feat(llmobs): support in-code config for llmobs [backport 2.9]

[github-actions]

Backport bf858f7 from #9172 to 2.9.

Support in-code configuration for LLMObs users, to enable LLMObs and specify the following configurations that currently require environment variable configuration.

• ml_app
• list of integrations to patch (will patch all LLMObs integrations by default)
• dd_llmobs_no_apm (turn off APM, telemetry, remote config, metrics)
• DD site, DD env, DD service (will override config/env vars)

from ddtrace.llmobs import LLMObs

LLMObs.enable(
    ml_app="comms/langchain", 
    integrations=["openai"],
    llmobs_agentless_enabled=True,
    # api_key =...
    # site=...
    # env=...
    # service=...
    # _tracer=None
)

Allowing in-code setup also improves the dev experience for people tracing experimental apps with LLMObs. It also abstracts away a long list of environment variables non-APM customers are required to set to turn off all APM related features.

This PR should not break any previous way of setting up the Python SDK (e.g. using env vars and ddtrace-run).

Arguments passed to enable() should take precedence over environment variables, with the exception of DD_LLMOBS_ENABLED.

This PR also does a couple minor things:

• If DD_LLMOBS_NO_APM env var is detected or configured through LLMObs.enable(), the OpenAI and LangChain integrations will disable submitting metrics unless the corresponding env vars DD_{OPENAI,LANGCHAIN}_METRICS_ENABLED is set to True.
• We also automatically disable both telemetry writer and remote config pollers if DD_LLMOBS_NO_APM is detected or configured through LLMObs.enable().
• We automatically patch the LLMObs integrations on LLMObs.enable().
• Removes all LLMObs.enable() references in individual integration patch code (openai, botocore, langchain)

Note:

• This change (only for LLMObs users) will override config.service, config.env if these are passed in to LLMObs.enable().
• If a user runs via ddtrace-run, they cannot use LLMObs.enable() to configure their settings.

Checklist

• Change(s) are motivated and described in the PR description
• Testing strategy is described if automated tests are not included in the PR
• Risks are described (performance impact, potential for breakage, maintainability)
• Change is maintainable (easy to change, telemetry, documentation)
• Library release note guidelines are followed or label changelog/no-changelog is set
• Documentation is included (in-code, generated user docs, public corp docs)
• Backport labels are set (if applicable)
• If this PR changes the public interface, I've notified @DataDog/apm-tees.

Reviewer Checklist

• Title is accurate
• All changes are related to the pull request's stated goal
• Description motivates each change
• Avoids breaking API changes
• Testing strategy adequately addresses listed risks
• Change is maintainable (easy to change, telemetry, documentation)
• Release note makes sense to a user of the library
• 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: backport-9172-to-2.9
Commit report: d051904
Test service: dd-trace-py

✅ 0 Failed, 3531 Passed, 165 Skipped, 1h 33m 23.32s Total duration (37.1s time saved)