feat(llmobs): support annotating primitive prompt templates

[lievan]

Support the ability for users to annotate prompt template data via the annotate function.

Users can pass in two types of objects as a prompt

• a dictionary that adheres to our Prompt typed dict
• importing ddtrace.llmobs.utils.Prompt and passing in the Prompt typed dict

Follow up: be able to pass in prompt template data to annotation_context

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

[datadog-dd-trace-py-rkomorn]

Datadog Report

Branch report: evan.li/prompt-v2
Commit report: 36fe0e1
Test service: dd-trace-py

✅ 0 Failed, 100 Passed, 850 Skipped, 1m 15.6s Total duration (13m 18.84s time saved)

[github-actions]

CODEOWNERS have been resolved as:

releasenotes/notes/support-prompt-annotations-b8e406261197f61a.yaml     @DataDog/apm-python
ddtrace/llmobs/_constants.py                                            @DataDog/ml-observability
ddtrace/llmobs/_llmobs.py                                               @DataDog/ml-observability
ddtrace/llmobs/_trace_processor.py                                      @DataDog/ml-observability
ddtrace/llmobs/_utils.py                                                @DataDog/ml-observability
ddtrace/llmobs/utils.py                                                 @DataDog/ml-observability
tests/llmobs/test_llmobs_service.py                                     @DataDog/ml-observability
tests/llmobs/test_llmobs_trace_processor.py                             @DataDog/ml-observability

[pr-commenter]

Benchmarks

Benchmark execution time: 2024-09-20 12:36:06

Comparing candidate commit 370758e in PR branch evan.li/prompt-v2 with baseline commit 0d44103 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 356 metrics, 48 unstable metrics.