A no-code/low-code tool to explore the capabilities of vector embeddings in InterSystems IRIS DB.
Connectors let load data from files as vector embeddings into IRIS DB
Playground let users explore different retrieval channels on the vector embeddings reside in IRIS DB
https://iris-ai-studio.vercel.app/
Designed and developed only for web interface, not compatible with mobile
Step 1: Setup the Instance details and API Keys in settings
Step 2: Through connectors load data into IRIS DB
Step 3: In playground, explore different retrieval options
Frontend: VueJS, TailwindCSS, Flowbite
Backend: Python, Flask
Database: InterSystems IRIS
Frameworks/Libraries/Services: Llama-Index, SQLalchemy-iris, OpenAI, Cohere
Infrastructure: Vercel (frontend hosting), Render (backend hosting)
Simply execute the script using the following command.
./build.sh
If any permission issue while executing the script, allow it through chmod +x build.sh
Access the UI at http://localhost:5173
Access the APIs at http://127.0.0.1:8000
Credentials for Local InterSystems IRIS Instance
username: demo
password: demo
hostname: localhost
port: 1972
namespace: USER
Follow the instructions to spin off a Cloud InterSystems Community Edition
Once you have the credentials, in the frontend application’s settings page the credentials can be added. You may add more than one instance and choose to use whichever one for data ingestion or retrieval process independently.
You may follow the following instructions to individually run the frontend and backend
Start from application’s root directory
cd frontend
npm i
npm run dev
Start from application’s root directory
cd backend
pip install -r requirements.txt
gunicorn app:app
Access the APIs at http://127.0.0.1:8000
iris-ai-studio/
├──frontend
│ ├── src/
│ ├── .env
│ └── ...
├── backend/
│ └── app.py
│ ├── data_loader.py
│ ├── chat_llama.py
│ ├── query_llama.py
│ ├── similarity_llama.py
│ ├── reco_llama.py
│ ├── requirements.txt
│ │ └── ...
├── assets/
├── README.md
└── https://github.com/ikram-shah/iris-ai-studio/blob/main/LICENSE
This project is licensed under the MIT License.
You can find the full text of the license in the https://github.com/ikram-shah/iris-ai-studio/blob/main/LICENSE file.