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title: K-Recipe2Vec API
emoji: π³
colorFrom: yellow
colorTo: red
sdk: docker
pinned: false
---
# π³ K-Recipe2Vec
AI κΈ°λ° νμ μμ¬λ£ λ체 μΆμ² μλΉμ€
## π Overview
νκ΅ μ리μμ μμ¬λ£λ₯Ό λ체ν μ μλ μ¬λ£λ₯Ό AIκ° μΆμ²ν΄μ£Όλ μΉ μλΉμ€μ
λλ€.
Doc2Vecκ³Ό Word2Vec λͺ¨λΈμ νμ©νμ¬ μμ¬λ£ κ°μ μλ―Έμ μ μ¬λλ₯Ό λΆμν©λλ€.
## π Demo
π **[Live Demo](https://korea-recipe-ai.streamlit.app/)** - Streamlit Cloud λ°°ν¬
## β¨ Features
- **π₯¬ μμ¬λ£ λ체 μΆμ²**: μλ μ¬λ£μ λν μ μ¬ μ¬λ£ μΆμ²
- **π 3D μκ°ν**: PCA κΈ°λ° μ¬λ£ λ²‘ν° κ³΅κ° μκ°ν
- **π° κ°κ²© μ 보**: μ¬λ£λ³ κ°κ²© μ 보 μ 곡
- **βοΈ μλν΄λΌμ°λ**: μΆμ² μ¬λ£ μκ°ν
## π οΈ Tech Stack
| Category | Technologies |
|----------|-------------|
| **Frontend** | Streamlit |
| **ML Models** | Gensim (Doc2Vec, Word2Vec) |
| **Data Processing** | Pandas, NumPy |
| **Visualization** | Plotly, Matplotlib, WordCloud |
| **Database** | Supabase |
| **Deployment** | Streamlit Cloud |
## π Project Structure
```
k-recipe2vec/
βββ app.py # Main Streamlit application
βββ logic.py # Core recommendation logic (if exists)
βββ requirements.txt # Python dependencies
βββ d2v.model # Doc2Vec trained model
βββ w2v.model # Word2Vec trained model
βββ price_rank.csv # Price data
βββ stats.pkl # Preprocessed statistics
```
## π Getting Started
### Prerequisites
- Python 3.8+
- pip
### Installation
```bash
# Clone the repository
git clone https://github.com/nneans/k-recipe2vec.git
cd k-recipe2vec
# Install dependencies
pip install -r requirements.txt
# Run the app
streamlit run src/app.py
```
## π Model Information
### Doc2Vec Model
- νκ΅ λ μνΌ λ°μ΄ν° κΈ°λ° νμ΅
- λ μνΌ λ¨μ λ¬Έμ μλ² λ©
### Word2Vec Model
- μμ¬λ£ κ° μλ―Έμ μ μ¬λ νμ΅
- λ체 κ°λ₯ν μ¬λ£ μΆμ²μ νμ©
## π€ Contributing
λ²κ·Έ 리ν¬νΈ, κΈ°λ₯ μ μ, PR νμν©λλ€!
## π License
MIT License
## π€ Author
**Mingyun Kang**
- GitHub: [@nneans](https://github.com/nneans)
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