rohanbhati0912/study-assistant：多智能体 AI 学习助手

A multi-agent AI study app that helps students plan learning, generate personalized quizzes, create roadmaps, and get tutoring support with uploaded documents.

Live demo

https://study-assistant-jyv1.onrender.com

About

Study Assistant is an AI-powered study companion built to help students learn faster, stay organized, and study with more confidence. It combines multiple specialized agents for student analysis, learning-path planning, quiz generation, tutoring, and document-based Q&A, giving users a complete digital study experience in one place.

This project is designed for students, learners, and academic users who want a more personalized and structured way to revise concepts, prepare for exams, and work through course materials. It brings together AI guidance, smart recommendations, and interactive learning tools in a simple Streamlit interface.

The app is currently live and ready to use at the Render demo link above, making it easy to explore the assistant without setting up a local environment first.

Overview

Study Assistant is a Streamlit-based learning platform built around multiple specialized AI agents. It helps students:

• analyze their current knowledge level
• define goals and study constraints
• generate personalized learning roadmaps
• find relevant learning resources
• create quizzes and explanations
• ask follow-up questions through an AI tutor
• search and answer questions from uploaded study material using RAG

Features

• Personalized student analysis
• Learning roadmap generation
• Smart resource recommendations
• Adaptive quiz generation
• AI tutoring experience
• Document Q&A with uploaded PDFs and notes
• Multi-provider AI support with Groq and OpenAI

Tech stack

• Python 3.12
• Streamlit
• LangChain
• ChromaDB
• Phidata
• Groq
• OpenAI

Project structure

study-assistant/
├── app.py
├── agent_handler.py
├── config.py
├── prompts.yaml
├── rag_helper.py
├── study_agents.py
├── requirements.txt
├── runtime.txt
├── .env.example
├── README.md
├── .streamlit/
└── .venv312/

Setup

1) Clone the repository

git clone https://github.com/rohanbhati0912/study-assistant.git
cd study-assistant

2) Create a virtual environment

python3.12 -m venv .venv312
source .venv312/bin/activate

3) Install dependencies

pip install --upgrade pip
pip install -r requirements.txt

4) Add environment variables

Create a .env file in the root folder:

GROQ_API_KEY=your_groq_key
OPENAI_API_KEY=your_openai_key

You can also copy the example file:

cp .env.example .env

Run locally

streamlit run app.py

If needed, run with the venv Python directly:

.venv312/bin/python -m streamlit run app.py

Render deployment

This project is set up for Render.

Create runtime.txt

python-3.12.13

Render build settings

Build command:

pip install -r requirements.txt

Start command:

streamlit run app.py --server.address 0.0.0.0 --server.port $PORT

Environment variables to add in Render:

• GROQ_API_KEY
• OPENAI_API_KEY

GitHub push

If the repo already exists:

git add .
git commit -m "Initial commit"
git push -u origin main

If the remote is not set:

git remote set-url origin https://github.com/rohanbhati0912/study-assistant.git
git add .
git commit -m "Initial commit"
git push -u origin main

Troubleshooting

Python version error

Use Python 3.12. Do not use Python 3.14 for this project.

Missing API keys

Ensure your .env file exists and contains valid keys.

Streamlit not found

python3.12 -m streamlit run app.py

Dependency issues

pip install -r requirements.txt

Notes

• The deployment is live on Render.
• Keep API keys in environment variables instead of hardcoding them.
• The app is designed for educational and study-use scenarios.

Running tests

Activate your virtual environment, then install the project and test dependencies:

python -m pip install -e .
python -m pip install pytest

Run the test suite:

python -m pytest -q

Tests should run without real AI API credentials. GitHub Actions runs the same test command on pushes and pull requests.

Author

Rohan Bhati