ai-student-assistant

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ai-student-assistant

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Simple AI Chat bot with ollama Qwen model, I have implemented React frontend and python FastAPI for backend

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ZIP 다운로드

- - settings.json
- - main.cpython-314.pyc
- college_faq.txt
- main.py
- README.md
- requirements.txt
- - favicon.svg
  - icons.svg
- - App.jsx
  - index.css
  - main.jsx
- .gitignore
- .oxlintrc.json
- index.html
- package-lock.json
- package.json
- README.md
- vite.config.js
README.md

# CDN으로 사용하기

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// repository documentation

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A lightweight, local AI chatbot application built with a React frontend, a Python FastAPI backend, and powered by Ollama running the Qwen model. All components run completely offline and locally on your machine.

## Tech Stack

* **Frontend:** React, Vite / Create React App
* **Backend:** Python, FastAPI, Uvicorn, Requests / HTTPX
* **LLM Engine:** Ollama (Qwen model)

##Prerequisites
Ensure you have the following installed on your system:

* **Node.js** (v18+ recommended)
* **Python** (v3.10+ recommended)
* **Ollama** running locally

1. Set Up Ollama
Ensure Ollama is installed and pull the Qwen model:
  ollama pull qwen
  ollama serve

2. Set Up the Backend (FastAPI)
Navigate to the backend directory, create a virtual environment, and install dependencies:

cd backend
python -m venv venv
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

pip install -r requirements.txt

To run: uvicorn main:app --reload --port 8000

3. Set Up the Frontend (React)
Open a new terminal window, navigate to the frontend directory, and start the development server:

commands:
  cd frontend
  npm install
  npm run dev

ai-student-assistant

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# CDN으로 사용하기

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