docs(deepeval): add upstream adapter documentation - #95
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Signed-off-by: Rui Vieira <ruidevieira@googlemail.com>
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📝 WalkthroughWalkthroughAdds DeepEval adapter documentation covering overview, configuration, benchmarks, examples, local execution, MLflow integration, and sidebar navigation. ChangesDeepEval adapter documentation
Estimated code review effort: 3 (Moderate) | ~20 minutes Possibly related PRs
Suggested labels: Suggested reviewers: 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 2
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Verify each finding against current code. Fix only still-valid issues, skip the
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Inline comments:
In `@src/content/docs/adapters/deepeval/configuration.md`:
- Around line 26-28: Update the JobSpec example’s "parameters" value in the
configuration documentation to valid JSON by replacing the inline comment with
an empty object or a concrete parameter entry; preserve the surrounding example
structure.
In `@src/content/docs/adapters/deepeval/examples.mdx`:
- Around line 277-291: Update the documented EvalHub job submission example to
configure MLflow using the top-level JobSpec experiment_name field rather than
passing experiment_name through DeepEval-specific --param values. Remove the
CLI-side MLFLOW_TRACKING_URI export and note or demonstrate that cluster-mode
tracking URI configuration is supplied by the EvalHub server/sidecar.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro Plus
Run ID: c6eab020-427c-47b6-b84f-185fa517242a
📒 Files selected for processing (5)
astro.config.mjssrc/content/docs/adapters/deepeval/benchmarks.mdsrc/content/docs/adapters/deepeval/configuration.mdsrc/content/docs/adapters/deepeval/examples.mdxsrc/content/docs/adapters/deepeval/index.mdx
What and why
Creates upstream documentation for the DeepEval adapter on eval-hub.github.io. Covers: usage guide, benchmark reference, dataset format schemas, MLflow integration, and configuration reference.
Type
Testing
Pages added
adapters/deepeval/— Overview with EvalHub-first quick start (SDK CLI, Python SDK, REST API tabs)adapters/deepeval/configuration— JobSpec structure, all parameters grouped by concern, MLflow integration, environment variablesadapters/deepeval/benchmarks— All 8 benchmarks (5 single-turn, 3 multi-turn) with required columns, output metrics, and dataset format reference (CSV / JSONL / JSON)adapters/deepeval/examples— Worked examples: faithfulness, hallucination detection, multi-turn role adherence, conversation completeness, local testing, MLflow-tracked evaluationSummary by CodeRabbit