Update app.py
Browse files
app.py
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@@ -60,38 +60,6 @@ MODEL_MAPPING = {
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}
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SYSTEM_ASSISTANT = """作为 Stable Diffusion Prompt 提示词专家,您将从关键词中创建提示,通常来自 Danbooru 等数据库。
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提示通常描述图像,使用常见词汇,按重要性排列,并用逗号分隔。避免使用"-"或".",但可以接受空格和自然语言。避免词汇重复。
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为了强调关键词,请将其放在括号中以增加其权重。例如,"(flowers)"将'flowers'的权重增加1.1倍,而"(((flowers)))"将其增加1.331倍。使用"(flowers:1.5)"将'flowers'的权重增加1.5倍。只为重要的标签增加权重。
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提示包括三个部分:**前缀**(质量标签+风格词+效果器)+ **主题**(图像的主要焦点)+ **场景**(背景、环境)。
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* 前缀影响图像质量。像"masterpiece"、"best quality"、"4k"这样的标签可以提高图像的细节。像"illustration"、"lensflare"这样的风格词定义图像的风格。像"bestlighting"、"lensflare"、"depthoffield"这样的效果器会影响光照和深度。
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* 主题是图像的主要焦点,如角色或场景。对主题进行详细描述可以确保图像丰富而详细。增加主题的权重以增强其清晰度。对于角色,描述面部、头发、身体、服装、姿势等特征。
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* 场景描述环境。没有场景,图像的背景是平淡的,主题显得过大。某些主题本身包含场景(例如建筑物、风景)。像"花草草地"、"阳光"、"河流"这样的环境词可以丰富场景。你的任务是设计图像生成的提示。请按照以下步骤进行操作:
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1. 我会发送给您一个图像场景。需要你生成详细的图像描述
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2. 图像描述必须是英文,输出为Positive Prompt。
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示例:
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我发送:二战时期的护士。
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您回复只回复:
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A WWII-era nurse in a German uniform, holding a wine bottle and stethoscope, sitting at a table in white attire, with a table in the background, masterpiece, best quality, 4k, illustration style, best lighting, depth of field, detailed character, detailed environment.
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"""
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RATIO_MAP = {
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"1:1": "1024x1024",
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"1:2": "1024x2048",
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"3:2": "1536x1024",
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"4:3": "1536x2048",
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"16:9": "2048x1152",
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"9:16": "1152x2048"
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}
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# 模拟身份验证函数
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def getAuthCookie(req):
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auth_cookie = req.headers.get('Authorization')
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@@ -99,6 +67,54 @@ def getAuthCookie(req):
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return auth_cookie
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return None
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@app.route('/ai/v1/models', methods=['GET'])
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def get_models():
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try:
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@@ -258,6 +274,38 @@ def translate_and_enhance_prompt(prompt, auth_token):
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result = response.json()
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return result['choices'][0]['message']['content']
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def stream_response(unique_id, image_data, original_prompt, translated_prompt, size, created, model, system_fingerprint, use_original):
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return Response(stream_with_context(generate_stream(unique_id, image_data, original_prompt, translated_prompt, size, created, model, system_fingerprint, use_original)), content_type='text/event-stream')
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}
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}
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# 模拟身份验证函数
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def getAuthCookie(req):
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auth_cookie = req.headers.get('Authorization')
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return auth_cookie
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return None
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@app.route('/')
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def index():
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usage = """
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<html>
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<head>
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<title>Text-to-Image API with SiliconFlow</title>
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<style>
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body { font-family: Arial, sans-serif; line-height: 1.6; padding: 20px; max-width: 800px; margin: 0 auto; }
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h1 { color: #333; }
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h2 { color: #666; }
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pre { background-color: #f4f4f4; padding: 10px; border-radius: 5px; }
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code { font-family: Consolas, monospace; }
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</style>
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</head>
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<body>
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<h1>Welcome to the Text-to-Image API with SiliconFlow!</h1>
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<h2>Usage:</h2>
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<ol>
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<li>Send a POST request to <code>/ai/v1/chat/completions</code></li>
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<li>Include your prompt in the 'content' field of the last message</li>
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<li>Optional parameters:
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<ul>
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<li><code>-s <ratio></code>: Set image size ratio (e.g., -s 1:1, -s 16:9)</li>
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<li><code>-o</code>: Use original prompt without enhancement</li>
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</ul>
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</li>
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</ol>
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<h2>Example Request:</h2>
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<pre><code>
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{
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"model": "flux",
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"messages": [
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{
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"role": "user",
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"content": "A beautiful landscape -s 16:9"
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}
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]
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}
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</code></pre>
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<p>For more details, please refer to the API documentation.</p>
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</body>
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</html>
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"""
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return usage, 200
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@app.route('/ai/v1/models', methods=['GET'])
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def get_models():
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try:
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result = response.json()
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return result['choices'][0]['message']['content']
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SYSTEM_ASSISTANT = """作为 Stable Diffusion Prompt 提示词专家,您将从关键词中创建提示,通常来自 Danbooru 等数据库。
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+
提示通常描述图像,使用常见词汇,按重要性排列,并用逗号分隔。避免使用"-"或".",但可以接受空格和自然语言。避免词汇重复。
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+
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为了强调关键词,请将其放在括号中以增加其权重。例如,"(flowers)"将'flowers'的权重增加1.1倍,而"(((flowers)))"将其增加1.331倍。使用"(flowers:1.5)"将'flowers'的权重增加1.5倍。只为重要的标签增加权重。
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+
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提示包括三个部分:**前缀**(质量标签+风格词+效果器)+ **主题**(图像的主要焦点)+ **场景**(背景、环境)。
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+
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* 前缀影响图像质量。像"masterpiece"、"best quality"、"4k"这样的标签可以提高图像的细节。像"illustration"、"lensflare"这���的风格词定义图像的风格。像"bestlighting"、"lensflare"、"depthoffield"这样的效果器会影响光照和深度。
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+
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* 主题是图像的主要焦点,如角色或场景。对主题进行详细描述可以确保图像丰富而详细。增加主题的权重以增强其清晰度。对于角色,描述面部、头发、身体、服装、姿势等特征。
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+
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* 场景描述环境。没有场景,图像的背景是平淡的,主题显得过大。某些主题本身包含场景(例如建筑物、风景)。像"花草草地"、"阳光"、"河流"这样的环境词可以丰富场景。你的任务是设计图像生成的提示。请按照以下步骤进行操作:
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+
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1. 我会发送给您一个图像场景。需要你生成详细的图像描述
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2. 图像描述必须是英文,输出为Positive Prompt。
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示例:
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+
我发送:二战时期的护士。
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您回复只回复:
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A WWII-era nurse in a German uniform, holding a wine bottle and stethoscope, sitting at a table in white attire, with a table in the background, masterpiece, best quality, 4k, illustration style, best lighting, depth of field, detailed character, detailed environment.
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"""
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RATIO_MAP = {
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"1:1": "1024x1024",
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"1:2": "1024x2048",
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"3:2": "1536x1024",
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"4:3": "1536x2048",
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"16:9": "2048x1152",
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"9:16": "1152x2048"
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}
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def stream_response(unique_id, image_data, original_prompt, translated_prompt, size, created, model, system_fingerprint, use_original):
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return Response(stream_with_context(generate_stream(unique_id, image_data, original_prompt, translated_prompt, size, created, model, system_fingerprint, use_original)), content_type='text/event-stream')
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