Add gemini 3.1 flash lite both as model-to-be-evaluated and LLM judge.

configs/medmarks-endpoints.toml

@@ -111,6 +111,15 @@ api_client_type = "openai_chat_completions"
 temperature = 1
 
 
+[[endpoint]]
+endpoint_id = "gemini-3_1-flash-lite"
+model = "google/gemini-3.1-flash-lite"
+api_client_type = "openai_chat_completions"
+
+[endpoint.sampling_args]
+temperature = 1
+
+
 [[endpoint]]
 endpoint_id = "gemma-3-12b-it"
 model = "google/gemma-3-12b-it"

medarc_verifiers/utils/judge_helpers.py

@@ -1,9 +1,21 @@
 from dataclasses import dataclass, field
 import os
 from typing import Dict, Iterable, Optional, Tuple, Union
+from urllib.parse import urlparse
 from .sampling_args import sanitize_sampling_args_for_openai
 from .prime_inference import PRIME_INFERENCE_URL, _resolve_include_usage
 
+# Google's OpenAI-compatibility endpoint strictly validates request payloads and
+# rejects fields it does not support (e.g. top_k) with 400 INVALID_ARGUMENT.
+_GOOGLE_OPENAI_COMPAT_HOST = "generativelanguage.googleapis.com"
+_GOOGLE_UNSUPPORTED_SAMPLING_KEYS = ("top_k", "min_p")
+
+
+def _is_google_openai_compat(base_url: str | None) -> bool:
+    if not base_url:
+        return False
+    return urlparse(base_url).hostname == _GOOGLE_OPENAI_COMPAT_HOST
+
 
 def _normalize_judge_name(name: str) -> str:
     return name.lower().replace("_", "-").replace("/", "-")
@@ -80,7 +92,7 @@ def as_dict(self, *, include_usage: bool = True) -> Dict[str, Union[float, int,
         top_k=64,
     ),
     JudgeSamplingDefaults(
-        name="gemini-3",
+        name=("gemini-3", "gemini-3.1"),
         temperature=1.0,
         top_p=0.95,
         top_k=64,
@@ -149,7 +161,8 @@ def judge_sampling_args_and_headers(
 
     Args:
         judge_name: The name of the judge model.
-        base_url: The base URL for the API. Used for Prime Inference detection.
+        base_url: The base URL for the API. Used for Prime Inference detection and
+            to drop sampling params rejected by Google's OpenAI-compatibility endpoint.
         timeout: Request timeout in seconds.
         include_usage: Whether to include usage reporting in extra_body.
             If None (default), checks MEDARC_INCLUDE_USAGE env var, then
@@ -174,6 +187,9 @@ def judge_sampling_args_and_headers(
             effective_include_usage = _resolve_include_usage(include_usage, is_prime_inference)
 
             payload = judge_defaults.as_dict(include_usage=effective_include_usage)
+            if _is_google_openai_compat(base_url):
+                for key in _GOOGLE_UNSUPPORTED_SAMPLING_KEYS:
+                    payload.pop(key, None)
             if reasoning_effort is not None and "reasoning_effort" in payload:
                 if isinstance(reasoning_effort, str) and reasoning_effort.lower().strip() == "none":
                     payload.pop("reasoning_effort", None)

tests/test_judge_helpers.py

@@ -124,6 +124,25 @@ def test_judge_sampling_defaults_supports_multiple_names_per_defaults(
     assert result_47 == result_46
 
 
+def test_judge_sampling_drops_params_unsupported_by_google_openai_compat(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    """Google's OpenAI-compat endpoint rejects unknown fields like top_k with 400."""
+    monkeypatch.delenv("PRIME_TEAM_ID", raising=False)
+    monkeypatch.delenv("MEDARC_INCLUDE_USAGE", raising=False)
+
+    google_url = "https://generativelanguage.googleapis.com/v1beta/openai/"
+    result, _ = judge_sampling_args_and_headers("gemini-3.1-flash-lite", base_url=google_url)
+    assert "top_k" not in result.get("extra_body", {})
+    assert "min_p" not in result.get("extra_body", {})
+    assert result["temperature"] == 1.0
+    assert result["top_p"] == 0.95
+
+    # Other base URLs keep the provider-recommended top_k.
+    result, _ = judge_sampling_args_and_headers("gemini-3.1-flash-lite", base_url="https://api.example.com/v1")
+    assert result["extra_body"]["top_k"] == 64
+
+
 def test_judge_sampling_override_temperature_non_reasoning(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.delenv("PRIME_TEAM_ID", raising=False)
     monkeypatch.delenv("MEDARC_INCLUDE_USAGE", raising=False)