add env example

.env.example

@@ -0,0 +1,14 @@
+# Server
+PORT=8787
+HOST=0.0.0.0
+
+# Set this in prod
+# ADMIN_TOKEN=change_me_to_a_long_random_string
+
+# Providers
+# OPENAI_API_KEY=
+# ANTHROPIC_API_KEY=
+# XAI_API_KEY=
+
+# Prisma (SQLite dev)
+DATABASE_URL="file:./dev.db"

.gitignore

@@ -0,0 +1,12 @@
+node_modules
+.env
+.env.*
+dev.db
+*.db
+prisma/migrations
+.DS_Store
+dist
+
+# leftovers from early prisma v7 experiment
+/generated
+prisma.config.ts.bak

README.md

@@ -1,3 +1,66 @@
 # llm-backend
 
-LLM multiplexer + personal chat DB backend
+Backend API for:
+- LLM multiplexer (OpenAI / Anthropic / xAI (Grok))
+- Personal chat database (chats/messages + LLM call log)
+
+## Stack
+- Node.js + TypeScript
+- Fastify (HTTP)
+- Prisma + SQLite (dev)
+
+## Quick start
+
+```bash
+cd llm-backend
+cp .env.example .env
+npm run db:migrate
+npm run dev
+```
+
+Open docs: `http://localhost:8787/docs`
+
+## Auth
+
+Set `ADMIN_TOKEN` and send:
+
+`Authorization: Bearer <ADMIN_TOKEN>`
+
+If `ADMIN_TOKEN` is not set, the server runs in open mode (dev).
+
+## Env
+- `OPENAI_API_KEY`
+- `ANTHROPIC_API_KEY`
+- `XAI_API_KEY`
+
+## API
+- `GET /health`
+- `GET /v1/chats`
+- `POST /v1/chats`
+- `GET /v1/chats/:chatId`
+- `POST /v1/chats/:chatId/messages`
+- `POST /v1/chat-completions`
+- `POST /v1/chat-completions/stream` (SSE)
+
+`POST /v1/chat-completions` body example:
+
+```json
+{
+  "chatId": "<optional chat id>",
+  "provider": "openai",
+  "model": "gpt-4.1-mini",
+  "messages": [
+    {"role":"system","content":"You are helpful."},
+    {"role":"user","content":"Say hi"}
+  ],
+  "temperature": 0.2,
+  "maxTokens": 256
+}
+```
+
+## Next steps (planned)
+- Better streaming protocol compatibility (OpenAI-style chunks + cancellation)
+- Tool/function calling normalization
+- User accounts + per-device API keys
+- Postgres support + migrations for prod
+- Attachments + embeddings + semantic search

package.json

@@ -0,0 +1,34 @@
+{
+  "name": "llm-backend",
+  "version": "0.1.0",
+  "private": true,
+  "type": "module",
+  "description": "LLM multiplexer + personal chat database backend",
+  "scripts": {
+    "dev": "tsx watch src/index.ts",
+    "start": "node dist/index.js",
+    "build": "tsc -p tsconfig.json",
+    "prisma:generate": "prisma generate",
+    "db:migrate": "prisma migrate dev",
+    "db:studio": "prisma studio"
+  },
+  "dependencies": {
+    "@anthropic-ai/sdk": "^0.71.2",
+    "@fastify/cors": "^11.2.0",
+    "@fastify/sensible": "^6.0.4",
+    "@fastify/swagger": "^9.6.1",
+    "@fastify/swagger-ui": "^5.2.5",
+    "@prisma/client": "^6.16.1",
+    "dotenv": "^17.2.3",
+    "fastify": "^5.7.2",
+    "openai": "^6.16.0",
+    "pino-pretty": "^13.1.3",
+    "zod": "^4.3.6"
+  },
+  "devDependencies": {
+    "@types/node": "^25.0.10",
+    "prisma": "^6.16.1",
+    "tsx": "^4.21.0",
+    "typescript": "^5.9.3"
+  }
+}

