputs=seed)
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submit_btn.click(
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generate_image,
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inputs=[image_file, prompt, seed, session_id, enable_safety],
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outputs=[status, output_image, output_url])
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if __name__ == "__main__":
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threading.Thread(target=cleanup_task, daemon=True).start()
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app.queue(max_size=4).launch(server_name="0.0.0.0",
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server_port=7860,
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show_error=True,
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share=False)
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