@icodenet/eval-dashboards is runner-agnostic and artifact-first.
If you can export rows and map them into eval-report/v1, you can use the same lint, check, report, history, and publish flow.
eval-dashboards import --from=promptfoo --input=./promptfoo.json --out=.evals_output/promptfoo.json
eval-dashboards import --from=deepeval --input=./deepeval.json --out=.evals_output/deepeval.json
eval-dashboards import --from=openevals --input=./agentevals-like.json --out=.evals_output/openevals.json
eval-dashboards import --from=otel-genai --input=./otel-genai-spans.json --out=.evals_output/otel-genai.json(openevals is an alias for the AgentEvals adapter.)
- Promptfoo
- DeepEval
- OpenAI eval surfaces / AgentEvals
- Anthropic eval methodology
- Langfuse
- W&B Weave
- Arize Phoenix
- Braintrust
- Ragas
- TruLens
- Patronus
- Trace/observability stacks
- OpenTelemetry GenAI evaluation events
Before adding or changing an integration, check: