👌 IMPROVE: English Cefr level assessment bot

examples/cefr-level-assessment-bot/.env.example

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+NEXT_LB_PIPE_API_KEY=""

examples/cefr-level-assessment-bot/.gitignore

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+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+
+# testing
+/coverage
+
+# next.js
+/.next/
+/out/
+
+# production
+/build
+
+# misc
+.DS_Store
+*.pem
+
+# debug
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+# local env files
+.env
+.env*.local
+.copy.local.env
+.copy.remote.env
+
+# vercel
+.vercel
+
+# typescript
+*.tsbuildinfo
+next-env.d.ts
+
+# Supabase
+seed.sql
+xseed.sql
+xxseed.sql
+-seed.sql
+/supabase/seed.sql
+/test-results/
+/playwright-report/
+/blob-report/
+/playwright/.cache/
+
+# No lock files.
+package-lock.json
+yarn.lock
+dist

examples/cefr-level-assessment-bot/README.md

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+![English (CEFR) Level Assessment Bot by ⌘ Langbase][cover]
+
+![License: MIT][mit] [![Fork to ⌘ Langbase][fork]][pipe]
+
+## Build English (CEFR) Level Assessment Bot with Pipes — ⌘ Langbase
+
+This chatbot is built by using an AI Pipe on Langbase, it works with 30+ LLMs (OpenAI, Gemini, Mistral, Llama, Gemma, etc), any Data (10M+ context with Memory sets), and any Framework (standard web API you can use with any software).
+
+Check out the live demo [here][demo].
+
+## Features
+
+- 💬 [CEFR Level Assessment Bot][demo] — Built with an [AI Pipe on ⌘ Langbase][pipe]
+- ⚡️ Streaming — Real-time chat experience with streamed responses
+- 🗣️ Q/A — Ask questions and get pre-defined answers with your preferred AI model and tone
+- 🔋 Responsive and open source — Works on all devices and platforms
+
+## Learn more
+
+1. Check the [CEFR Level Assessment Bot on ⌘ Langbase][pipe]
+2. Read the [source code on GitHub][gh] for this example
+3. Go through Documentaion: [Pipe Quick Start][qs]
+4. Learn more about [Pipes & Memory features on ⌘ Langbase][docs]
+
+## Get started
+
+Let's get started with the project:
+
+To get started with Langbase, you'll need to [create a free personal account on Langbase.com][signup] and verify your email address. _Done? Cool, cool!_
+
+1. Fork the [CEFR Level Assessment Bot][pipe] Pipe on ⌘ Langbase.
+2. Go to the API tab to copy the Pipe's API key (to be used on server-side only).
+3. Download the example project folder from [here][download] or clone the reppository.
+4. `cd` into the project directory and open it in your code editor.
+5. Duplicate the `.env.example` file in this project and rename it to `.env.local`.
+6. Add the following environment variables (.env.local):
+```
+    # Replace `PIPE_API_KEY` with the copied API key.
+    NEXT_LB_PIPE_API_KEY="PIPE_API_KEY"
+```    
+7. In your CLI issue the following:
+```sh
+    # Install the dependencies using the following command:
+    npm install
+
+    # Run the project using the following command:
+    npm run dev
+```
+
+8. Your app template should now be running on [localhost:3000][local].
+
+> NOTE:
+> This is a Next.js project, so you can build and deploy it to any platform of your choice, like Vercel, Netlify, Cloudflare, etc.
+
+---
+
+## Authors
+
+This project is created by [Langbase][lb] team members, with contributions from:
+
+- Muhammad-Ali Danish - Software Engineer, [Langbase][lb]
+
+**_Built by ⌘ [Langbase.com][lb] — Ship hyper-personalized AI assistants with memory!_**
+
+[cover]:https://raw.githubusercontent.com/LangbaseInc/docs-images/main/examples/cefr-level-assessment-bot/cefr-level-assessment-bot.png
+[demo]: https://cefr-level-assessment-bot.langbase.dev
+[lb]: https://langbase.com
+[pipe]: https://beta.langbase.com/examples/cefr-level-assessment-bot
+[gh]: https://github.com/LangbaseInc/langbase-examples/tree/main/examples/cefr-level-assessment-bot
+[download]:https://download-directory.github.io/?url=https://github.com/LangbaseInc/langbase-examples/tree/main/examples/cefr-level-assessment-bot
+[signup]: https://langbase.fyi/io
+[qs]:https://langbase.com/docs/pipe/quickstart
+[docs]:https://langbase.com/docs
+[xaa]:https://x.com/MrAhmadAwais
+[xab]:https://x.com/AhmadBilalDev
+[local]:http://localhost:3000
+[mit]: https://img.shields.io/badge/license-MIT-blue.svg?style=for-the-badge&color=%23000000
+[fork]: https://img.shields.io/badge/FORK%20ON-%E2%8C%98%20Langbase-000000.svg?style=for-the-badge&logo=%E2%8C%98%20Langbase&logoColor=000000

