Address QA feedback (#1859)

Author: vbrodsky

libs/labelbox/src/labelbox/schema/data_row_payload_templates.py

@@ -1,11 +1,11 @@
-from typing import Dict, List
+from typing import Dict, List, Optional
 
 from pydantic import BaseModel, Field
 
 from labelbox.schema.data_row import DataRowMetadataField
 
 
-class ModelEvalutationTemlateRowData(BaseModel):
+class ModelEvalutationTemplateRowData(BaseModel):
     type: str = Field(
         default="application/vnd.labelbox.conversational.model-chat-evaluation",
         frozen=True,
@@ -15,6 +15,7 @@ class ModelEvalutationTemlateRowData(BaseModel):
     actors: Dict = Field(default={})
     version: int = Field(default=2, frozen=True)
     messages: Dict = Field(default={})
+    global_key: Optional[str] = None
 
 
 class ModelEvaluationTemplate(BaseModel):
@@ -32,8 +33,8 @@ class ModelEvaluationTemplate(BaseModel):
         >>> task = dataset.create_data_rows([content])
     """
 
-    row_data: ModelEvalutationTemlateRowData = Field(
-        default=ModelEvalutationTemlateRowData()
+    row_data: ModelEvalutationTemplateRowData = Field(
+        default=ModelEvalutationTemplateRowData()
     )
     attachments: List[Dict] = Field(default=[])
     embeddings: List[Dict] = Field(default=[])

libs/labelbox/tests/integration/test_mmc_data_rows.py

@@ -10,7 +10,7 @@
 def mmc_data_row(dataset):
     data = ModelEvaluationTemplate()
 
-    content_all = data.model_dump()
+    content_all = data.model_dump(exclude_none=True)
     task = dataset.create_data_rows([content_all])
     task.wait_till_done()
     assert task.status == "COMPLETE"
@@ -26,12 +26,13 @@ def mmc_data_row(dataset):
 def mmc_data_row_all(dataset, make_metadata_fields, embedding):
     data = ModelEvaluationTemplate()
     data.row_data.rootMessageIds = ["root1"]
+    data.row_data.global_key = "global_key"
     vector = [random.uniform(1.0, 2.0) for _ in range(embedding.dims)]
     data.embeddings = [{"embedding_id": embedding.id, "vector": vector}]
     data.metadata_fields = make_metadata_fields
     data.attachments = [{"type": "RAW_TEXT", "value": "attachment value"}]
 
-    content_all = data.model_dump()
+    content_all = data.model_dump(exclude_none=True)
     task = dataset.create_data_rows([content_all])
     task.wait_till_done()
     assert task.status == "COMPLETE"
@@ -64,6 +65,7 @@ def test_mmc_all(mmc_data_row_all, embedding, constants):
         "actors": {},
         "messages": {},
         "version": 2,
+        "globalKey": "global_key",
     }
 
     metadata_fields = data_row.metadata_fields