chore: import upstream snapshot with attribution

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

@@ -0,0 +1,39 @@
+from typing import Union
+
+from utils import llm_call
+
+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 generate_question(
+    connection: Union[OpenAIConnection, AzureOpenAIConnection],
+    generate_question_prompt: str,
+    deployment_name: str = "",
+    model: str = "",
+    context: str = None,
+    temperature: float = 0.2,
+):
+    """
+    Generates a question based on the given context.
+
+    Returns:
+        str: The generated seed question.
+    """
+    # text chunk is not valid, just skip test data gen.
+    if not context:
+        return ""
+
+    seed_question = llm_call(connection, model, deployment_name, generate_question_prompt, temperature=temperature)
+    return seed_question