prisma/schema.prisma

@@ -0,0 +1,94 @@
+// Prisma schema for the personal chat DB + LLM call log
+
+generator client {
+  provider = "prisma-client-js"
+}
+
+datasource db {
+  provider = "sqlite"
+  url      = env("DATABASE_URL")
+}
+
+enum Provider {
+  openai
+  anthropic
+  xai
+}
+
+enum MessageRole {
+  system
+  user
+  assistant
+  tool
+}
+
+model User {
+  id        String   @id @default(cuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  // minimal for now (single-user is fine). Keep extensible.
+  handle String? @unique
+
+  chats Chat[]
+}
+
+model Chat {
+  id        String   @id @default(cuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  title String?
+
+  user   User?   @relation(fields: [userId], references: [id])
+  userId String?
+
+  messages Message[]
+  calls    LlmCall[]
+
+  @@index([userId])
+}
+
+model Message {
+  id        String      @id @default(cuid())
+  createdAt DateTime    @default(now())
+
+  chat   Chat   @relation(fields: [chatId], references: [id], onDelete: Cascade)
+  chatId String
+
+  role    MessageRole
+  content String
+
+  // for tool messages or attachments later
+  name     String?
+  metadata Json?
+
+  @@index([chatId, createdAt])
+}
+
+model LlmCall {
+  id        String   @id @default(cuid())
+  createdAt DateTime @default(now())
+
+  chat   Chat   @relation(fields: [chatId], references: [id], onDelete: Cascade)
+  chatId String
+
+  provider Provider
+  model    String
+
+  // request/response snapshots for debugging + replay
+  request  Json
+  response Json?
+
+  // usage/cost basics
+  inputTokens  Int?
+  outputTokens Int?
+  totalTokens  Int?
+
+  latencyMs Int?
+
+  error   String?
+
+  @@index([chatId, createdAt])
+  @@index([provider, model, createdAt])
+}

src/auth.ts

@@ -0,0 +1,22 @@
+import type { FastifyRequest } from "fastify";
+import { env } from "./env.js";
+
+export function requireAdmin(req: FastifyRequest) {
+  // If ADMIN_TOKEN isn't set, run in "open" mode (dev).
+  if (!env.ADMIN_TOKEN) return;
+
+  const auth = req.headers.authorization;
+  if (!auth?.startsWith("Bearer ")) {
+    const err = new Error("missing bearer token");
+    // @ts-expect-error attach status
+    err.statusCode = 401;
+    throw err;
+  }
+  const token = auth.slice("Bearer ".length);
+  if (token !== env.ADMIN_TOKEN) {
+    const err = new Error("invalid bearer token");
+    // @ts-expect-error attach status
+    err.statusCode = 403;
+    throw err;
+  }
+}

src/db.ts

@@ -0,0 +1,16 @@
+import { PrismaClient } from "@prisma/client";
+
+export const prisma = new PrismaClient({
+  log: [
+    { emit: "event", level: "error" },
+    { emit: "event", level: "warn" },
+  ],
+});
+
+prisma.$on("error", (e: any) => {
+  console.error("[prisma:error]", e);
+});
+
+prisma.$on("warn", (e: any) => {
+  console.warn("[prisma:warn]", e);
+});

src/env.ts

@@ -0,0 +1,19 @@
+import { z } from "zod";
+import "dotenv/config";
+
+const EnvSchema = z.object({
+  PORT: z.coerce.number().int().positive().default(8787),
+  HOST: z.string().default("0.0.0.0"),
+
+  // simple bearer-token auth for your personal backend
+  ADMIN_TOKEN: z.string().min(20).optional(),
+
+  // provider keys
+  OPENAI_API_KEY: z.string().optional(),
+  ANTHROPIC_API_KEY: z.string().optional(),
+  XAI_API_KEY: z.string().optional(),
+});
+
+export type Env = z.infer<typeof EnvSchema>;
+
+export const env: Env = EnvSchema.parse(process.env);

src/index.ts

@@ -0,0 +1,45 @@
+import Fastify from "fastify";
+import cors from "@fastify/cors";
+import swagger from "@fastify/swagger";
+import swaggerUI from "@fastify/swagger-ui";
+import sensible from "@fastify/sensible";
+import { env } from "./env.js";
+import { registerRoutes } from "./routes.js";
+
+const app = Fastify({
+  logger: {
+    transport: {
+      target: "pino-pretty",
+      options: { colorize: true, translateTime: "SYS:standard" },
+    },
+  },
+});
+
+await app.register(cors, { origin: true, credentials: true });
+
+await app.register(swagger, {
+  openapi: {
+    info: {
+      title: "LLM Multiplexer Backend",
+      version: "0.1.0",
+    },
+  },
+});
+
+await app.register(swaggerUI, { routePrefix: "/docs" });
+await app.register(sensible);
+
+app.setErrorHandler((err, _req, reply) => {
+  const e = err as any;
+  const statusCode = e.statusCode ?? 500;
+  reply.status(statusCode).send({
+    error: true,
+    message: e.message ?? String(e),
+    statusCode,
+  });
+});
+
+await registerRoutes(app);
+
+await app.listen({ port: env.PORT, host: env.HOST });
+app.log.info(`listening on http://${env.HOST}:${env.PORT}`);

