chore: import upstream snapshot with attribution

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

@@ -0,0 +1,49 @@
+from typing import Union
+
+from utils import ErrorMsg, ResponseFormat, get_text_chunk_score
+
+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_text_chunk(
+    connection: Union[OpenAIConnection, AzureOpenAIConnection],
+    score_text_chunk_prompt: str,
+    score_threshold: float,
+    deployment_name: str = "",
+    model: str = "",
+    context: str = None,
+    response_format: str = ResponseFormat.TEXT,
+    temperature: float = 0.2,
+):
+    """
+    Validates the given text chunk. If the validation fails, return an empty context and the validation result.
+
+    Returns:
+        dict: Text chunk context and its validation result.
+    """
+    text_chunk_score_res = get_text_chunk_score(
+        connection,
+        model,
+        deployment_name,
+        score_text_chunk_prompt,
+        response_format,
+        score_threshold,
+        temperature,
+    )
+    if not text_chunk_score_res.pass_validation:
+        print(ErrorMsg.INVALID_TEXT_CHUNK.format(context))
+        return {"context": "", "validation_res": text_chunk_score_res._asdict()}
+
+    return {"context": context, "validation_res": text_chunk_score_res._asdict()}