chore: import upstream snapshot with attribution

examples/tutorials/generate-test-data/example_flow/validate_question.py

@@ -0,0 +1,60 @@
+from typing import Union
+
+from utils import ErrorMsg, QuestionType, ResponseFormat, get_question_validation_res
+
+from promptflow._core.tool import InputSetting
+from promptflow.connections import AzureOpenAIConnection, OpenAIConnection
+from promptflow.core import tool
+
+
+@tool(
+    input_settings={
+        "deployment_name": InputSetting(
+            enabled_by="connection",
+            enabled_by_type=["AzureOpenAIConnection"],
+            capabilities={"completion": False, "chat_completion": True, "embeddings": False},
+        ),
+        "model": InputSetting(enabled_by="connection", enabled_by_type=["OpenAIConnection"]),
+    }
+)
+def validate_question(
+    connection: Union[OpenAIConnection, AzureOpenAIConnection],
+    generated_question: str,
+    validate_question_prompt: str,
+    deployment_name: str = "",
+    model: str = "",
+    response_format: str = ResponseFormat.TEXT,
+    temperature: float = 0.2,
+):
+    """
+    1. Validates the given seed question.
+    2. Generates a test question based on the given prompts and distribution ratios.
+
+    Returns:
+        dict: The generated test question and its type.
+    """
+    # text chunk is not valid, seed question not generated.
+    if not generated_question:
+        return {"question": "", "question_type": "", "validation_res": None}
+
+    validation_res = get_question_validation_res(
+        connection,
+        model,
+        deployment_name,
+        validate_question_prompt,
+        generated_question,
+        response_format,
+        temperature,
+    )
+    is_valid_seed_question = validation_res.pass_validation
+    question = ""
+    question_type = ""
+    failed_reason = ""
+    if not is_valid_seed_question:
+        failed_reason = ErrorMsg.INVALID_QUESTION.format(generated_question)
+        print(failed_reason)
+    else:
+        question = generated_question
+        question_type = QuestionType.SIMPLE
+
+    return {"question": question, "question_type": question_type, "validation_res": validation_res._asdict()}