src/llm/multiplexer.ts

@@ -0,0 +1,124 @@
+import { performance } from "node:perf_hooks";
+import { prisma } from "../db.js";
+import { anthropicClient, openaiClient, xaiClient } from "./providers.js";
+import type { MultiplexRequest, MultiplexResponse, Provider } from "./types.js";
+
+function asProviderEnum(p: Provider) {
+  // Prisma enum values match these strings.
+  return p;
+}
+
+export async function runMultiplex(req: MultiplexRequest): Promise<MultiplexResponse> {
+  const t0 = performance.now();
+
+  // Persist call record early so we can attach errors.
+  const call = await prisma.llmCall.create({
+    data: {
+      chatId: req.chatId ?? (await prisma.chat.create({ data: {} })).id,
+      provider: asProviderEnum(req.provider) as any,
+      model: req.model,
+      request: req as any,
+    },
+    select: { id: true, chatId: true },
+  });
+
+  try {
+    let outText = "";
+    let usage: MultiplexResponse["usage"] | undefined;
+    let raw: unknown;
+
+    if (req.provider === "openai" || req.provider === "xai") {
+      const client = req.provider === "openai" ? openaiClient() : xaiClient();
+      const r = await client.chat.completions.create({
+        model: req.model,
+        // OpenAI SDK has very specific message union types; our normalized schema is compatible.
+        messages: req.messages.map((m) => ({ role: m.role, content: m.content, name: m.name })) as any,
+        temperature: req.temperature,
+        max_tokens: req.maxTokens,
+      });
+      raw = r;
+      outText = r.choices?.[0]?.message?.content ?? "";
+      usage = r.usage
+        ? {
+            inputTokens: r.usage.prompt_tokens,
+            outputTokens: r.usage.completion_tokens,
+            totalTokens: r.usage.total_tokens,
+          }
+        : undefined;
+    } else if (req.provider === "anthropic") {
+      const client = anthropicClient();
+
+      // Anthropic splits system prompt. We'll convert first system message into system string.
+      const system = req.messages.find((m) => m.role === "system")?.content;
+      const msgs = req.messages
+        .filter((m) => m.role !== "system")
+        .map((m) => ({ role: m.role === "assistant" ? "assistant" : "user", content: m.content }));
+
+      const r = await client.messages.create({
+        model: req.model,
+        system,
+        max_tokens: req.maxTokens ?? 1024,
+        temperature: req.temperature,
+        messages: msgs as any,
+      });
+      raw = r;
+      outText = r.content
+        .map((c: any) => (c.type === "text" ? c.text : ""))
+        .join("")
+        .trim();
+
+      // Anthropic usage (SDK typing varies by version)
+      const ru: any = (r as any).usage;
+      if (ru) {
+        usage = {
+          inputTokens: ru.input_tokens,
+          outputTokens: ru.output_tokens,
+          totalTokens: (ru.input_tokens ?? 0) + (ru.output_tokens ?? 0),
+        };
+      }
+    } else {
+      throw new Error(`unknown provider: ${req.provider}`);
+    }
+
+    const latencyMs = Math.round(performance.now() - t0);
+
+    // Store assistant message + call record
+    await prisma.$transaction([
+      prisma.message.create({
+        data: {
+          chatId: call.chatId,
+          role: "assistant" as any,
+          content: outText,
+        },
+      }),
+      prisma.llmCall.update({
+        where: { id: call.id },
+        data: {
+          response: raw as any,
+          latencyMs,
+          inputTokens: usage?.inputTokens,
+          outputTokens: usage?.outputTokens,
+          totalTokens: usage?.totalTokens,
+        },
+      }),
+    ]);
+
+    return {
+      provider: req.provider,
+      model: req.model,
+      message: { role: "assistant", content: outText },
+      usage,
+      raw,
+    };
+  } catch (e: any) {
+    const latencyMs = Math.round(performance.now() - t0);
+    await prisma.llmCall.update({
+      where: { id: call.id },
+      data: {
+        error: e?.message ?? String(e),
+        latencyMs,
+      },
+    });
+    throw e;
+  }
+}

