【第二弹】用不完，根本用不完，部署cf worker无限免费绘画，可Api，支持多模型切换 - 常规话题 / 人工智能 - LINUX DO
各位道友，求个爱心，助我飞升
【无限虚假的dall-e-3绘画，可NewApi】更新-支持多模型切换 - 常规话题 / 高阶秘辛 - LINUX DO
在大佬的基础上，增加了模型映射，适配/v1/models接口，适配/v1/chat/completions接口，增加授权验证，增加流和非流模式
8月27日更新
部署到 CF 的 worker.js
//本项目授权api_key，防止被恶意调用
const API_KEY = "sk-1234567890";
//硅基流动Token列表，每次请求都会随机从列表里取一个Token
const SILICONFLOW_TOKEN_LIST = ["sk-xxx1","sk-xxx2","sk-xxx3"];
//是否开启提示词翻译、优化功能
const SILICONFLOW_IS_TRANSLATE = true;
//提示词翻译、优化模型
const SILICONFLOW_TRANSLATE_MODEL = "Qwen/Qwen1.5-7B-Chat";
//模型映射，设置客户端可用的模型。one-api，new-api在添加渠道时可使用“获取模型列表”功能，一键添加模型
const CUSTOMER_MODEL_MAP = {
"FLUX.1": "flux",
"stable-diffusion-3-medium": "sd3",
"stable-diffusion-xl-base": "sdxl",
"stable-diffusion-xl-turbo": "sdxlt",
"stable-diffusion-xl-lightning": "sdxll",
"stable-diffusion-2-1": "sd2",
"stable-diffusion-turbo": "sdt",
"PhotoMaker": "pm"
};
const URL_MAP = {
flux: "https://api.siliconflow.cn/v1/black-forest-labs/FLUX.1-schnell/text-to-image",
sd3: "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-3-medium/text-to-image",
sdxl: "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-xl-base-1.0/text-to-image",
sd2: "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-2-1/text-to-image",
sdt: "https://api.siliconflow.cn/v1/stabilityai/sd-turbo/text-to-image",
sdxlt: "https://api.siliconflow.cn/v1/stabilityai/sdxl-turbo/text-to-image",
sdxll: "https://api.siliconflow.cn/v1/ByteDance/SDXL-Lightning/text-to-image"
};
const IMG_URL_MAP = {
sdxl: "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-xl-base-1.0/image-to-image",
sd2: "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-2-1/image-to-image",
sdxll: "https://api.siliconflow.cn/v1/ByteDance/SDXL-Lightning/image-to-image",
pm: "https://api.siliconflow.cn/v1/TencentARC/PhotoMaker/image-to-image"
};
const RATIO_MAP = {
"1:1": "1024x1024",
"1:2": "1024x2048",
"3:2": "1536x1024",
"4:3": "1536x2048",
"16:9": "2048x1152",
"9:16": "1152x2048"
};
async function handleRequest(request) {
try {
if (request.method === "OPTIONS") {
return new Response("", {
status: 204,
headers: {
'Access-Control-Allow-Origin': '*',
"Access-Control-Allow-Headers": '*'
}
});
}
const authHeader = request.headers.get("Authorization");
if (!authHeader || !authHeader.startsWith("Bearer ") || authHeader.split(" ")[1] !== API_KEY) {
return new Response("Unauthorized", { status: 401 });
}
if (request.url.endsWith("/v1/models")) {
const arrs = [];
Object.keys(CUSTOMER_MODEL_MAP).map(element => arrs.push({ id: element, object: "model" }))
const response = {
data: arrs,
success: true
};
return new Response(JSON.stringify(response), {
headers: {
'Content-Type': 'application/json',
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Headers': '*'
}
});
}
if (request.method !== "POST") {
return new Response("Only POST requests are allowed", {
status: 405,
});
}
if (!request.url.endsWith("/v1/chat/completions")) {
return new Response("Not Found", {
status: 404,
});
}
const data = await request.json();
const messages = data.messages || [];
const model = CUSTOMER_MODEL_MAP[data.model] || CUSTOMER_MODEL_MAP["FLUX.1"];
const stream = data.stream || false;
const userMessage = messages.reverse().find((msg) => msg.role === "user")?.content;
if (!userMessage) {
return new Response(JSON.stringify({ error: "未找到用户消息" }), {
status: 400,
headers: {
'Content-Type': 'application/json',
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Headers': '*'
}
});
}
const size = extractImageSize(userMessage);
