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feat(llmobs): ragas evaluation framework integration #11939

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@lievan lievan commented Jan 14, 2025

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

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)

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  • 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

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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

@lievan lievan changed the title feat(llmobs): integration with the ragas evaluation framework feat(llmobs): ragas evaluation framework integration Jan 14, 2025
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Datadog Report

Branch report: evan.li/release-ragas
Commit report: f642a1c
Test service: dd-trace-py

✅ 0 Failed, 130 Passed, 1468 Skipped, 4m 46.34s Total duration (29m 10.85s time saved)

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pr-commenter bot commented Jan 14, 2025

Benchmarks

Benchmark execution time: 2025-01-17 19:03:15

Comparing candidate commit 867fd84 in PR branch evan.li/release-ragas with baseline commit 0e0848f in branch main.

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

@lievan lievan marked this pull request as ready for review January 17, 2025 18:19
@lievan lievan requested review from a team as code owners January 17, 2025 18:19
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