src/llm/providers.ts

@@ -0,0 +1,19 @@
+import OpenAI from "openai";
+import Anthropic from "@anthropic-ai/sdk";
+import { env } from "../env.js";
+
+export function openaiClient() {
+  if (!env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY not set");
+  return new OpenAI({ apiKey: env.OPENAI_API_KEY });
+}
+
+// xAI (Grok) is OpenAI-compatible at https://api.x.ai/v1
+export function xaiClient() {
+  if (!env.XAI_API_KEY) throw new Error("XAI_API_KEY not set");
+  return new OpenAI({ apiKey: env.XAI_API_KEY, baseURL: "https://api.x.ai/v1" });
+}
+
+export function anthropicClient() {
+  if (!env.ANTHROPIC_API_KEY) throw new Error("ANTHROPIC_API_KEY not set");
+  return new Anthropic({ apiKey: env.ANTHROPIC_API_KEY });
+}

src/llm/streaming.ts

@@ -0,0 +1,130 @@
+import { performance } from "node:perf_hooks";
+import type OpenAI from "openai";
+import { prisma } from "../db.js";
+import { anthropicClient, openaiClient, xaiClient } from "./providers.js";
+import type { MultiplexRequest, Provider } from "./types.js";
+
+export type StreamEvent =
+  | { type: "meta"; chatId: string; callId: string; provider: Provider; model: string }
+  | { type: "delta"; text: string }
+  | { type: "done"; text: string; usage?: { inputTokens?: number; outputTokens?: number; totalTokens?: number } }
+  | { type: "error"; message: string };
+
+function getChatIdOrCreate(chatId?: string) {
+  if (chatId) return Promise.resolve(chatId);
+  return prisma.chat.create({ data: {}, select: { id: true } }).then((c) => c.id);
+}
+
+export async function* runMultiplexStream(req: MultiplexRequest): AsyncGenerator<StreamEvent> {
+  const t0 = performance.now();
+  const chatId = await getChatIdOrCreate(req.chatId);
+
+  const call = await prisma.llmCall.create({
+    data: {
+      chatId,
+      provider: req.provider as any,
+      model: req.model,
+      request: req as any,
+    },
+    select: { id: true },
+  });
+
+  yield { type: "meta", chatId, callId: call.id, provider: req.provider, model: req.model };
+
+  let text = "";
+  let usage: StreamEvent extends any ? any : never;
+  let raw: unknown = { streamed: true };
+
+  try {
+    if (req.provider === "openai" || req.provider === "xai") {
+      const client = req.provider === "openai" ? openaiClient() : xaiClient();
+
+      const stream = await client.chat.completions.create({
+        model: req.model,
+        messages: req.messages.map((m) => ({ role: m.role, content: m.content, name: m.name })) as any,
+        temperature: req.temperature,
+        max_tokens: req.maxTokens,
+        stream: true,
+      });
+
+      for await (const chunk of stream as any as AsyncIterable<OpenAI.Chat.Completions.ChatCompletionChunk>) {
+        const delta = chunk.choices?.[0]?.delta?.content ?? "";
+        if (delta) {
+          text += delta;
+          yield { type: "delta", text: delta };
+        }
+      }
+
+      // no guaranteed usage in stream mode across providers; leave empty for now
+    } else if (req.provider === "anthropic") {
+      const client = anthropicClient();
+
+      const system = req.messages.find((m) => m.role === "system")?.content;
+      const msgs = req.messages
+        .filter((m) => m.role !== "system")
+        .map((m) => ({ role: m.role === "assistant" ? "assistant" : "user", content: m.content }));
+
+      const stream = await client.messages.create({
+        model: req.model,
+        system,
+        max_tokens: req.maxTokens ?? 1024,
+        temperature: req.temperature,
+        messages: msgs as any,
+        stream: true,
+      });
+
+      for await (const ev of stream as any as AsyncIterable<any>) {
+        // Anthropic streaming events include content_block_delta with text_delta
+        if (ev?.type === "content_block_delta" && ev?.delta?.type === "text_delta") {
+          const delta = ev.delta.text ?? "";
+          if (delta) {
+            text += delta;
+            yield { type: "delta", text: delta };
+          }
+        }
+        // capture usage if present on message_delta
+        if (ev?.type === "message_delta" && ev?.usage) {
+          usage = {
+            inputTokens: ev.usage.input_tokens,
+            outputTokens: ev.usage.output_tokens,
+            totalTokens:
+              (ev.usage.input_tokens ?? 0) + (ev.usage.output_tokens ?? 0),
+          };
+        }
+        // some streams end with message_stop
+      }
+    } else {
+      throw new Error(`unknown provider: ${req.provider}`);
+    }
+
+    const latencyMs = Math.round(performance.now() - t0);
+
+    await prisma.$transaction([
+      prisma.message.create({
+        data: { chatId, role: "assistant" as any, content: text },
+      }),
+      prisma.llmCall.update({
+        where: { id: call.id },
+        data: {
+          response: raw as any,
+          latencyMs,
+          inputTokens: usage?.inputTokens,
+          outputTokens: usage?.outputTokens,
+          totalTokens: usage?.totalTokens,
+        },
+      }),
+    ]);
+
+    yield { type: "done", text, usage };
+  } catch (e: any) {
+    const latencyMs = Math.round(performance.now() - t0);
+    await prisma.llmCall.update({
+      where: { id: call.id },
+      data: {
+        error: e?.message ?? String(e),
+        latencyMs,
+      },
+    });
+    yield { type: "error", message: e?.message ?? String(e) };
+  }
+}

