📖 LLM Diary: 감정 분석 기반 다이어리 플랫폼

📌 Table of Contents

• 🔍 About the Project
• 🚀 Features
• 💻 Technologies
• 🛠 Getting Started
• 📌 Usage
• 📧 Contact
• 📜 License

🔍 About the Project

거대 언어 모델(LLM)을 사용하여 사용자의 일기를 바탕으로 감정을 분석하고, 사용자에게 감정 통계 및 맞춤형 상담을 제안하는 시스템.

🚀 Features

🏷️ROLE

• User
• Counselor
• Admin
• UserSupporter

📊 Emotion Analsis

• Model: koBERT.
• Fine-tuning Dataset: 감성대화 말뭉치
• Emotion : 분노, 슬픔, 불안, 상처, 당황, 기쁨

🏥 Counsel

• User can request a consultation, view connselor info
• Counselor can schedule, conduct, suggest consultations.

💻 Technologies

• Python 3.10.0
• Django 5.1.3
• tailwindcss 3.4.14
• transformers 4.47.0

🛠 Getting Started

0️⃣ Pre-requisite

The easiest way to start the LLMDiary is through docker compose. Before running this with the following commands, make sure that Docker and Docker Compose are installed on your machine:

1️⃣ Clone the Repository

git clone https://github.com/Jeon-Jinhyeok/LLMDiary.git
cd LLMDiary

2️⃣ Download the Model (Hugging Face)

sudo apt install git-lfs
git lfs clone https://huggingface.co/xxhyeok/koBERT-emotion

💡 참고: Hugging Face 모델 저장소에 접근하려면 SSH를 이용한 로그인 인증이 필요할 수 있습니다. Hugging Face SSH Key 설정 가이드 참고

3️⃣ Configure Environment Variables

• setup.env파일 수정

POSTGRES_DB=emotion_diary_db
POSTGRES_USER=admin
POSTGRES_PASSWORD=your-password
POSTGRES_HOST=db
POSTGRES_PORT=5432
DJANGO_SECRET_KEY=your-secret-key
DEBUG=False
ALLOWED_HOSTS=*

• setup.env 파일 적용

source ./setup.env

4️⃣ Run with Docker

docker compose up

5️⃣ Access the Web Interface

http://localhost:8000

📌 Usage

Login Page

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Diary List with Representative emotion

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Diary Details

• Diary Details with Result of Emotion Analysis and Recommended Action
• You can edit or delete the written diary.

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Home

• You can check latest Diaries in Home
• You can check emotional statistics for one week.

📧 Contact

• Jinhyeok, JEON - [email protected]
• Donggeon, KIM -

📜 License

Apache 2.0

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