Free login GPT3.5 to API
https://github.com/missuo/FreeGPT35
https://github.com/aurora-develop/aurora
https://github.com/Dalufishe/freegptjs
https://github.com/PawanOsman/ChatGPT
https://github.com/nashsu/FreeAskInternet
https://github.com/aurorax-neo/free-gpt3.5-2api
https://github.com/aurora-develop/free-gpt3.5-2api
https://github.com/LanQian528/chat2api
https://github.com/k0baya/FreeGPT35-Glitch
https://github.com/cliouo/FreeGPT35-Vercel
https://github.com/hominsu/freegpt35
https://github.com/xsigoking/chatgpt-free-api
https://github.com/skzhengkai/free-chatgpt-api
https://github.com/aurora-develop/aurora-glitch （使用glitch资源）
https://github.com/fatwang2/coze2openai（COZE转API，GPT4）
Domestic Model Reverse
search in depth(DeepSeek) Interface to API deepseek-free-api
Moonshot AI (Kimi.ai) Interface to API kimi-free-api
jumping stars (Leapfrog Ask StepChat) Interface to API step-free-api
Ali Tongyi (Qwen) Interface to API qwen-free-api
ZhipuAI (lit. record wisdom and say clearly) Interface to API glm-free-api
Meta AI (metaso) Interface to API metaso-free-api
Byte Jump (Beanbag) Interface to API doubao-free-api
Byte Jump (i.e. Dream AI) Interface to API jimeng-free-api
Spark Interface to API spark-free-api
MiniMax (Conch AI) Interface to API hailuo-free-api
Emohaa Interface to API emohaa-free-api
Login-free program with chat interface
https://github.com/Mylinde/FreeGPT
The work code for cloudflare, tie up your own domain name to play:
addEventListener(“fetch”, event => {
event.respondWith(handleRequest(event.request))
})async function handleRequest(request) {
// 确保请求是 POST 请求，并且路径正确
if (request.method === “POST” && new URL(request.url).pathname === “/v1/chat/completions”) {
const url = 'https://multillm.ai-pro.org/api/openai-completion'; // target API address
const headers = new Headers(request.headers);// 添加或修改需要的 headers
headers.set(‘Content-Type’, ‘application/json’);// 获取请求的 body 并解析 JSON
const requestBody = await request.json();
const stream = requestBody.stream; // get the stream argument// 构造新的请求
const newRequest = new Request(url, {
method: ‘POST’,
headers: headers,
body: JSON.stringify(requestBody) // use modified body
});try {
// 向目标 API 发送请求
const response = await fetch(newRequest);// 根据 stream 参数确定响应类型
if (stream) {
// 处理流式响应
const { readable, writable } = new TransformStream();
response.body.pipeTo(writable);
return new Response(readable, {
headers: response.headers
});
} else {
// 正常返回响应
return new Response(response.body, {
status: response.status,
headers: response.headers
});
}
} catch (e) {
// 如果请求失败，返回错误信息
return new Response(JSON.stringify({ error: ‘Unable to reach the backend API’ }), { status: 502 });
}
} else {
// 如果请求方法不是 POST 或路径不正确，返回错误
return new Response(‘Not found’, { status: 404 });
}
}
POST Example:
curl –location ‘https://ai-pro-free.aivvm.com/v1/chat/completions’ \
–header ‘Content-Type: application/json’ \
–data ‘{
“model”: “gpt-4-turbo”,
“messages”: [
{
"role": "user", "content": "Why Lu Xun hit Zhou Shuren "
}],
“stream”: true
}’
Add a pseudo-streaming code (output will be slower):
addEventListener(“fetch”, event => {
event.respondWith(handleRequest(event.request))
})async function handleRequest(request) {
if (request.method === “OPTIONS”) {
return new Response(null, {
headers: {
‘Access-Control-Allow-Origin’: ‘*’,
“Access-Control-Allow-Headers”: ‘*’
}, status: 204
})
}
// 确保请求是 POST 请求，并且路径正确
if (request.method === “POST” && new URL(request.url).pathname === “/v1/chat/completions”) {
const url = 'https://multillm.ai-pro.org/api/openai-completion'; // target API address
const headers = new Headers(request.headers);// 添加或修改需要的 headers
headers.set(‘Content-Type’, ‘application/json’);// 获取请求的 body 并解析 JSON
const requestBody = await request.json();
const stream = requestBody.stream; // get the stream argument// 构造新的请求
const newRequest = new Request(url, {
method: ‘POST’,
headers: headers,
body: JSON.stringify(requestBody) // use modified body
});try {
// 向目标 API 发送请求
const response = await fetch(newRequest);// 根据 stream 参数确定响应类型
if (stream) {
const originalJson = await response.json(); // read the full data at once
// 创建一个可读流
const readableStream = new ReadableStream({
start(controller) {
// 发送开始数据
const startData = createDataChunk(originalJson, “start”);
controller.enqueue(new TextEncoder().encode(‘data: ‘ + JSON.stringify(startData) + ‘\n\n’));// 假设根据 originalJson 处理并发送多个数据块
// 例如，模拟分批次发送数据
const content = originalJson.choices[0].message.content; // assume this is the content to send
const newData = createDataChunk(originalJson, “data”, content);
controller.enqueue(new TextEncoder().encode(‘data: ‘ + JSON.stringify(newData) + ‘\n\n’));// 发送结束数据
const endData = createDataChunk(originalJson, “end”);
controller.enqueue(new TextEncoder().encode(‘data: ‘ + JSON.stringify(endData) + ‘\n\n’));controller.enqueue(new TextEncoder().encode(‘data: [DONE]’));
// 标记流的结束
controller.close();
}
});
return new Response(readableStream, {
headers: {
‘Access-Control-Allow-Origin’: ‘*’,
“Access-Control-Allow-Headers”: ‘*’,
‘Content-Type’: ‘text/event-stream’,
‘Cache-Control’: ‘no-cache’,
‘Connection’: ‘keep-alive’
}
});
} else {
// 正常返回响应
return new Response(response.body, {
status: response.status,
headers: response.headers
});
}
} catch (e) {
// 如果请求失败，返回错误信息
return new Response(JSON.stringify({ error: ‘Unable to reach the backend API’ }), { status: 502 });
}
} else {
// 如果请求方法不是 POST 或路径不正确，返回错误
return new Response(‘Not found’, { status: 404 });
}
}// 根据类型创建不同的数据块
function createDataChunk(json, type, content = {}) {
switch (type) {
case “start”:
return {
id: json.id,
object: “chat.completion.chunk”,
created: json.created,
model: json.model,
choices: [{ delta: {}, index: 0, finish_reason: null }]
};
case “data”:
return {
id: json.id,
object: “chat.completion.chunk”,
created: json.created,
model: json.model,
choices: [{ delta: { content }, index: 0, finish_reason: null }]
};
case “end”:
return {
id: json.id,
object: “chat.completion.chunk”,
created: json.created,
model: json.model,
choices: [{ delta: {}, index: 0, finish_reason: ‘stop’ }]
};
default:
return {};
}
}
