add responses example

Author: Dylan Huang

eval_protocol/quickstart/llm_judge_openai_responses.py

@@ -0,0 +1,55 @@
+"""
+LLM Judge quickstart that PULLS DATA FROM OpenAI Responses API and persists results locally via Eval Protocol.
+
+This mirrors `eval_protocol/quickstart/llm_judge.py` (Langfuse source), but uses
+OpenAI Responses API as the source of evaluation rows.
+
+Env vars:
+  export OPENAI_API_KEY=...             # required to fetch examples
+
+Judge model keys:
+  - Default judge is "gemini-2.5-pro" from utils; requires GEMINI_API_KEY
+  - Or set judge in the code to "gpt-4.1" and export OPENAI_API_KEY
+
+Run:
+  pytest python-sdk/eval_protocol/quickstart/llm_judge_openai_responses.py -q -s
+"""
+
+import os
+from typing import List
+
+import pytest
+
+from eval_protocol.models import EvaluationRow
+from eval_protocol.pytest import evaluation_test
+from eval_protocol.pytest.default_single_turn_rollout_process import SingleTurnRolloutProcessor
+from eval_protocol.quickstart import aha_judge, split_multi_turn_rows
+from eval_protocol.adapters.openai_responses import OpenAIResponsesAdapter
+
+adapter = OpenAIResponsesAdapter()
+input_rows = adapter.get_evaluation_rows(
+    response_ids=[
+        "resp_0e1b7db5d96e92470068c99506443c819e9305e92915d2405f",
+        "resp_05639dcaca074fbc0068c9946593b481908cac70075926d85c",
+    ]
+)
+
+
+@pytest.mark.skipif(os.environ.get("CI") == "true", reason="Skip in CI")  # pyright: ignore[reportAttributeAccessIssue]
+@pytest.mark.asyncio  # pyright: ignore[reportAttributeAccessIssue]
+@evaluation_test(
+    input_rows=[input_rows],
+    completion_params=[
+        {
+            "model": "fireworks_ai/accounts/fireworks/models/deepseek-v3p1",
+        },
+        {
+            "model": "fireworks_ai/accounts/fireworks/models/kimi-k2-instruct-0905",
+        },
+    ],
+    rollout_processor=SingleTurnRolloutProcessor(),
+    preprocess_fn=split_multi_turn_rows,
+    mode="all",
+)
+async def test_llm_judge_openai_responses(rows: List[EvaluationRow]) -> List[EvaluationRow]:
+    return await aha_judge(rows)