BambooAI in 60 Minutes
TL;DR: Learn how to build intelligent data analysis systems with BambooAI in 60 minutes with hands-on examples covering multi-agent workflows, dataframe analysis, and dynamic code generation.
Tutorial in 30 Seconds#
BambooAI is a flexible framework for building intelligent systems made of multiple collaborating LLM agents that can reason over data and execute code.
Key capabilities:
- Multi-agent orchestration: Expert Selector, Code Generator, Error Corrector, and other specialized agents working together
- Data-aware reasoning: Dataframe Inspector and Analyst agents that understand and explore tabular data
- Dynamic code generation and execution: Planner and Code Generator agents that create and run Python code
- Multi-provider support: Works with OpenAI, Anthropic Claude, Google Gemini, Mistral, DeepSeek, and more
- Extensible architecture: Easy to add custom agents and integrate with external tools like Google Search
This tutorial's goal is to show you in 60 minutes:
- The basic API of BambooAI (a framework for building multi-agent AI systems that can reason over data)
- Concrete examples of using BambooAI to build specialized agents that analyze dataframes, generate code, and execute complex workflows
Official References#
Tutorial Content#
This tutorial includes all the code, notebooks, and Docker containers in tutorials/BambooAI
README.md: Instructions and setup for the tutorial environment- A Docker system to build and run the environment using our standardized approach
bambooai.API.ipynb: Tutorial notebook focusing on fundamental classes, methods, and API configurationsbambooai.example.ipynb: Complete real-world application workflow using BambooAI- Data exploration: Using Dataframe Inspector and Analyst agents to understand your data
- Dynamic planning: Planner agent that decomposes complex analysis tasks into steps
- Code generation: Code Generator agent that writes and proposes solutions
- Error handling: Error Corrector agent that fixes and improves generated code
bambooai.example.py: Stand-alone script version of the example for quick reference or automationbambooai_utils.py: Utility functions required by the example notebooks