src/llm/types.ts

@@ -0,0 +1,28 @@
+export type Provider = "openai" | "anthropic" | "xai";
+
+export type ChatMessage = {
+  role: "system" | "user" | "assistant" | "tool";
+  content: string;
+  name?: string;
+};
+
+export type MultiplexRequest = {
+  chatId?: string;
+  provider: Provider;
+  model: string;
+  messages: ChatMessage[];
+  temperature?: number;
+  maxTokens?: number;
+};
+
+export type MultiplexResponse = {
+  provider: Provider;
+  model: string;
+  message: { role: "assistant"; content: string };
+  usage?: {
+    inputTokens?: number;
+    outputTokens?: number;
+    totalTokens?: number;
+  };
+  raw: unknown;
+};

src/routes.ts

@@ -0,0 +1,171 @@
+import { z } from "zod";
+import type { FastifyInstance } from "fastify";
+import { prisma } from "./db.js";
+import { requireAdmin } from "./auth.js";
+import { runMultiplex } from "./llm/multiplexer.js";
+import { runMultiplexStream } from "./llm/streaming.js";
+
+export async function registerRoutes(app: FastifyInstance) {
+  app.get("/health", async () => ({ ok: true }));
+
+  app.get("/v1/chats", async (req) => {
+    requireAdmin(req);
+    const chats = await prisma.chat.findMany({
+      orderBy: { updatedAt: "desc" },
+      take: 100,
+      select: { id: true, title: true, createdAt: true, updatedAt: true },
+    });
+    return { chats };
+  });
+
+  app.post("/v1/chats", async (req) => {
+    requireAdmin(req);
+    const Body = z.object({ title: z.string().optional() });
+    const body = Body.parse(req.body ?? {});
+    const chat = await prisma.chat.create({ data: { title: body.title } });
+    return { chat };
+  });
+
+  app.get("/v1/chats/:chatId", async (req) => {
+    requireAdmin(req);
+    const Params = z.object({ chatId: z.string() });
+    const { chatId } = Params.parse(req.params);
+
+    const chat = await prisma.chat.findUnique({
+      where: { id: chatId },
+      include: { messages: { orderBy: { createdAt: "asc" } }, calls: { orderBy: { createdAt: "desc" } } },
+    });
+    if (!chat) return app.httpErrors.notFound("chat not found");
+    return { chat };
+  });
+
+  app.post("/v1/chats/:chatId/messages", async (req) => {
+    requireAdmin(req);
+    const Params = z.object({ chatId: z.string() });
+    const Body = z.object({
+      role: z.enum(["system", "user", "assistant", "tool"]),
+      content: z.string(),
+      name: z.string().optional(),
+      metadata: z.unknown().optional(),
+    });
+
+    const { chatId } = Params.parse(req.params);
+    const body = Body.parse(req.body);
+
+    const msg = await prisma.message.create({
+      data: {
+        chatId,
+        role: body.role as any,
+        content: body.content,
+        name: body.name,
+        metadata: body.metadata as any,
+      },
+    });
+
+    return { message: msg };
+  });
+
+  // Main: create a completion via provider+model and store everything.
+  app.post("/v1/chat-completions", async (req) => {
+    requireAdmin(req);
+
+    const Body = z.object({
+      chatId: z.string().optional(),
+      provider: z.enum(["openai", "anthropic", "xai"]),
+      model: z.string().min(1),
+      messages: z.array(
+        z.object({
+          role: z.enum(["system", "user", "assistant", "tool"]),
+          content: z.string(),
+          name: z.string().optional(),
+        })
