feat(AIC-3363): Support inline datasets

[aknight-ld]

Server side support of inline datasets is in flight; this PR covers the corresponding SDK work to pass in dataset rows defined from code.

Sizable test suite added in, testing underway to ensure we are matching the server.

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Note

Overview
Adds inline datasets so init_evaluations().run() accepts either a hosted dataset key or caller-supplied rows=[DatasetRow(...)], with exactly one required and no dataset API traffic for inline runs.

Inline rows are normalized through shared _render_row (templates, injected input/expected_output in variables) without mutating caller objects. Pre-flight validation covers row count (10k), unique non-negative row_index, JSON-serializable variables/metadata, and rendered UTF-8 byte limits (1 MiB per field) so bad payloads fail before generation or silent event loss.

Generation events for inline runs omit datasetId/datasetKey (five-field eventId) and include row input, expectedOutput, variables, and metadata; hosted runs keep excluding row bodies. Run creation sends {"source": "api"} without datasetId when inline. Criterion payloads treat dataset identifiers as optional.

Docs in packages/ai and packages/client READMEs plus agents.md describe the new mode and pitfalls. A large test_evaluations_run.py suite covers API shapes, events, rendering, limits, and validation errors.

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