Bloom is an open-source evaluation framework designed for the automated assessment of behaviors in Large Language Models (LLMs). Built as a scaffolded evaluation system, Bloom enables researchers and developers to define precise evaluation configurations—referred to as seeds—that specify target behaviors, example transcripts, and the interaction patterns to be tested.
Key Features
- Open-source framework for LLM behavior evaluation
- Scaffolded evaluation system using configurable “seeds”
- Definition of target behaviors and evaluation criteria
- Support for exemplary transcripts and interaction types
- Automated and repeatable evaluation workflows
- Suitable for research, benchmarking, and testing
Pros
- Transparent and customizable evaluation process
- Encourages reproducible LLM behavior testing
- Flexible configuration for diverse evaluation goals
- Useful for alignment, safety, and performance analysis
- Open-source and community-extensible
Cons
- Requires technical expertise to configure and use
- Not designed for non-technical users
- Evaluation quality depends on well-defined seeds
Who Is This Tool For?
- AI researchers and ML engineers
- LLM developers and evaluators
- Alignment and safety research teams
- Organizations benchmarking language models
Pricing Packages
- Free & Open Source: Available under an open-source license
