khanon
130 lines
3.6 KiB
TypeScript
130 lines
3.6 KiB
TypeScript
import { Request, RequestHandler, Router } from "express";
|
|
import { OpenAIImageGenerationResult } from "../shared/file-storage/mirror-generated-image";
|
|
import { generateModelList } from "./openai";
|
|
import { ipLimiter } from "./rate-limit";
|
|
import {
|
|
addKey,
|
|
createPreprocessorMiddleware,
|
|
finalizeBody,
|
|
} from "./middleware/request";
|
|
import { ProxyResHandlerWithBody } from "./middleware/response";
|
|
import { ProxyReqManager } from "./middleware/request/proxy-req-manager";
|
|
import { createQueuedProxyMiddleware } from "./middleware/request/proxy-middleware-factory";
|
|
|
|
const KNOWN_MODELS = ["dall-e-2", "dall-e-3"];
|
|
|
|
let modelListCache: any = null;
|
|
let modelListValid = 0;
|
|
const handleModelRequest: RequestHandler = (_req, res) => {
|
|
if (new Date().getTime() - modelListValid < 1000 * 60) {
|
|
return res.status(200).json(modelListCache);
|
|
}
|
|
const result = generateModelList("openai").filter((m: { id: string }) =>
|
|
KNOWN_MODELS.includes(m.id)
|
|
);
|
|
modelListCache = { object: "list", data: result };
|
|
modelListValid = new Date().getTime();
|
|
res.status(200).json(modelListCache);
|
|
};
|
|
|
|
const openaiImagesResponseHandler: ProxyResHandlerWithBody = async (
|
|
_proxyRes,
|
|
req,
|
|
res,
|
|
body
|
|
) => {
|
|
if (typeof body !== "object") {
|
|
throw new Error("Expected body to be an object");
|
|
}
|
|
|
|
let newBody = body;
|
|
if (req.inboundApi === "openai") {
|
|
req.log.info("Transforming OpenAI image response to OpenAI chat format");
|
|
newBody = transformResponseForChat(
|
|
body as OpenAIImageGenerationResult,
|
|
req
|
|
);
|
|
}
|
|
|
|
res.status(200).json({ ...newBody, proxy: body.proxy });
|
|
};
|
|
|
|
/**
|
|
* Transforms a DALL-E image generation response into a chat response, simply
|
|
* embedding the image URL into the chat message as a Markdown image.
|
|
*/
|
|
function transformResponseForChat(
|
|
imageBody: OpenAIImageGenerationResult,
|
|
req: Request
|
|
): Record<string, any> {
|
|
const prompt = imageBody.data[0].revised_prompt ?? req.body.prompt;
|
|
const content = imageBody.data
|
|
.map((item) => {
|
|
const { url, b64_json } = item;
|
|
if (b64_json) {
|
|
return ``;
|
|
} else {
|
|
return ``;
|
|
}
|
|
})
|
|
.join("\n\n");
|
|
|
|
return {
|
|
id: "dalle-" + req.id,
|
|
object: "chat.completion",
|
|
created: Date.now(),
|
|
model: req.body.model,
|
|
usage: {
|
|
prompt_tokens: 0,
|
|
completion_tokens: req.outputTokens,
|
|
total_tokens: req.outputTokens,
|
|
},
|
|
choices: [
|
|
{
|
|
message: { role: "assistant", content },
|
|
finish_reason: "stop",
|
|
index: 0,
|
|
},
|
|
],
|
|
};
|
|
}
|
|
|
|
function replacePath(manager: ProxyReqManager) {
|
|
const req = manager.request;
|
|
const pathname = req.url.split("?")[0];
|
|
req.log.debug({ pathname }, "OpenAI image path filter");
|
|
if (req.path.startsWith("/v1/chat/completions")) {
|
|
manager.setPath("/v1/images/generations");
|
|
}
|
|
}
|
|
|
|
const openaiImagesProxy = createQueuedProxyMiddleware({
|
|
target: "https://api.openai.com",
|
|
mutations: [replacePath, addKey, finalizeBody],
|
|
blockingResponseHandler: openaiImagesResponseHandler,
|
|
});
|
|
|
|
const openaiImagesRouter = Router();
|
|
openaiImagesRouter.get("/v1/models", handleModelRequest);
|
|
openaiImagesRouter.post(
|
|
"/v1/images/generations",
|
|
ipLimiter,
|
|
createPreprocessorMiddleware({
|
|
inApi: "openai-image",
|
|
outApi: "openai-image",
|
|
service: "openai",
|
|
}),
|
|
openaiImagesProxy
|
|
);
|
|
openaiImagesRouter.post(
|
|
"/v1/chat/completions",
|
|
ipLimiter,
|
|
createPreprocessorMiddleware({
|
|
inApi: "openai",
|
|
outApi: "openai-image",
|
|
service: "openai",
|
|
}),
|
|
openaiImagesProxy
|
|
);
|
|
export const openaiImage = openaiImagesRouter;
|