examples/cefr-level-assessment-bot/app/api/chat/route.ts

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+import { OpenAIStream, StreamingTextResponse } from 'ai'
+
+export const runtime = 'edge'
+
+/**
+ * Stream AI Chat Messages from Langbase
+ *
+ * @param req
+ * @returns
+ */
+export async function POST(req: Request) {
+  try {
+    if (!process.env.NEXT_LB_PIPE_API_KEY) {
+      throw new Error(
+        'Please set NEXT_LB_PIPE_API_KEY in your environment variables.'
+      )
+    }
+
+    const endpointUrl = 'https://api.langbase.com/beta/chat'
+
+    const headers = {
+      'Content-Type': 'application/json',
+      Authorization: `Bearer ${process.env.NEXT_LB_PIPE_API_KEY}`
+    }
+
+    // Get chat prompt messages and threadId from the client.
+    const body = await req.json()
+    const { messages, threadId } = body
+
+    const requestBody = {
+      messages,
+      ...(threadId && { threadId }) // Only include threadId if it exists
+    }
+
+    // Send the request to Langbase API.
+    const response = await fetch(endpointUrl, {
+      method: 'POST',
+      headers,
+      body: JSON.stringify(requestBody)
+    })
+
+    if (!response.ok) {
+      const res = await response.json()
+      throw new Error(`Error ${res.error.status}: ${res.error.message}`)
+    }
+
+    // Handle Langbase response, which is a stream in OpenAI format.
+    const stream = OpenAIStream(response)
+    // Respond with a text stream.
+    return new StreamingTextResponse(stream, {
+      headers: response.headers
+    })
+  } catch (error: any) {
+    console.error('Uncaught API Error:', error)
+    return new Response(JSON.stringify(error), { status: 500 })
+  }
+}

