fix(components): [text2sql] Turn model_inference_results_path to mode…

…l_inference_results_directory and remove duplicate comment

PiperOrigin-RevId: 576576299

components/google-cloud/google_cloud_pipeline_components/_implementation/model_evaluation/text2sql/evaluation_llm_text2sql_pipeline.py

@@ -73,10 +73,6 @@ def evaluation_llm_text2sql_pipeline(
       must be one of the Model's supportedInputStorageFormats. If not set,
       default to "jsonl".  For more details about this input config, see
       https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.batchPredictionJobs#InputConfig.
-    batch_predict_instances_format: The format in which perdictions are made,
-      must be one of the Model's supportedInputStorageFormats. If not set,
-      default to "jsonl".  For more details about this input config, see
-      https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.batchPredictionJobs#InputConfig.
     machine_type: The machine type of this custom job. If not set, defaulted to
       `e2-highmem-16`. More details:
       https://cloud.google.com/compute/docs/machine-resource
@@ -148,9 +144,11 @@ def evaluation_llm_text2sql_pipeline(
       location=location,
       sql_dialect=sql_dialect,
       evaluation_method=evaluation_method,
-      # TODO(bozhengbz) Add value to model_inference_results_path
-      # when model batch prediction component is added.
-      model_inference_results_path='gs://test/model_inference_results.json',
+      # TODO(bozhengbz) Change value to model_inference_results_directory
+      # when sql query model batch prediction component is added.
+      model_inference_results_directory=batch_predict_table_names_task.outputs[
+          'gcs_output_directory'
+      ],
       tables_metadata_path=tables_metadata_path,
       machine_type=machine_type,
       service_account=service_account,

components/google-cloud/google_cloud_pipeline_components/_implementation/model_evaluation/text2sql_evaluation/component.py

@@ -16,7 +16,9 @@
 from google_cloud_pipeline_components import utils as gcpc_utils
 from google_cloud_pipeline_components._implementation.model_evaluation import utils
 from google_cloud_pipeline_components._implementation.model_evaluation import version
+from kfp.dsl import Artifact
 from kfp.dsl import container_component
+from kfp.dsl import Input
 from kfp.dsl import Metrics
 from kfp.dsl import Output
 from kfp.dsl import OutputPath
@@ -33,7 +35,7 @@ def text2sql_evaluation(
     location: str,
     sql_dialect: str,
     evaluation_method: str,
-    model_inference_results_path: str,
+    model_inference_results_directory: Input[Artifact],
     tables_metadata_path: str,
     display_name: str = 'text2sql-evaluation',
     machine_type: str = 'e2-highmem-16',
@@ -49,8 +51,8 @@ def text2sql_evaluation(
       sql_dialect: Required. SQL dialect type, e.g. bigquery, mysql, etc.
       evaluation_method: Required. Text2SQL evaluation method, value can be
         'parser', 'execution', 'all'.
-      model_inference_results_path: Required. The path for json file containing
-        text2sql model inference results from the last step.
+      model_inference_results_directory: Required. The path for json file
+        containing text2sql model inference results from the last step.
       tables_metadata_path: Required. The path for json file containing database
         metadata, including table names, schema fields.
       display_name: The name of the Evaluation job.
@@ -98,7 +100,7 @@ def text2sql_evaluation(
               f'--location={location}',
               f'--sql_dialect={sql_dialect}',
               f'--evaluation_method={evaluation_method}',
-              f'--model_inference_results_path={model_inference_results_path}',
+              f'--model_inference_results_directory={model_inference_results_directory.path}',
               f'--tables_metadata_path={tables_metadata_path}',
               f'--root_dir={PIPELINE_ROOT_PLACEHOLDER}',
               f'--gcp_resources={gcp_resources}',