AI Study Assistant for any OpenAI-compatible LLM
Chat, flashcards, quizzes, and study plans — streaming SSE responses, runs on OpenAI, OpenRouter, Ollama, or Xiaomi MiMo.
Works with OpenAI, OpenRouter, Ollama, llama.cpp, Xiaomi MiMo, or any endpoint that speaks the OpenAI /chat/completions protocol. Pick a provider with one env var — no code changes.
┌──────────────────────────────────────────────────────────────┐
│ StudyPal │
│ Any OpenAI-compatible LLM backend │
├──────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ 💬 Chat │ │ 📇 Flashcards│ │ 📝 Quiz │ │
│ │ (SSE) │ │ (JSON) │ │ (JSON) │ │
│ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Next.js API Routes (Edge) │ │
│ │ /api/chat /api/flashcards /api/quiz │ │
│ └────────────────────────┬────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ OpenAI-compatible LLM Client │ │
│ │ Streaming SSE · reasoning_content · bearer/api-key │ │
│ │ Providers: OpenAI · OpenRouter · Ollama · MiMo │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Token Tracker (client-side) │ │
│ │ Per-session stats · Cache hit rate · Avg/call │ │
│ └─────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────┘
| Feature | Description | Streaming |
|---|---|---|
| 💬 Chat | Ask questions, get explanations with reasoning | SSE streaming |
| 📇 Flashcards | Auto-generated study cards with spaced repetition | JSON response |
| 📝 Quiz | Adaptive quizzes with explanations | JSON response |
| 📋 Summarize | Paste content, get study-optimized summaries | SSE streaming |
| 📊 Dashboard | Real-time token consumption tracking | Client-side |
StudyPal talks to any OpenAI-compatible /chat/completions endpoint. Built-in presets:
| Provider | LLM_PROVIDER |
Default model | Auth | Key env var |
|---|---|---|---|---|
| OpenAI | openai |
gpt-4o-mini |
Bearer | OPENAI_API_KEY |
| OpenRouter | openrouter |
openai/gpt-4o-mini |
Bearer | OPENROUTER_API_KEY |
| Ollama (local) | ollama |
llama3.1 |
Bearer | OLLAMA_BASE_URL |
| Groq | groq |
llama-3.3-70b-versatile |
Bearer | GROQ_API_KEY |
| DeepSeek | deepseek |
deepseek-chat |
Bearer | DEEPSEEK_API_KEY |
| Together | together |
meta-llama/Llama-3.3-70B-Instruct-Turbo |
Bearer | TOGETHER_API_KEY |
| Mistral | mistral |
mistral-small-latest |
Bearer | MISTRAL_API_KEY |
| Xiaomi MiMo | mimo |
mimo-v2.5-pro |
api-key | MIMO_API_KEY |
Set LLM_PROVIDER + the matching key (or just LLM_API_KEY). Override LLM_BASE_URL / LLM_MODEL for any other compatible endpoint (llama.cpp, vLLM, LM Studio). The right auth header (bearer vs api-key) is chosen automatically. The chat feature surfaces a model's reasoning_content when available, but it isn't required.
Per-feature estimated consumption:
- Chat message: ~800 tokens (400 prompt + 400 completion)
- Flashcard set (8 cards): ~600 tokens
- Quiz (5 questions): ~500 tokens
- Summarize (1000 words): ~1200 tokens
Daily estimate for active student: 20K-50K tokens/day
# Clone and install
git clone https://github.com/aimanmalib/studypal.git
cd studypal
npm install
# Set environment — pick any provider (OpenAI shown here)
echo 'LLM_PROVIDER=openai' > .env.local
echo 'OPENAI_API_KEY=YOUR_KEY_HERE' >> .env.local
# Run dev server
npm run dev
# Open http://localhost:3000
# Run tests
npm test
# Build for production
npm run build# Install Vercel CLI
npm i -g vercel
# Deploy
vercel --prod
# Set environment variables
vercel env add LLM_PROVIDER
vercel env add OPENAI_API_KEYSSE streaming chat with the configured LLM.
{ "messages": [{"role": "user", "content": "..."}], "topic": "optional" }Generate flashcards for a topic.
{ "topic": "Machine Learning", "count": 8, "difficulty": "mixed" }Generate a quiz.
{ "topic": "Calculus", "count": 5, "difficulty": "mixed" }SSE streaming content summarization.
{ "content": "paste text here...", "topic": "optional" }- Frontend: Next.js 14, React 18, TypeScript 5.4, Tailwind CSS 3.4
- State: Zustand (client-side)
- Animations: Framer Motion
- AI: any OpenAI-compatible LLM (OpenAI, OpenRouter, Ollama, Xiaomi MiMo)
- Auth: bearer token or
api-keyheader, selected automatically per provider - Streaming: Server-Sent Events (SSE) with optional
reasoning_content - Deploy: Vercel Edge Functions
studypal/
├── src/
│ ├── app/
│ │ ├── api/
│ │ │ ├── chat/route.ts # SSE streaming chat
│ │ │ ├── flashcards/route.ts # Flashcard generation
│ │ │ ├── quiz/route.ts # Quiz generation
│ │ │ └── summarize/route.ts # SSE streaming summary
│ │ ├── dashboard/page.tsx # Token stats
│ │ ├── flashcards/page.tsx # Flashcard viewer
│ │ ├── quiz/page.tsx # Quiz interface
│ │ ├── page.tsx # Main chat page
│ │ ├── layout.tsx # Root layout
│ │ └── globals.css # Tailwind + custom styles
│ ├── components/ # Reusable components
│ ├── hooks/
│ │ └── useTokenTracker.ts # Token consumption hook
│ └── lib/
│ ├── mimo.ts # OpenAI-compatible LLM client (SSE)
│ ├── prompts.ts # System prompts per feature
│ └── store.ts # Zustand state management
├── tests/ # Jest + React Testing Library
├── docs/ # Documentation
├── package.json
├── next.config.js
├── tailwind.config.js
├── tsconfig.json
└── README.md
MIT License — see LICENSE for details.
Provider-agnostic — runs on OpenAI, OpenRouter, Ollama, llama.cpp, Xiaomi MiMo, or any OpenAI-compatible /chat/completions endpoint.