Pin google-adk to 1.17.0 for YAML/Xlang precommit dependency resolution

[aIbrahiim]

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Summary of Changes

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This pull request updates the dependency management for the Python SDK by explicitly pinning the google-adk package to a specific version. This change ensures consistent behavior and stability for YAML and Xlang precommit workflows by preventing unexpected dependency resolution issues.

Highlights

• Dependency Pinning: Pinned the google-adk package to version 1.17.0 in the Python SDK setup configuration.

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[damccorm]

Is there a reason we need to pin these opentelemetry dependencies as well?

[aIbrahiim]

Yes as ADK fixes OTel versions, unpinned exporters were upgrading and conflicting with ADK’s SDK constraint, so i pined the trio to match

[aIbrahiim]

and pip failed with something like google-adk 1.17.0 wants opentelemetry-sdk exactly 1.37.x, but pip pulled opentelemetry-exporter-otlp-proto-http 1.40.x, which requires opentelemetry-sdk~=1.40

[damccorm]

Do you know where the opentelemetry requirement was coming from that installed 1.40.x? I would've expected that to be handled by pip

[aIbrahiim]

Pip was handling it, it ended in ResolutionImpossible / a hard conflict, not a wrong install and the 1.40.x side was coming from opentelemetry-exporter-otlp-proto-http (e.g. 1.40.0 wants opentelemetry-sdk~=1.40). google-adk meanwhile pins opentelemetry-sdk to 1.37.x, so theres no single version of the SDK that satisfies both so pip can’t merge those, it just fails unless we pin the exporter (and api) to the same minor as ADK’s SDK so nothing pulls 1.40.x into the graph

[damccorm]

Right, but what requires opentelemetry-exporter-otlp-proto-http?

[aIbrahiim]

I had to pin opentelemetry-exporter-otlp-proto-http because otherwise pip kept grabbing a newer 1.40.x build that wants opentelemetry-sdk~=1.40, while ADK only lines up with 1.37.x so resolution blew up unless i locked the exporter to the same minor as the SDK @damccorm

[aIbrahiim]

https://github.com/apache/beam/actions/runs/24147952925/job/70466786922?pr=38090 passed @derrickaw

[damccorm]

Why don't we need this anymore?

[aIbrahiim]

if you mean protobuf<4, i dropped that cap because with ADK/OTel in the same extra it fought protobuf>=5. ml_test no longer pulls ADK, so that specific cap isnt what unblocks resolution anymore, we can revisit a narrower cap separately if [gcp]+[ml_test] still allows it.

[damccorm]

Do you know where the opentelemetry requirement was coming from that installed 1.40.x? I would've expected that to be handled by pip

[damccorm]

If this is the case, we should just put this constraint in the adk portion of the extra and should keep the broader constraint here. This updates the core constraint which will be enforced on all users of beam

[damccorm]

I'm going to merge so that we can get this green/get it on the release branch. I think we can probably simplify this further though. If tensorflow-transform is the source of most of the pain, maybe we can scope it out for now and skip tests (or have a special suite/dependency set for tft only)

[damccorm]

Right, but what requires opentelemetry-exporter-otlp-proto-http?

[damccorm]

Actually, I noticed https://github.com/apache/beam/actions/runs/24153581426/job/70486866605?pr=38090 is failing because of this. Could you please take a look/fix?

[aIbrahiim]

@damccorm the failure in beam_PreCommit_Python_ML looks unrelated to the ADK pin changes as the install step succeeds and tests fail later in Milvus IT setup with pymilvus Fail connecting to server on localhost:46509: so it’s a Milvus container readiness/connectivity issue in py313-ml

[damccorm]

The original failure I linked to was:

The conflict is caused by:
    The user requested tenacity<9 and >=8.0.0
    google-adk 1.28.1 depends on tenacity<10.0.0 and >=9.0.0

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip to attempt to solve the dependency conflict

This was clearly an adk issue.

The new set of changes seems to be causing https://github.com/apache/beam/actions/runs/24182541038/job/70578913707 to fail all dataframes tests:

self = <apache_beam.runners.interactive.display.pipeline_graph.PipelineGraph object at 0x13ef82060>
vertex_dict = defaultdict(<class 'dict'>, {'"Create"': {}, 'pcoll5370': {'shape': 'circle', 'label': ''}, '"Map(<lambda at interacti...onymous_pcollection_5363630832': {'shape': 'circle'}, '"PlaceholderExpression[placeholder_DataFrame_5363640192]"': {}})
edge_dict = defaultdict(<class 'dict'>, {('"Create"', 'pcoll5370'): {}, ('pcoll5370', '"Map(<lambda at interactive_runner_test.py:...640192]"'): {}, ('"PlaceholderExpression[placeholder_DataFrame_5363640192]"', 'anonymous_pcollection_5363630832'): {}})
default_vertex_attrs = {'color': 'blue', 'fontcolor': 'blue', 'shape': 'box'}
default_edge_attrs = None

    def _construct_graph(
        self, vertex_dict, edge_dict, default_vertex_attrs, default_edge_attrs):
      """Constructs the pydot.Dot object for the pipeline graph.
    
      Args:
        vertex_dict: (Dict[str, Dict[str, str]]) maps vertex names to attributes
        edge_dict: (Dict[(str, str), Dict[str, str]]) maps vertex name pairs to
            attributes
        default_vertex_attrs: (Dict[str, str]) a dict of attributes
        default_edge_attrs: (Dict[str, str]) a dict of attributes
      """
      with self._lock:
        try:
          pydot.Dot()
        except NameError:
>         raise RuntimeError(
              'pydot is required for pipeline graph generation. '
              'Install it with: pip install pydot')
E         RuntimeError: pydot is required for pipeline graph generation. Install it with: pip install pydot

We need this to be fixed before we can merge