Framework for evaluating and improving agents
- evals
- rl-environments
- terminal-bench
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Framework for evaluating and improving agents
The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.
This is the official repo for paper InteractiveWorld A Verifiable Human-Centric Environment for Building Better Interactive MLLM Assistants
Fault-injected tool environments with side-effect grading for evaluating and post-training LLM agents