RAG based chatbot to deal with school rules related questions of Seoul National University.
Done as a part of Creative Integrated Design2 Class.
- Install dependencies
pip install -r requirements.txt
-
Install Milvus standalone based on your environment. Details are given here.
-
Prepare the database
cd snu_milvus
python init_db.py -n “snu_milvus_final”
python insert_embedding.py -n “snu_milvus_final” -I “output_final.csv” -b “4” -d “cuda”
-
Move and run
llm_inference.ipynb
in your own colab environment -
Run the backend
- You must set replace
COLAB_URI
ofrag_backend/rag/views.py
based on thengrok
url that you received from thellm_inference.ipynb
- You must set replace
cd rag_backend
python manage.py runserver
- Run the frontend
cd rag_frontend
npm install
npm start