feat(llmobs): make model name an optional argument for llm(), embedding()

[Yun-Kim]

This PR changes the model_name argument from LLMObs.llm(), LLMObs.embedding(), @llmobs.decorators.llm, @llmobs.decorators.embedding to being an optional argument with a default value of custom.

Previously, being a required argument resulted in slight onboarding friction due to breaking if users did not pass in a model name. By being optional and defaulting to a placeholder value, the llm/embedding() methods should be easier to use and generate spans.

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/feat-llmobs-model-name-optional-d916c96c7ace9375.yaml  @DataDog/apm-python
ddtrace/llmobs/_llmobs.py                                               @DataDog/ml-observability
ddtrace/llmobs/decorators.py                                            @DataDog/ml-observability
tests/llmobs/test_llmobs_decorators.py                                  @DataDog/ml-observability
tests/llmobs/test_llmobs_service.py                                     @DataDog/ml-observability

[pr-commenter]

Benchmarks

Benchmark execution time: 2024-10-21 19:09:03

Comparing candidate commit 330c120 in PR branch yunkim/llmobs-model-name-custom-default with baseline commit d45ebca in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 365 metrics, 53 unstable metrics.

[lievan]

Thoughts on defaulting to custom instead of custom_model ? for consistency with model provider