const prompt = cleanPromptString(userMessage, model);
const imageUrl = extractImageUrl(prompt);
const originalPrompt = removeImageUrls(prompt);
const translatedPrompt = SILICONFLOW_IS_TRANSLATE ? await getPrompt(originalPrompt) : originalPrompt;
let url;
if (!imageUrl) {
url = await generateImageByText(translatedPrompt, model, size);
} else {
const base64 = await convertImageToBase64(imageUrl);
url = await generateImageByImg(translatedPrompt, base64, model, size);
}
if (!url) {
url = "https://pic.netbian.com/uploads/allimg/240808/192001-17231160015724.jpg";
}
if (stream) {
return handleStreamResponse(originalPrompt, translatedPrompt, size, model, url);
} else {
return handleNonStreamResponse(originalPrompt, translatedPrompt, size, model, url);
}
} catch (error) {
console.error("处理请求时出错:", error);
return new Response(
JSON.stringify({ error: `处理请求失败: ${error.message}` }), {
status: 500,
headers: {
'Content-Type': 'application/json',
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Headers': '*'
}
}
);
}
}
async function generateImageByText(translatedPrompt, model, imageSize) {
const modelKey = model;
const apiUrl = URL_MAP[modelKey] || URL_MAP.flux;
const jsonBody = {
prompt: translatedPrompt,
image_size: imageSize,
num_inference_steps: 50
};
if (modelKey === "") {
this.modelKey = "flux";
}
if (modelKey !== "flux") {
jsonBody.batch_size = 1;
jsonBody.guidance_scale = 7.5;
if (["sdt", "sdxlt"].includes(modelKey)) {
jsonBody.num_inference_steps = 6;
jsonBody.guidance_scale = 1;
} else if (modelKey === "sdxll") {
jsonBody.num_inference_steps = 4;
jsonBody.guidance_scale = 1;
}
}
return await getImageUrl(apiUrl, jsonBody);
}
async function generateImageByImg(translatedPrompt, base64, model, imageSize) {
const modelKey = model;
const apiUrl = IMG_URL_MAP[modelKey] || IMG_URL_MAP.sdxl;
const jsonBody = {
prompt: translatedPrompt,
image: base64,
image_size: imageSize,
batch_size: 1,
num_inference_steps: 50,
guidance_scale: 7.5
};
if (modelKey === "") {
this.modelKey = "sdxl";
}
if (modelKey === "sdxll") {
jsonBody.num_inference_steps = 4;
jsonBody.guidance_scale = 1;
} else if (modelKey === "pm") {
jsonBody.style_name = "Photographic (Default)";
jsonBody.guidance_scale = 5;
jsonBody.style_strengh_radio = 20;
}
return await getImageUrl(apiUrl, jsonBody);
}
function handleStreamResponse(originalPrompt, translatedPrompt, size, model, imageUrl) {
const uniqueId = `chatcmpl-${Date.now()}`;
const createdTimestamp = Math.floor(Date.now() / 1000);
const systemFingerprint = "fp_" + Math.random().toString(36).substr(2, 9);
const content = `🎨 原始提示词：${originalPrompt}\n` +
`🌐 翻译后的提示词：${translatedPrompt}\n` +
`📐 图像规格：${size}\n` +
`🌟 图像生成成功！\n` +
`以下是结果：\n\n` +
``;
const responsePayload = {
id: uniqueId,
object: "chat.completion.chunk",
created: createdTimestamp,
model: model,
system_fingerprint: systemFingerprint,
choices: [
{
index: 0,
delta: {
content: content,
},
finish_reason: "stop",
},
],
};
const dataString = JSON.stringify(responsePayload);
return new Response(`data: ${dataString}\n\n`, {
status: 200,
headers: {
"Content-Type": "text/event-stream",
'Access-Control-Allow-Origin': '*',
"Access-Control-Allow-Headers": '*',
},
});
}
function handleNonStreamResponse(originalPrompt, translatedPrompt, size, model, imageUrl) {
const uniqueId = `chatcmpl-${Date.now()}`;
const createdTimestamp = Math.floor(Date.now() / 1000);
const systemFingerprint = "fp_" + Math.random().toString(36).substr(2, 9);
const content = `🎨 原始提示词：${originalPrompt}\n` +
