Allow users to omit any traces they want by returning none in the
user_span_processor method.

Motivation:
I am trying to prevent some auto traces from cluttering my Datadog
observability dashboards. These traces create noise and make it harder
to focus on the more critical traces. My LLM observability overview is
filled with what is clustered as empty input which is incorrect. e.g.
all embedding traces are are just a spammer.

To do that, I am using the new span_processor, and the new way to omit
specific spans, will be to return null by the relevant span processor.

I have added a test for that.

The only risk is that there is no indication that span was omitted but I
was afraid that a debug log would be too spammy. But please let me know
if that will help. Also there are some telemetric collected about sent
span which might also need to be changed, will be great to hear your
thoughts

Co-authored-by: amirbenami <amir@linxsecurity.io>

Annotates LangGraph agents (compiled state graphs, even those created
through `create_react_agent`) with the following agent metadata
information:

- name (always)
- tools (always - best effort, depending on the presence of `ToolNode`s
within the agent)
- instructions (if done through `create_react_agent`)
- model name, provider, & settings (if done through
`create_react_agent`)
- handoffs (always - assuming the agent is directly a part of a
supergraph)
- framework (always)
- dependencies (since state should always be passed in, always)
- max_iterations (always, defaulting to 25 if not provided explicitly)

Additionally, to help accomplish this, we patch the `create_react_agent`
function to record agent manifest data on agent instance creation,
should it be invoked. The means of doing this is a bit strange, as it is
in completely different submodule (`langgraph.prebuilt`), and it
required me to do what I think are some pretty not normal things for
patching 😅 so, happy to discuss/change as needed!

MLOB-3102

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Remove importlib_metadata dependency since it is no longer needed.
Support for Python 3.7 has been dropped, and dd-trace-py now requires
Python 3.8 or later, which includes importlib.metadata in the standard
library.


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---------

Co-authored-by: Munir Abdinur <munir_abdinur@hotmail.com>
Co-authored-by: Munir Abdinur <munir.abdinur@datadoghq.com>

This PR introduces:
- remove of the `_appsec_processor` in the tracer. The appsec processor
is now part of the list of regular processors. This fixes several
problems.
- change the logic order of how appsec is enabled and loaded

This is removing 2 static import cycles, only 2 left (none with appsec).

Context: Before that PR, the appsec product was loaded through the
tracer, by creating an instance of AppSecSpanProcessor. After that PR,
the appsec product or the remote config layer will register the
AppSecSpanProcessor into the list of regular span processors of the
tracer.


**Bonus**:
As the appsec processor is not reset anymore at fork time by the respawn
of the tracer (because it does not depend on the tracer object anymore),
it looks like it's also fixing the gap time we could have where appsec
was back to factory setting at work respawn time.

APPSEC-57505

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See builds here


https://app.readthedocs.org/projects/ddtrace/builds/?version__slug=taegyunkim-native-cargo-home

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…nGroup (#14250)

## Description

When an Appsec `BlockingException` is raised within a fastapi
middleware, it can be aggregated and nested in a `BaseExceptionGroup`
multiple levels deep. The behaviour occurs when using http middlewares.

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fixing issue #14258

Also little change to the django app for threats tests to have a
regression test.

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---------

Co-authored-by: Brett Langdon <brett.langdon@datadoghq.com>

Follows #14248 and
DataDog/images#7477

Also adds parallelism to `azure_functions` tests since they were
finishing right around the 20 minute timeout following the upgrade of
`azure-functions-core-tools.

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CI Visibility: Fix for a bug introduced in
#14115 where session tags
would not have the proper count of tests skipped by ITR, counting the
suite number instead when ITR is configured at suite level skipping.

Regression tests added for both suite level skipping and test level
skipping.

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Update celery lockfiles and dependency package lockfiles.
This performs the following updates:
1) Some celery lockfiles use celery `latest`. This will update celery
and dependencies.
2) Some celery lockfiles use a pinned (non-latest) version of celery,
but require the `latest` version of another package. This will update
all such packages.

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Co-authored-by: quinna-h <175135214+quinna-h@users.noreply.github.com>

Broken out from #14361 

`ddtrace.trace.Pin` is being deprecated

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Broken out from #14361 

`ddtrace.trace.Pin` is being deprecated

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Following #14113, this PR
adds endpoint discovery at startup for Flask.
Also:
- add blueprints in Flask testing app for threat tests (to make sure
blueprints are properly supported)
- Improve endpoint discovery test to ensure that we get the expected
endpoint reported
- Moved endpoint_collection away from asm settings to neutral file
endpoints as this is a feature not directly related to security.
- Kept flag enabling/disabling this feature inside asm settings as
security team will maintain this feature.

This was also tested on new endpoint discovery system tests.

APPSEC-58374

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There isn't much need for the Pin API anymore, we generally encourage
environment variable or backend controlled configuration.

The big benefit of deprecating and removing this API is because of the
performance impact it has on integrations, the operations to check for
Pins is very slow, when generally it is expected people to use sane
defaults or configure once via env variables.

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## Description

This PR fixes the tracer flare when `DD_TRACE_AGENT_URL` is not set.
`ddtrace.config._trace_agent_url` is `None` when not set, which leads to
`Failed to send tracer flare to Zendesk ticket XXXXXXXXX: Unsupported
protocol 'b''' in intake URL 'None'. Must be one of: http, https, unix`
when sending a flare.

This PR makes sure to use the default.

## Motivation

Making tracer flares for Python work again

## Testing strategy
- Create a VM
- Install the agent
- Install the tracer with SSI
- Create a sample Flask app
- Start it with `DD_TRACE_DEBUG=true`
- Go to the Datadog UI & trigger a flare for your host (no need to force
debug logs)
- After a few minutes a Zendesk ticket should be created and contain
your tracer flare
- You should see a log starting with `Successfully sent the flare to
Zendesk ticket` 

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---------

Co-authored-by: Brett Langdon <brett.langdon@datadoghq.com>

This PR adds improved tracking of tool results and definitions to the
LLMObs OpenAI integration

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---------

Co-authored-by: Yun Kim <35776586+Yun-Kim@users.noreply.github.com>

…otfile

…-suites