StudyMate AI is a full-stack, intelligent study assistant that empowers students to interact with their study materials, ask questions, and receive real-time, context-aware help powered by advanced LLMs.
-
Customizable Prompts:
Define assistant behavior with a system prompt and interact naturally via user prompts. -
LLM Tuning:
Adjust temperature, top-p, and max tokens for tailored responses. -
Structured Output:
Receive summaries, comparisons, and explanations in bullet points, tables, or JSON. -
Function Calling:
Trigger backend functions for flashcard generation, reminders, and quiz creation. -
Retrieval-Augmented Generation (RAG):
Leverage a vector database to fetch relevant information from notes, PDFs, or course materials for highly contextual answers.
- Frontend: React.js, Tailwind CSS
- Backend: Node.js, Express.js
- Database: MongoDB, Vector DB (Pinecone, FAISS, etc.)
- AI Integration: OpenAI / LLM API
Studymate-AI-Your-Personalized-Learning-Assistant/
ββ backend/
β ββ .env.example
β ββ package.json
β ββ src/
β ββ server.js
β ββ llm.js
β ββ routes/
β β ββ chat.js
β β ββ rag.js
β ββ rag/
β β ββ store.js
β β ββ ingest.js
β ββ utils/
β β ββ similarity.js
β ββ tools/
β ββ functions.js
β ββ test/
β ββ eval.js
ββ README.md
- Upload Notes: Convert notes to vector embeddings and store in the vector DB.
- Ask Questions: Combine system prompt with RAG-fetched context for structured responses.
- Trigger Functions: Use commands like
generateFlashcards(),setReminder(), orgenerateQuiz(). - Display Output: Present results in a clear, structured format for easy understanding.
{
"Topic": "Supervised vs Unsupervised Learning",
"Comparison": [
{
"Aspect": "Definition",
"Supervised": "Learns from labeled data",
"Unsupervised": "Learns from unlabeled data"
},
{
"Aspect": "Example",
"Supervised": "Spam detection",
"Unsupervised": "Customer segmentation"
}
]
}Empower your learning with StudyMate AI β your personalized, intelligent study