`🌐 翻译后的提示词：${translatedPrompt}\n` +
`📐 图像规格：${size}\n` +
`🌟 图像生成成功！\n` +
`以下是结果：\n\n` +
``;
const response = {
id: uniqueId,
object: "chat.completion",
created: createdTimestamp,
model: model,
system_fingerprint: systemFingerprint,
choices: [{
index: 0,
message: {
role: "assistant",
content: content
},
finish_reason: "stop"
}],
usage: {
prompt_tokens: translatedPrompt.length,
completion_tokens: content.length,
total_tokens: translatedPrompt.length + content.length
}
};
const dataString = JSON.stringify(response);
return new Response(dataString, {
status: 200,
headers: {
'Content-Type': 'application/json',
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Headers': '*'
}
});
}
async function getPrompt(prompt) {
const requestBodyJson = {
model: SILICONFLOW_TRANSLATE_MODEL,
messages: [
{
role: "system",
content: `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。
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。
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。
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）。
* 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。
* 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。
* 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：
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
2. 图像描述必须是英文，输出为Positive Prompt。
示例：
我发送：二战时期的护士。
您回复只回复：
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.`
},
{
role: "user",
content: prompt
}
],
stream: false,
max_tokens: 512,
temperature: 0.7,
top_p: 0.7,
top_k: 50,
frequency_penalty: 0.5,
n: 1
};
const apiUrl="https://api.siliconflow.cn/v1/chat/completions";
const response = await postRequest(apiUrl,requestBodyJson);
const jsonResponse = await response.json();
const res = jsonResponse.choices[0].message.content;
return res;
}
async function getImageUrl(apiUrl, jsonBody){
const response = await postRequest(apiUrl,jsonBody);
if (!response.ok) {
throw new Error('Unexpected response ' + response.status);
}
const jsonResponse = await response.json();
return jsonResponse.images[0].url;
}
async function postRequest(apiUrl, jsonBody) {
const token = SILICONFLOW_TOKEN_LIST[Math.floor(Math.random() * SILICONFLOW_TOKEN_LIST.length)];
const response = await fetch(apiUrl, {
method: 'POST',
headers: {
'Authorization': `Bearer ${token}`,
'Accept': 'application/json',
'Content-Type': 'application/json'
},
body: JSON.stringify(jsonBody)
});
return response;
}
function extractModelKey(prompt) {
const match = prompt.match(/-m ?(\S+)/);
return match ? match[1].trim() : "";
}
function extractImageSize(prompt) {
const match = prompt.match(/---(\d+:\d+)/);
return match ? RATIO_MAP[match[1].trim()] || "1024x1024" : "1024x1024";
}
function cleanPromptString(prompt, modelKey) {
return prompt.replace(/ -m ?\S+/, "").replace(/---\d+:\d+/, "").trim();
}
function extractImageUrl(text) {
const regex = /(https?:\/\/[^\s]+?\.(?:png|jpe?g|gif|bmp|webp|svg))/i;
const match = text.match(regex);
return match ? match[0] : null;
}
async function convertImageToBase64(imageUrl) {
const response = await fetch(imageUrl);
if (!response.ok) {
throw new Error('Failed to download image');
}
const arrayBuffer = await response.arrayBuffer();
const base64Image = btoa(String.fromCharCode(...new Uint8Array(arrayBuffer)));
return `data:image/webp;base64,${base64Image}`;
}
function removeImageUrls(text) {
return text.replace(/https?:\/\/\S+\.(?:png|jpe?g|gif|bmp|webp|svg)/gi, "");
}
addEventListener('fetch', event => {
event.respondWith(handleRequest(event.request));
});
