Initial Release
Welcome to the Retrieval-Augmented Generation (RAG) workshop! ๐ This hands-on experience will teach you how to build intelligent AI applications that combine the power of Large Language Models with vector databases using InterSystems IRIS.
In this workshop, youโll become a RAG wizard by building three different types of AI applications:
This workshop is developed in Python ๐ (Jupyter Notebook) and InterSystems IRIS - because why settle for ordinary databases when you can have one that speaks vector? ๐
Make sure you have these tools ready for battle:
Time to bring this beast to life! ๐ช
1. Clone the repository:
git clone https://github.com/intersystems-ib/workshop-llm
cd workshop-llm
2. Build the image:
docker compose build
3. Launch the containers:
docker compose up -d
4. Access your AI playground:
superuser / SYSTransform boring medical documents into an intelligent assistant! Using Spanish medicine leaflets in https://github.com/intersystems-ib/workshop-llm/blob/main/./data, youโll build systems that can answer questions like a knowledgeable pharmacist. ๐
Choose your adventure:
๐ PDF-RAG-CloudLLM.ipynb - Cloud-powered RAG using Mistral AI
๐ PDF-RAG-LocalModels.ipynb - Privacy-first with local models

Meet Holefoods - a quirky company that sells food with holes in it! ๐ฉ (Creative, right?)
Build an intelligent SQL assistant that translates natural language into database queries. Ask questions like โHow many donuts did we sell in Europe last month?โ and watch the magic happen! โจ
Want to see the full power of AI agents in action? Check out this complete customer support agent built with smolagents and InterSystems IRIS:
๐ Customer Support AI Agent Demo
๐ Developer Community Article - Deep dive explanation
This demo showcases:
Ready to build your own AI applications? Set up a local Python environment:
For Mac/Linux users:
cd python
python3 -m venv .venv
source .venv/bin/activate
pip3 install -r requirements.txt
For Windows users:
cd python
python -m venv .venv
./.venv/Scripts/Activate.ps1
pip3 install -r requirements.txt
Create your API keys file:
# Create .env file
echo 'OPENAI_API_KEY="your-openai-key"' > .env
echo 'MISTRAL_API_KEY="your-mistral-key"' >> .env
Want to productionize your SQL skills? Try our FastAPI service based on the notebook:
cd python/holefoods_text2sql
fastapi dev main.py
๐ Explore the API: http://127.0.0.1:8000/docs
Experience a beautiful chat interface:
cd python/assistant
streamlit run chatbot.py
๐จ Chat away: http://localhost:8501
Challenge: Can you integrate the medicine leaflet logic into this assistant? ๐ค
Want to dive deeper into the InterSystems universe?
Youโre now equipped with the knowledge to build:
Go forth and create amazing AI applications! The only limit is your imagination! ๐โจ