YAshhh29 commented on code in PR #71575:
URL: https://github.com/apache/airflow/pull/71575#discussion_r4112452294
##########
providers/common/ai/tests/unit/common/ai/durable/test_fingerprint.py:
##########
@@ -210,3 +224,199 @@ def test_arg_order_does_not_matter(self):
assert fingerprint_tool_call("t", {"a": 1, "b": 2}, "id1") ==
fingerprint_tool_call(
"t", {"b": 2, "a": 1}, "id1"
)
+
+
+class TestPydanticNativeValues:
+ """Values that are not JSON types but hash the same on every attempt must
still fingerprint.
+
+ Tool arguments reach ``fingerprint_tool_call`` already coerced by
pydantic, and
+ ``tool_choice`` accepts a dataclass while genuinely affecting the
response, so it
+ cannot be stripped as transport-only. Since a step that cannot be
fingerprinted is
+ no longer cached at all, refusing these values would stop an ordinary
typed tool
+ from ever being cached.
+ """
+
+ def test_datetime_tool_argument_fingerprints(self):
+ when = datetime.datetime(2026, 1, 1, tzinfo=datetime.timezone.utc)
+
+ assert fingerprint_tool_call("t", {"when": when}, "id1") is not None
+
+ def test_decimal_tool_argument_fingerprints(self):
+ assert fingerprint_tool_call("t", {"amount": Decimal("10.5")}, "id1")
is not None
+
+ def test_datetime_tool_argument_is_stable_and_distinguishing(self):
+ early = datetime.datetime(2026, 1, 1, tzinfo=datetime.timezone.utc)
+ late = datetime.datetime(2026, 6, 1, tzinfo=datetime.timezone.utc)
+
+ assert fingerprint_tool_call("t", {"when": early}, "id1") ==
fingerprint_tool_call(
+ "t", {"when": early}, "id1"
+ )
+ assert fingerprint_tool_call("t", {"when": early}, "id1") !=
fingerprint_tool_call(
+ "t", {"when": late}, "id1"
+ )
+
+ def test_tool_choice_dataclass_fingerprints(self):
+ fp = fingerprint_model_request(
+ "m",
+ make_messages(),
+ {"tool_choice": ToolOrOutput(function_tools=["my_tool"])},
+ ModelRequestParameters(),
+ )
+
+ assert fp is not None
+
+ def test_tool_choice_dataclass_still_affects_the_fingerprint(self):
+ one = fingerprint_model_request(
+ "m",
+ make_messages(),
+ {"tool_choice": ToolOrOutput(function_tools=["a"])},
+ ModelRequestParameters(),
+ )
+ other = fingerprint_model_request(
+ "m",
+ make_messages(),
+ {"tool_choice": ToolOrOutput(function_tools=["b"])},
+ ModelRequestParameters(),
+ )
+
+ assert one is not None
+ assert one != other
+
+ def test_value_pydantic_cannot_serialize_still_returns_none(self):
+ """Normalization must not turn a genuinely unserializable value into a
hash."""
+ assert fingerprint_tool_call("t", {"v": object()}, "id1") is None
+
+ def test_plain_payload_digest_is_unchanged_by_normalization(self):
Review Comment:
Added a test helper that hashes the json-mode dump the way main does, and
cases that must equal it: non-UTF-8 `BinaryContent`, a bytes tool return, date
and mixed keys, NaN, a datetime, and an agent's `instruction_parts`. Reverting
either dump to python mode now fails them. I compute main's digest in the test
rather than hard-coding it, since a fixed digest would break whenever
pydantic-ai adds a field. There's also a subprocess test for a set inside
`ToolReturnPart.content` across hash seeds.
##########
providers/common/ai/src/airflow/providers/common/ai/durable/fingerprint.py:
##########
@@ -119,13 +195,21 @@ def fingerprint_model_request(
output mode and schema, native tools, ...) so any change to what is sent
to the model invalidates the cached response.
- Returns ``None`` when the request cannot be serialized; ``None`` compares
- equal to ``None``, so requests that cannot be fingerprinted degrade to
- unverified positional replay rather than disabling caching.
+ Returns ``None`` when the request cannot be serialized even through
pydantic,
+ which prevents the step from being replayed or cached. Because model
settings
+ and message history are carried into every later request, such a value in
+ either usually degrades every subsequent model step of the run the same
way.
+ ``step`` is attached to that warning so the log names where it began.
"""
try:
- dumped = ModelMessagesTypeAdapter.dump_python(messages, mode="json")
- params =
_MODEL_REQUEST_PARAMETERS_ADAPTER.dump_python(model_request_parameters,
mode="json")
+ # ``mode="python"``, not ``mode="json"``: a json-mode dump renders a
set as
+ # a list in iteration order, and a tool that returned a set puts one
in the
+ # message history, where it would reach the hash already unstably
ordered.
+ # Python mode leaves it a set for ``_canonical`` to order. For values
that
+ # are not sets the two modes produce the same digest, so stored
Review Comment:
With the json-mode dump back, that claim holds again. On 2.44,
`Agent(instructions="Be terse.")` gives the same digest as main (it drifted at
the previous head), and NaN renders as `null` again. Checked on 2.33 and 2.44.
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