examples/cefr-level-assessment-bot/app/globals.css

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+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+/* Zinc */
+/* --background: 240 10% 3.9%; */
+/* --muted: 240 3.7% 15.9%; */
+@layer base {
+  :root {
+    --background: 0 0% 100%;
+    --foreground: 240 10% 3.9%;
+    --card: 0 0% 100%;
+    --card-foreground: 240 10% 3.9%;
+    --popover: 0 0% 100%;
+    --popover-foreground: 240 10% 3.9%;
+    --primary: 240 5.9% 10%;
+    --primary-foreground: 0 0% 98%;
+    --secondary: 240 4.8% 95.9%;
+    --secondary-foreground: 240 5.9% 10%;
+    --muted: 240 4.8% 95.9%;
+    --muted-foreground: 240 3.8% 46.1%;
+    --accent: 240 4.8% 95.9%;
+    --accent-foreground: 240 5.9% 10%;
+    /* --destructive: 0 84.2% 60.2%; */
+    --destructive: 2.74 92.59% 62.94%;
+    --destructive-foreground: 0 0% 98%;
+    --warning: 46.38 70.61% 48.04%;
+    --warning-foreground: 120 12.5% 3.14%;
+    --border: 240 5.9% 90%;
+    --input: 240 5.9% 90%;
+    --ring: 240 5.9% 10%;
+    --radius: 6px;
+    --danger: 2.74 92.59% 62.94%;
+  }
+
+  .dark {
+    /* --background: 120 12.5% 3.14%; */
+    --background: 240, 3%, 9%;
+    --foreground: 0 0% 98%;
+    --card: 240 10% 3.9%;
+    --card-foreground: 0 0% 98%;
+    --popover: 240 10% 3.9%;
+    --popover-foreground: 0 0% 98%;
+    --primary: 0 0% 98%;
+    --primary-foreground: 240 5.9% 10%;
+    --secondary: 240 3.7% 15.9%;
+    --secondary-foreground: 0 0% 98%;
+    /* --muted: 165 10% 7.84%; */
+    --muted: 240 3.45% 11.37%;
+    --muted-foreground: 240 5% 64.9%;
+    --accent: 240 3.7% 15.9%;
+    --accent-foreground: 0 0% 98%;
+    /* --destructive: 0 62.8% 30.6%; */
+    --destructive: 356.18 70.61% 48.04%;
+    --destructive-foreground: 0 0% 98%;
+    --warning: 46.38 70.61% 48.04%;
+    --warning-foreground: 120 12.5% 3.14%;
+    /* --border: 240 3.7% 15.9%; */
+    --border: 240 2% 14%;
+    --border-muted: 240 2% 14%;
+    --input: 240 3.7% 15.9%;
+    --ring: 240 4.9% 83.9%;
+    --danger: 356.18 70.61% 48.04%;
+  }
+}
+
+@layer base {
+  * {
+    @apply border-border;
+  }
+  body {
+    @apply bg-background text-foreground;
+  }
+}
+
+::selection {
+  color: hsl(var(--background));
+  background: hsl(var(--foreground));
+}
+
+.google {
+  display: inline-block;
+  width: 20px;
+  height: 20px;
+  position: relative;
+  background-size: contain;
+  background-repeat: no-repeat;
+  background-position: 50%;
+  background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' viewBox='0 0 48 48'%3E%3Cdefs%3E%3Cpath id='a' d='M44.5 20H24v8.5h11.8C34.7 33.9 30.1 37 24 37c-7.2 0-13-5.8-13-13s5.8-13 13-13c3.1 0 5.9 1.1 8.1 2.9l6.4-6.4C34.6 4.1 29.6 2 24 2 11.8 2 2 11.8 2 24s9.8 22 22 22c11 0 21-8 21-22 0-1.3-.2-2.7-.5-4z'/%3E%3C/defs%3E%3CclipPath id='b'%3E%3Cuse xlink:href='%23a' overflow='visible'/%3E%3C/clipPath%3E%3Cpath clip-path='url(%23b)' fill='%23FBBC05' d='M0 37V11l17 13z'/%3E%3Cpath clip-path='url(%23b)' fill='%23EA4335' d='M0 11l17 13 7-6.1L48 14V0H0z'/%3E%3Cpath clip-path='url(%23b)' fill='%2334A853' d='M0 37l30-23 7.9 1L48 0v48H0z'/%3E%3Cpath clip-path='url(%23b)' fill='%234285F4' d='M48 48L17 24l-4-3 35-10z'/%3E%3C/svg%3E");
+}
+
+@keyframes spin {
+  from {
+    transform: rotate(0deg);
+  }
+  to {
+    transform: rotate(360deg);
+  }
+}

examples/cefr-level-assessment-bot/app/layout.tsx

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+import { Header } from '@/components/header'
+import cn from 'mxcn'
+import type { Metadata } from 'next'
+import { Inter } from 'next/font/google'
+import { Toaster } from 'sonner'
+import './globals.css'
+
+const inter = Inter({ subsets: ['latin'] })
+
+export const metadata: Metadata = {
+  title: 'English (CEFR) Level Assessment Bot - Langbase',
+  description: 'Build an English (CEFR) Level Assessment Bot with ⌘ Langbase using any LLM model.',
+  keywords: ['English', 'CEFR Level Assessment Bot', 'Langbase']
+}
+
+export default function RootLayout({
+  children
+}: Readonly<{
+  children: React.ReactNode
+}>) {
+  return (
+    <html lang="en">
+      <body className={cn(inter.className, 'dark bg-background')}>
+        <div className="flex min-h-screen flex-col px-3 pr-0 pt-6">
+          <div className="rounded-l-[calc(var(--radius)+2px)] border border-r-0 pb-1 pl-1">
+            <Toaster />
+            <Header />
+            <main className="rounded-l-[calc(var(--radius)+2px)] bg-muted">
+              {children}
+            </main>
+          </div>
+        </div>
+      </body>
+    </html>
+  )
+}

examples/cefr-level-assessment-bot/app/page.tsx

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+import { Chatbot } from '@/components/chatbot-page'
+
+export const runtime = 'edge'
+
+export default function ChatPage() {
+  return <Chatbot />
+}