chore: kv

.env.example

@@ -1,14 +1,15 @@
 NEXT_PUBLIC_APP_URL=http://localhost:3000
 NEXTAUTH_URL=http://localhost:3000
+USER_SESSION_KEY=markdx-user-session
 
-# Database (MySQL - Planetscale)
 DATABASE_URL="mysql://root:root@localhost:3306/markdx?schema=public"
 
 OPENAI_API_KEY=
 OPENAI_MODEL=gpt-4-1106-preview
 
 # openssl rand -base64 32 : Run this in your command line and paste here the generated secret
 NEXTAUTH_SECRET=
+CRYPTO_SECRET_KEY=
 
 # Required 👆🏻
 # Optional 👇🏻

app/(dashboard)/dashboard/billing/page.tsx

@@ -14,7 +14,7 @@ export const metadata = {
 }
 
 export default async function BillingPage() {
-  const user = await getCurrentUser()
+  const { sessionUser: user } = await getCurrentUser()
 
   if (!user) {
     redirect(authOptions?.pages?.signIn || "/login")

app/(dashboard)/dashboard/page.tsx

@@ -12,7 +12,7 @@ import { DashboardShell } from "@/components/dashboard/shell"
 import { Icons } from "@/components/icons"
 
 async function Dashboard() {
-  const user = (await getCurrentUser()) as any
+  const { sessionUser: user } = await getCurrentUser()
 
   if (!user) {
     redirect(authOptions?.pages?.signIn || "/login")

app/(dashboard)/layout.tsx

@@ -13,7 +13,7 @@ export const metadata = {
 }
 
 async function DashboardLayout({ children }: DashboardLayout) {
-  const user = await getCurrentUser()
+  const { sessionUser: user } = await getCurrentUser()
 
   if (!user) {
     return notFound()

app/(editor)/edit/[id]/page.tsx

@@ -7,13 +7,13 @@ import {
   monacoInstanceState,
 } from "@/atoms/editor"
 import { handleShortCut } from "@/utils/editor"
+import { GET } from "@/utils/http.utils"
 import { useAtom, useAtomValue } from "jotai"
 
 import { editorCode } from "types"
 import { defaultEditorContent } from "@/config/editor"
 import AIToolsSection from "@/components/editor/ai-tools-section"
 import EditorSection from "@/components/editor/editor-section"
-import MarkdownNotFound from "@/components/editor/markdown-not-found"
 import PreviewSection from "@/components/editor/preview-section"
 
 type prevCodeType = {
@@ -22,29 +22,26 @@ type prevCodeType = {
   content: string
 }
 
+type Markdown = {
+  markdownPost: {
+    postCodes: editorCode[]
+  }
+  isEligibleForAI: boolean
+}
+
 export default function page({ params }: { params: { id: string } }) {
   const [editorCodes, setEditorCodes] = useAtom(editorCodesState)
   const editorActiveSection = useAtomValue(editorActiveSectionState)
   const [markdownCode, setMarkdownCode] = useState("")
   const monacoInstance = useAtomValue(monacoInstanceState)
-  const [markdownNotFoundDialogOpen, setMarkdownNotFoundDialogOpen] =
-    useState(false)
   const [isEligibleForAI, setIsEligibleForAI] = useState(true)
 
   const markdownId = params.id
 
   const getMarkdownPost = async (markdownId: string) => {
-    const response = await fetch(`/api/posts/${markdownId}`, {
-      method: "GET",
-    })
+    const markdown = await GET<Markdown>(`/api/posts/${markdownId}`)
 
-    if (!response?.ok) {
-      setMarkdownNotFoundDialogOpen(true)
-      return
-    }
-
-    const resJson = await response.json()
-    const markdownPost = resJson.markdownPost
+    const markdownPost = markdown.markdownPost
 
     if (
       markdownPost?.postCodes?.length > 0 &&
@@ -60,16 +57,7 @@ export default function page({ params }: { params: { id: string } }) {
           setMarkdownCode(code.content)
         })
 
-      // Check if the user is eligible for AI - make a request to the API
-      const response = await fetch(`/api/user/eligible-for-ai`, {
-        method: "GET",
-        next: {
-          revalidate: 0,
-        },
-        cache: "no-store",
-      })
-      const resJson = await response.json()
-      setIsEligibleForAI(resJson.isEligibleForAI)
+      setIsEligibleForAI(markdown.isEligibleForAI)
     } else {
       const defaultCode = [defaultEditorContent] as editorCode[]
 
@@ -125,11 +113,6 @@ export default function page({ params }: { params: { id: string } }) {
       <PreviewSection
         code={editorCodes.map((code: editorCode) => code.content).join("\n\n")}
       />
-      {markdownNotFoundDialogOpen && (
-        <MarkdownNotFound
-          markdownNotFoundDialogOpen={markdownNotFoundDialogOpen}
-        />
-      )}
     </div>
   )
 }

app/(home)/layout.tsx

@@ -8,7 +8,7 @@ interface MarketingLayoutProps {
 export default async function MarketingLayout({
   children,
 }: MarketingLayoutProps) {
-  const user = await getCurrentUser()
+  const { sessionUser: user } = await getCurrentUser()
 
   return (
     <div className="flex min-h-screen flex-col">

app/api/chat/route.ts

@@ -1,13 +1,12 @@
+import { ServerResponse } from "@/server/utils"
 import { OpenAIBody } from "@/types"
+import { OpenAIStream, StreamingTextResponse } from "ai"
 import OpenAI from "openai"
 
 import { env } from "@/env.mjs"
-
-import { OpenAIStream, StreamingTextResponse } from 'ai';
-
-import { ServerResponse } from "@/server/utils"
-import { getCurrentUser } from "@/lib/session"
+import { kvget, kvset } from "@/lib/kv"
 import { openai } from "@/lib/openai"
+import { getCurrentUser } from "@/lib/session"
 
 if (!env.OPENAI_API_KEY) {
   throw new Error("Missing env var from OpenAI")
@@ -16,9 +15,9 @@ if (!env.OPENAI_API_KEY) {
 export async function POST(req: Request): Promise<Response> {
   // Parse the request body.
   const body: OpenAIBody = (await req.json()) as OpenAIBody
-  const userId = (await getCurrentUser())?.id
+  const { sessionUser: user } = await getCurrentUser()
 
-  if(!userId) {
+  if (!user?.id) {
     return ServerResponse.unauthorized()
   }
 
@@ -32,7 +31,16 @@ export async function POST(req: Request): Promise<Response> {
     stream: true,
   }
 
-  const response = await openai.chat.completions.create(payload);
-  const stream = OpenAIStream(response);
-  return new StreamingTextResponse(stream);
+  const response = await openai.chat.completions.create(payload)
+  const user_ai_run_count = await kvget(user.id, "ai_run_count")
+
+  // Count the number of times the user has used the AI.
+  kvset(
+    user.id,
+    "ai_run_count",
+    user_ai_run_count ? Number(user_ai_run_count) + 1 : 1
+  )
+
+  const stream = OpenAIStream(response)
+  return new StreamingTextResponse(stream)
 }