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import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
import { type CoreMessage, type Message, streamText } from "ai";
import type { Connect, PreviewServer, ViteDevServer } from "vite";
import { verifyTokenAndRateLimit } from "./verifyTokenAndRateLimit";
interface ChatCompletionRequestBody {
messages: CoreMessage[] | Omit<Message, "id">[];
temperature?: number;
top_p?: number;
frequency_penalty?: number;
presence_penalty?: number;
max_tokens?: number;
}
interface ChatCompletionChunk {
id: string;
object: string;
created: number;
model: string;
choices: Array<{
index: number;
delta: { content?: string };
finish_reason: string | null;
}>;
}
function createChunkPayload(
model: string,
content?: string,
finish_reason: string | null = null,
): ChatCompletionChunk {
return {
id: Date.now().toString(),
object: "chat.completion.chunk",
created: Date.now(),
model,
choices: [
{
index: 0,
delta: content ? { content } : {},
finish_reason,
},
],
};
}
export function internalApiEndpointServerHook<
T extends ViteDevServer | PreviewServer,
>(server: T) {
server.middlewares.use(async (request, response, next) => {
if (!request.url.startsWith("/inference")) return next();
const authHeader = request.headers.authorization;
const tokenPrefix = "Bearer ";
const token = authHeader?.startsWith(tokenPrefix)
? authHeader.slice(tokenPrefix.length)
: null;
const authResult = await verifyTokenAndRateLimit(token);
if (!authResult.isAuthorized) {
response.statusCode = authResult.statusCode;
response.end(authResult.error);
return;
}
if (
!process.env.INTERNAL_OPENAI_COMPATIBLE_API_BASE_URL ||
!process.env.INTERNAL_OPENAI_COMPATIBLE_API_KEY
) {
response.statusCode = 500;
response.end(
JSON.stringify({ error: "OpenAI API configuration is missing" }),
);
return;
}
const openaiProvider = createOpenAICompatible({
baseURL: process.env.INTERNAL_OPENAI_COMPATIBLE_API_BASE_URL,
apiKey: process.env.INTERNAL_OPENAI_COMPATIBLE_API_KEY,
name: "openai",
});
try {
const requestBody = await getRequestBody(request);
const model = process.env.INTERNAL_OPENAI_COMPATIBLE_API_MODEL;
if (!model) {
throw new Error("OpenAI model configuration is missing");
}
const stream = streamText({
model: openaiProvider.chatModel(model),
messages: requestBody.messages,
temperature: requestBody.temperature,
topP: requestBody.top_p,
frequencyPenalty: requestBody.frequency_penalty,
presencePenalty: requestBody.presence_penalty,
maxTokens: requestBody.max_tokens,
});
response.setHeader("Content-Type", "text/event-stream");
response.setHeader("Cache-Control", "no-cache");
response.setHeader("Connection", "keep-alive");
try {
for await (const part of stream.fullStream) {
if (part.type === "text-delta") {
const payload = createChunkPayload(model, part.textDelta);
response.write(`data: ${JSON.stringify(payload)}\n\n`);
} else if (part.type === "finish") {
const payload = createChunkPayload(model, undefined, "stop");
response.write(`data: ${JSON.stringify(payload)}\n\n`);
response.write("data: [DONE]\n\n");
response.end();
}
}
} catch (streamError) {
console.error("Error in stream processing:", streamError);
if (!response.headersSent) {
response.statusCode = 500;
response.end(JSON.stringify({ error: "Stream processing error" }));
} else {
response.end();
}
}
} catch (error) {
console.error("Error in internal API endpoint:", error);
response.statusCode = 500;
response.end(
JSON.stringify({
error: "Internal server error",
message: error instanceof Error ? error.message : "Unknown error",
}),
);
}
});
}
async function getRequestBody(
request: Connect.IncomingMessage,
): Promise<ChatCompletionRequestBody> {
return new Promise((resolve, reject) => {
const chunks: Buffer[] = [];
request.on("data", (chunk: Buffer) => {
chunks.push(chunk);
});
request.on("end", () => {
try {
const body = Buffer.concat(chunks).toString();
resolve(JSON.parse(body));
} catch (error) {
reject(new Error("Failed to parse request body"));
}
});
request.on("error", (error) => {
reject(new Error(`Request stream error: ${error.message}`));
});
});
}
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