feat(llmobs): introduce ragas eval integration

[lievan]

Publicize the RAGAS integration

RAGAS is an evaluation framework for RAG Applications. The integration supports evaluating LLM inferences with three RAGAS metrics

• faithfulness
• answer relevancy
• context precision

dupe of #11939 to get in ddtrace 3.0

Checklist

• PR author has checked that all the criteria below are met
• The PR description includes an overview of the change
• The PR description articulates the motivation for the change
• The change includes tests OR the PR description describes a testing strategy
• The PR description notes risks associated with the change, if any
• Newly-added code is easy to change
• The change follows the library release note guidelines
• The change includes or references documentation updates if necessary
• Backport labels are set (if applicable)

Reviewer Checklist

• Reviewer has checked that all the criteria below are met
• Title is accurate
• All changes are related to the pull request's stated goal
• Avoids breaking API changes
• Testing strategy adequately addresses listed risks
• Newly-added code is easy to change
• Release note makes sense to a user of the library
• If necessary, author has acknowledged and discussed the performance implications of this PR as reported in the benchmarks PR comment
• Backport labels are set in a manner that is consistent with the release branch maintenance policy

[github-actions]

CODEOWNERS have been resolved as:

releasenotes/notes/ragas-integration-a81b696757c0e7a5.yaml              @DataDog/apm-python
ddtrace/llmobs/_evaluators/runner.py                                    @DataDog/ml-observability
ddtrace/llmobs/_evaluators/sampler.py                                   @DataDog/ml-observability
tests/llmobs/test_llmobs_evaluator_runner.py                            @DataDog/ml-observability
tests/llmobs/test_llmobs_ragas_evaluators.py                            @DataDog/ml-observability
tests/llmobs/test_llmobs_service.py                                     @DataDog/ml-observability

[datadog-dd-trace-py-rkomorn]

Datadog Report

Branch report: evan.li/release-ragas-3.0
Commit report: 092306e
Test service: dd-trace-py

✅ 0 Failed, 130 Passed, 1468 Skipped, 5m 5.47s Total duration (35m 38.84s time saved)

[pr-commenter]

Benchmarks

Benchmark execution time: 2025-01-31 17:27:51

Comparing candidate commit 7fbfc76 in PR branch evan.li/release-ragas-3.0 with baseline commit 4ebedf0 in branch 3.x-staging.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 394 metrics, 2 unstable metrics.

[Kyle-Verhoog]

small thing, good to go once addressed!