business-science /ai-data-science-team

An AI-powered data science team of agents to help you perform common data science tasks 10X faster.

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README

AI Data Science Team + AI Pipeline Studio


  
  
  
  


 AI Data Science Team

AI Data Science Team is a Python library of specialized agents for common data science workflows, plus a flagship app: AI Pipeline Studio. The Studio turns your work into a visual, reproducible pipeline, while the AI team handles data loading, cleaning, visualization, and modeling.

Status: Beta. Breaking changes may occur until 0.1.0.

Please ⭐ us on GitHub (it takes 2 seconds and means a lot).

 AI Pipeline Studio (Flagship App)

AI Pipeline Studio is the main example of the AI Data Science Team in action.

!AI Pipeline Studio

Highlights:
- Pipeline-first workspace: Visual Editor, Table, Chart, EDA, Code, Model, Predictions, MLflow
- Manual + AI steps with lineage and reproducible scripts
- Multi-dataset handling and merge workflows
- Project saves: metadata-only or full-data
- Storage footprint controls and rehydrate workflows

Run it:
bash
streamlit run apps/ai-pipeline-studio-app/app.py


Full app docs: apps/ai-pipeline-studio-app/README.md

 Quickstart

 Requirements
- Python 3.10+
- OpenAI API key (or Ollama for local models)

 Install the app and library
Clone the repo and install in editable mode:
bash
pip install -e .


 Run the AI Pipeline Studio app
bash
streamlit run apps/ai-pipeline-studio-app/app.py


 Library Overview

The repository includes both the AI Pipeline Studio app and the underlying AI Data Science Team library. The library provides agent building blocks and multi-agent workflows for:
- Data loading and inspection
- Cleaning, wrangling, and feature engineering
- Visualization and EDA
- Modeling and evaluation (H2O + MLflow tools)
- SQL database interaction

 Agents (Snapshot)

Agent examples live in examples/. Notable agents:
- Data Loader Tools Agent
- Data Wrangling Agent
- Data Cleaning Agent
- Data Visualization Agent
- EDA Tools Agent
- Feature Engineering Agent
- SQL Database Agent
- H2O ML Agent
- MLflow Tools Agent
- Multi-agent workflows (e.g., Pandas Data Analyst, SQL Data Analyst)
- Supervisor Agent (oversees other agents)
- Custom tools for data science tasks

 Apps

See all apps in apps/. Notable apps:
- AI Pipeline Studio: apps/ai-pipeline-studio-app/
- EDA Explorer App: apps/exploratory-copilot-app/
- Pandas Data Analyst App: apps/pandas-data-analyst-app/

 Use OpenAI

python
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
    model_name="gpt-4.1-mini",
)


 Use Ollama (Local LLM)

bash
ollama serve
ollama pull llama3.1:8b


python
from langchain_ollama import ChatOllama

llm = ChatOllama(
    model="llama3.1:8b",
)


 Next-Gen AI Agentic Workshop

Want to learn how to build AI agents and AI apps for real data science workflows? Join my next‑gen AI workshop:
https://learn.business-science.io/ai-register

Snapshot: 2026-11-04T14:00:00Z · Data license Apache-2.0 · JSON