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fix: Strip None fields from agent_data in GenerateLossClusters to prevent INVALID_ARGUMENT errors #6600

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Merged
copybara-service merged 1 commit into from
Apr 17, 2026
+96 −3
Merged

fix: Strip None fields from agent_data in GenerateLossClusters to prevent INVALID_ARGUMENT errors #6600

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15 changes: 14 additions & 1 deletion tests/unit/vertexai/genai/replays/test_generate_loss_clusters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@


def _make_eval_result():
"""Creates an EvaluationResult with representative data for loss analysis."""
"""Creates an EvaluationResult with rubric verdicts for loss analysis."""
return types.EvaluationResult(
eval_case_results=[
types.EvalCaseResult(
Expand All @@ -32,6 +32,19 @@ def _make_eval_result():
"multi_turn_task_success_v1": types.EvalCaseMetricResult(
score=0.0,
explanation="Failed tool invocation",
rubric_verdicts=[
types.evals.RubricVerdict(
evaluated_rubric=types.evals.Rubric(
rubric_id="tool_invocation",
content=types.evals.RubricContent(
property=types.evals.RubricContentProperty(
description="The agent should invoke the find_flights tool with the correct parameters.",
)
),
),
verdict=False,
)
],
)
},
)
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80 changes: 80 additions & 0 deletions tests/unit/vertexai/genai/test_evals.py
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Original file line number Diff line number Diff line change
Expand Up @@ -441,6 +441,86 @@ def test_sanitize_agent_data_skips_error_payload(self):
assert "error" not in sanitized
assert sanitized == {}

def test_t_inline_results_strips_none_tool_fields(self):
"""Tests that t_inline_results strips None tool fields like file_search."""
eval_result = common_types.EvaluationResult(
eval_case_results=[
common_types.EvalCaseResult(
eval_case_index=0,
response_candidate_results=[
common_types.ResponseCandidateResult(
response_index=0,
metric_results={
"multi_turn_task_success_v1": common_types.EvalCaseMetricResult(
score=0.0,
explanation="Failed",
)
},
)
],
)
],
evaluation_dataset=[
common_types.EvaluationDataset(
eval_cases=[
common_types.EvalCase(
agent_data=vertexai_genai_types.evals.AgentData(
agents={
"agent_0": vertexai_genai_types.evals.AgentConfig(
agent_id="agent_0",
agent_type="LlmAgent",
instruction="You are a helper.",
tools=[
genai_types.Tool(
function_declarations=[
genai_types.FunctionDeclaration(
name="search",
description="Searches the web.",
)
]
)
],
)
},
turns=[
vertexai_genai_types.evals.ConversationTurn(
turn_index=0,
events=[
vertexai_genai_types.evals.AgentEvent(
author="user",
content=genai_types.Content(
parts=[genai_types.Part(text="Hi")],
),
),
],
)
],
)
)
]
)
],
metadata=common_types.EvaluationRunMetadata(
candidate_names=["candidate-1"]
),
)

payload = _transformers.t_inline_results([eval_result])
assert len(payload) == 1

agent_data = payload[0]["request"]["prompt"]["agent_data"]
agent_config = agent_data["agents"]["agent_0"]
assert "tools" in agent_config
tool = agent_config["tools"][0]
# function_declarations should be preserved
assert "function_declarations" in tool
assert tool["function_declarations"][0]["name"] == "search"
# Gemini-API-only fields must NOT be present (they would be None)
assert "file_search" not in tool
assert "mcp_servers" not in tool
assert "google_search" not in tool
assert "code_execution" not in tool

def test_t_inline_results_skips_error_agent_data_in_df(self):
"""Tests that t_inline_results skips error agent_data from DataFrame."""
error_json = json.dumps({"error": "Agent run failed"})
Expand Down
4 changes: 2 additions & 2 deletions vertexai/_genai/_transformers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -422,7 +422,7 @@ def t_inline_results(
if agent_data:
if hasattr(agent_data, "model_dump"):
prompt_payload["agent_data"] = _sanitize_agent_data(
agent_data.model_dump()
agent_data.model_dump(exclude_none=True)
)
elif isinstance(agent_data, dict):
prompt_payload["agent_data"] = _sanitize_agent_data(agent_data)
Expand All @@ -442,7 +442,7 @@ def t_inline_results(
if df_agent_data is not None:
if hasattr(df_agent_data, "model_dump"):
prompt_payload["agent_data"] = _sanitize_agent_data(
df_agent_data.model_dump()
df_agent_data.model_dump(exclude_none=True)
)
elif isinstance(df_agent_data, str):
try:
Expand Down
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