Nice Classification with RAG

Requirements

• Python: Runtime Platform
• OpenAI: Embedding of the text & Inference of the class
• Qdrant: Vector Database

Prepare the environment

1. Set up virtual environment for runtime
   • Linux or Macos

     python -m venv .venv
     source .venv/bin/activate
     pip install -r requirements.txt

   • Windows

     python -m venv .venv
     .venv/Scripts/activate
     pip install -r requirements.txt

2. Configure the environment variables
   • Create a new .env file.
   • Edit .env file

     OPENAI_API_KEY="OPENAI_API_KEY"
     OPENAI_ORGANIZATION_KEY="OPENAI_ORGANIZATION_KEY"
     
     QDRANT_API_KEY="QDRANT_API_KEY"
     QDRANT_CLUSTER="QDRANT_CLUSTER"

How to prepare data

1. Parse XML files to prepare the data

   python xml_parse.py

2. Prepare the Qdrant and prepare the vector database

   python data_retrieve.py data/output.json

Run the server

1. Run the flask server

   python -m flask run

2. Results