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fix: GenAI SDK client(multimodal) - Fix Pydantic validation errors when using create_* in some cases #6606

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Merged
copybara-service merged 1 commit into from
Apr 27, 2026
Merged

fix: GenAI SDK client(multimodal) - Fix Pydantic validation errors when using create_* in some cases #6606

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29 changes: 19 additions & 10 deletions vertexai/_genai/_datasets_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@

import google.auth.credentials
from vertexai._genai.types import common
from pydantic import BaseModel
from google.genai import _common


METADATA_SCHEMA_URI = (
Expand All @@ -31,18 +31,27 @@
_DEFAULT_BQ_DATASET_PREFIX = "vertex_datasets"
_DEFAULT_BQ_TABLE_PREFIX = "multimodal_dataset"

T = TypeVar("T", bound=BaseModel)
T = TypeVar("T", bound=_common.BaseModel)


def create_from_response(model_type: Type[T], response: dict[str, Any]) -> T:
def create_from_response(
model_type: Type[T],
response: dict[str, Any],
config: Any | None = None,
) -> T:
"""Creates a model from a response."""
model_field_names = model_type.model_fields.keys()
filtered_response = {}
for key, value in response.items():
snake_key = common.camel_to_snake(key)
if snake_key in model_field_names:
filtered_response[snake_key] = value
return model_type(**filtered_response)
kwargs = (
{
"config": {
"response_schema": getattr(config, "response_schema", None),
"response_json_schema": getattr(config, "response_json_schema", None),
"include_all_fields": getattr(config, "include_all_fields", None),
}
}
if config
else {}
)
return model_type._from_response(response=response, kwargs=kwargs)


def validate_multimodal_dataset_bigquery_uri(
Expand Down
20 changes: 14 additions & 6 deletions vertexai/_genai/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -963,7 +963,9 @@ def create_from_bigquery(
operation=multimodal_dataset_operation,
timeout_seconds=config.timeout,
)
return _datasets_utils.create_from_response(types.MultimodalDataset, response)
return _datasets_utils.create_from_response(
types.MultimodalDataset, response, config
)

def create_from_pandas(
self,
Expand Down Expand Up @@ -1302,6 +1304,7 @@ def assess_tuning_resources(
return _datasets_utils.create_from_response(
types.TuningResourceUsageAssessmentResult,
response["tuningResourceUsageAssessmentResult"],
config,
)

def assess_tuning_validity(
Expand Down Expand Up @@ -1368,6 +1371,7 @@ def assess_tuning_validity(
return _datasets_utils.create_from_response(
types.TuningValidationAssessmentResult,
response["tuningValidationAssessmentResult"],
config,
)

def assess_batch_prediction_resources(
Expand Down Expand Up @@ -1430,7 +1434,7 @@ def assess_batch_prediction_resources(
)
result = response["batchPredictionResourceUsageAssessmentResult"]
return _datasets_utils.create_from_response(
types.BatchPredictionResourceUsageAssessmentResult, result
types.BatchPredictionResourceUsageAssessmentResult, result, config
)

def assess_batch_prediction_validity(
Expand Down Expand Up @@ -1493,7 +1497,7 @@ def assess_batch_prediction_validity(
)
result = response["batchPredictionValidationAssessmentResult"]
return _datasets_utils.create_from_response(
types.BatchPredictionValidationAssessmentResult, result
types.BatchPredictionValidationAssessmentResult, result, config
)


Expand Down Expand Up @@ -2231,7 +2235,9 @@ async def create_from_bigquery(
operation=multimodal_dataset_operation,
timeout_seconds=config.timeout,
)
return _datasets_utils.create_from_response(types.MultimodalDataset, response)
return _datasets_utils.create_from_response(
types.MultimodalDataset, response, config
)

async def create_from_pandas(
self,
Expand Down Expand Up @@ -2568,6 +2574,7 @@ async def assess_tuning_resources(
return _datasets_utils.create_from_response(
types.TuningResourceUsageAssessmentResult,
response["tuningResourceUsageAssessmentResult"],
config,
)

async def assess_tuning_validity(
Expand Down Expand Up @@ -2634,6 +2641,7 @@ async def assess_tuning_validity(
return _datasets_utils.create_from_response(
types.TuningValidationAssessmentResult,
response["tuningValidationAssessmentResult"],
config,
)

async def assess_batch_prediction_resources(
Expand Down Expand Up @@ -2696,7 +2704,7 @@ async def assess_batch_prediction_resources(
)
result = response["batchPredictionResourceUsageAssessmentResult"]
return _datasets_utils.create_from_response(
types.BatchPredictionResourceUsageAssessmentResult, result
types.BatchPredictionResourceUsageAssessmentResult, result, config
)

async def assess_batch_prediction_validity(
Expand Down Expand Up @@ -2759,5 +2767,5 @@ async def assess_batch_prediction_validity(
)
result = response["batchPredictionValidationAssessmentResult"]
return _datasets_utils.create_from_response(
types.BatchPredictionValidationAssessmentResult, result
types.BatchPredictionValidationAssessmentResult, result, config
)
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