“LangSmith supports dataset-based experiments, trace evaluation and comparison across agent versions.”
“LangSmith supports dataset-based experiments, trace evaluation and comparison across agent versions.”
“- Agent tracing and debugging.”
“- Offline and online evaluations.”
“- Dataset and experiment comparisons.”
“- Regression detection.”
“· Particularly useful for LangChain and LangGraph workflows, but framework-agnostic.”
“For example, Braintrust supports versioned datasets and side-by-side experiment comparisons.”
“For example, Braintrust supports versioned datasets and side-by-side experiment comparisons.”
“- Dataset management.”
“- Experiment tracking.”
“- Scoring and evaluator comparisons.”
“- Performance and cost analysis.”
“· Useful for systematic evaluation and experiment management.”
“- Experiment and artifact tracking.”
“- Model version management.”
“- Evaluation metrics.”
“- Reproducibility and deployment tracking.”
“· Useful for integrating agent evaluations into broader ML workflows.”
“- Use Inspect AI for benchmark execution and custom evaluation tasks.”
“- Multi-step agent benchmarks.”
“- Custom datasets, solvers and scorers.”
“- Sandboxed execution.”
“- Repeated evaluation runs.”
“· Particularly useful for custom agent evaluations and research.”
“Inspect's architecture is especially useful to understand: an evaluation combines a dataset, a solver (the agent) and a scorer.”
“- AgentBench – evaluates agents across multiple interactive environments.”
“- WebArena – tests whether agents can complete realistic website tasks.”
“- τ-bench – evaluates tool use, policy adherence and consistency in realistic domains.”
“- SWE-bench – measures agents' ability to resolve real software issues.”
“- GAIA – tests multi-step reasoning, research and tool-use capabilities.”