feat: Populate OpenFeature flag metadata from the evaluation reason

[kinyoklion]

Populates OpenFeature flag metadata with the LaunchDarkly specific parts of the evaluation result, so hooks (including the OpenTelemetry hook) can read them.

• Keys mirror the evaluation reason fields: variationIndex, inExperiment, ruleIndex, ruleId, prerequisiteKey, bigSegmentsStatus.
• Each key is omitted rather than default-valued when it does not apply, so a consumer can distinguish "not in an experiment" from "no information".
• Matches openfeature-java-server#56 and openfeature-dotnet-server#61; the naming is being defined in an sdk-specs spec.

No screenshots or staging preview apply - this is a server-side library change with no UI.

Implementation details

Requirements

• I have added test coverage for new or changed functionality
• I have followed the repository's pull request submission guidelines
• I have validated my changes against all supported platform versions

Describe the solution you've provided

ResolutionDetailsConverter now builds flag_metadata from the LaunchDarkly reason dictionary:

flag_metadata=self.__to_flag_metadata(reason, variation_index if not is_default else None)

Each reason field is read defensively with an isinstance check, since the reason is a plain dictionary, so a malformed reason cannot put an unexpected type into the metadata. variationIndex uses the same default-value check that already gates variant.

The README gains a "Flag Metadata" section documenting the keys.

Describe alternatives you've considered

Passing the whole reason dictionary through as a single reason metadata entry would be closer to the LaunchDarkly shape, but FlagMetadata values are scalars, so the flat keys are the only available shape.

Additional context

poetry run pytest
poetry run mypy ld_openfeature tests

All tests pass, including 7 new cases covering each key and the omissions. make test/make lint currently fail on poetry install on main as well, because poetry.lock is out of date relative to pyproject.toml - unrelated to this change.

@cursor review

Link to Devin session: https://app.devin.ai/sessions/0c452d209ec54b068ba120b4c92b8f6c
Requested by: @kinyoklion

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