+      ),
+      temperature: z.number().min(0).max(2).optional(),
+      maxTokens: z.number().int().positive().optional(),
+    });
+
+    const body = Body.parse(req.body);
+
+    // ensure chat exists if provided
+    if (body.chatId) {
+      const exists = await prisma.chat.findUnique({ where: { id: body.chatId }, select: { id: true } });
+      if (!exists) return app.httpErrors.notFound("chat not found");
+    }
+
+    // store user messages (anything not assistant) for DB fidelity
+    if (body.chatId) {
+      const toInsert = body.messages.filter((m) => m.role !== "assistant");
+      if (toInsert.length) {
+        await prisma.message.createMany({
+          data: toInsert.map((m) => ({ chatId: body.chatId!, role: m.role as any, content: m.content, name: m.name })),
+        });
+      }
+    }
+
+    const result = await runMultiplex(body);
+
+    return {
+      chatId: body.chatId ?? null,
+      ...result,
+    };
+  });
+
+  // Streaming SSE endpoint.
+  app.post("/v1/chat-completions/stream", async (req, reply) => {
+    requireAdmin(req);
+
+    const Body = z.object({
+      chatId: z.string().optional(),
+      provider: z.enum(["openai", "anthropic", "xai"]),
+      model: z.string().min(1),
+      messages: z.array(
+        z.object({
+          role: z.enum(["system", "user", "assistant", "tool"]),
+          content: z.string(),
+          name: z.string().optional(),
+        })
+      ),
+      temperature: z.number().min(0).max(2).optional(),
+      maxTokens: z.number().int().positive().optional(),
+    });
+
+    const body = Body.parse(req.body);
+
+    // ensure chat exists if provided
+    if (body.chatId) {
+      const exists = await prisma.chat.findUnique({ where: { id: body.chatId }, select: { id: true } });
+      if (!exists) return app.httpErrors.notFound("chat not found");
+    }
+
+    // store user messages (anything not assistant) for DB fidelity
+    if (body.chatId) {
+      const toInsert = body.messages.filter((m) => m.role !== "assistant");
+      if (toInsert.length) {
+        await prisma.message.createMany({
+          data: toInsert.map((m) => ({ chatId: body.chatId!, role: m.role as any, content: m.content, name: m.name })),
+        });
+      }
+    }
+
+    reply.raw.writeHead(200, {
+      "Content-Type": "text/event-stream; charset=utf-8",
+      "Cache-Control": "no-cache, no-transform",
+      Connection: "keep-alive",
+    });
+
+    const send = (event: string, data: any) => {
+      reply.raw.write(`event: ${event}\n`);
+      reply.raw.write(`data: ${JSON.stringify(data)}\n\n`);
+    };
+
+    for await (const ev of runMultiplexStream(body)) {
+      if (ev.type === "meta") send("meta", ev);
+      else if (ev.type === "delta") send("delta", ev);
+      else if (ev.type === "done") send("done", ev);
+      else if (ev.type === "error") send("error", ev);
+    }
+
+    reply.raw.end();
+    return reply;
+  });
+}

tsconfig.json

@@ -0,0 +1,15 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "module": "NodeNext",
+    "moduleResolution": "NodeNext",
+    "lib": ["ES2022"],
+    "strict": true,
+    "esModuleInterop": true,
+    "skipLibCheck": true,
+    "forceConsistentCasingInFileNames": true,
+    "outDir": "dist",
+    "rootDir": "src"
+  },
+  "include": ["src/**/*"]
+}