[SC-16225] Add Gemini support

pyproject.toml

@@ -46,6 +46,8 @@ all = [
   "langchain-community (>=0.2.0,<0.4.0)",
   "sentencepiece (>=0.2.0,<0.3.0)",
   "langchain-openai (>=0.1.8)",
+  "langchain-google-genai",
+  "google-genai",
   "scipy",
   "statsmodels (>=0.14.2,<0.15.0)",
   "langdetect",
@@ -79,6 +81,8 @@ llm = [
   "datasets (>=4.4,<5.0.0) ; python_version >= '3.14'",
   "sentencepiece (>=0.2.0,<0.3.0)",
   "langchain-openai (>=0.1.8)",
+  "langchain-google-genai",
+  "google-genai",
   "pyarrow (<16) ; python_version < '3.13'",
   "pyarrow (>=20,<21) ; python_version == '3.13'",
   "pyarrow (>=22,<23) ; python_version >= '3.14'",

tests/unit_tests/model_validation/ragas/test_utils.py

@@ -0,0 +1,48 @@
+from types import SimpleNamespace
+
+from langchain_core.messages import AIMessage
+from langchain_core.outputs import ChatGeneration
+
+from validmind.tests.model_validation.ragas.utils import _ragas_is_finished_parser
+
+
+def test_ragas_is_finished_parser_accepts_gemini_stop_reason():
+    response = SimpleNamespace(
+        flatten=lambda: [
+            SimpleNamespace(
+                generations=[
+                    [
+                        ChatGeneration(
+                            message=AIMessage(
+                                content="done",
+                                response_metadata={"finish_reason": "STOP"},
+                            )
+                        )
+                    ]
+                ]
+            )
+        ]
+    )
+
+    assert _ragas_is_finished_parser(response) is True
+
+
+def test_ragas_is_finished_parser_accepts_max_tokens_reason():
+    response = SimpleNamespace(
+        flatten=lambda: [
+            SimpleNamespace(
+                generations=[
+                    [
+                        ChatGeneration(
+                            message=AIMessage(
+                                content="partial",
+                                response_metadata={"finish_reason": "MAX_TOKENS"},
+                            )
+                        )
+                    ]
+                ]
+            )
+        ]
+    )
+
+    assert _ragas_is_finished_parser(response) is True

tests/unit_tests/test_ai_utils.py

@@ -0,0 +1,99 @@
+import os
+import sys
+import types
+from unittest import mock
+
+from validmind.ai import utils as ai_utils
+
+
+def _reset_ai_utils_state():
+    ai_utils.__dict__["__client"] = None
+    ai_utils.__dict__["__model"] = None
+    ai_utils.__dict__["__judge_llm"] = None
+    ai_utils.__dict__["__judge_embeddings"] = None
+    ai_utils.__dict__["__ack"] = None
+
+
+def test_get_client_and_model_supports_gemini_env():
+    _reset_ai_utils_state()
+
+    with mock.patch.dict(os.environ, {"GEMINI_API_KEY": "test-key"}, clear=True):
+        client, model = ai_utils.get_client_and_model()
+
+    assert client is None
+    assert model == ai_utils.GEMINI_MODEL
+
+
+def test_get_judge_config_builds_gemini_models():
+    _reset_ai_utils_state()
+
+    class FakeChatGoogleGenerativeAI:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+    class FakeGoogleGenerativeAIEmbeddings:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+    fake_module = types.SimpleNamespace(
+        ChatGoogleGenerativeAI=FakeChatGoogleGenerativeAI,
+        GoogleGenerativeAIEmbeddings=FakeGoogleGenerativeAIEmbeddings,
+    )
+
+    with mock.patch.dict(
+        os.environ,
+        {"GEMINI_API_KEY": "test-key", "GEMINI_MODEL": "gemini-test-model"},
+        clear=True,
+    ), mock.patch.dict(sys.modules, {"langchain_google_genai": fake_module}):
+        judge_llm, judge_embeddings = ai_utils.get_judge_config()
+
+    assert isinstance(judge_llm, FakeChatGoogleGenerativeAI)
+    assert judge_llm.kwargs == {
+        "model": "gemini-test-model",
+        "api_key": "test-key",
+    }
+    assert isinstance(judge_embeddings, FakeGoogleGenerativeAIEmbeddings)
+    assert judge_embeddings.kwargs == {
+        "model": ai_utils.GEMINI_EMBEDDINGS_MODEL,
+        "google_api_key": "test-key",
+    }
+
+
+def test_is_configured_uses_resolved_judge_model():
+    _reset_ai_utils_state()
+
+    class FakeJudgeLLM:
+        def invoke(self, messages):
+            assert messages == [("user", "ping")]
+            return types.SimpleNamespace(content="pong")
+
+    with mock.patch.object(
+        ai_utils,
+        "get_judge_config",
+        return_value=(FakeJudgeLLM(), None),
+    ):
+        assert ai_utils.is_configured() is True
+
+
+def test_get_deepeval_model_supports_gemini_env():
+    _reset_ai_utils_state()
+
+    class FakeGeminiModel:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+    fake_module = types.SimpleNamespace(GeminiModel=FakeGeminiModel)
+
+    with mock.patch.dict(
+        os.environ,
+        {"GEMINI_API_KEY": "test-key", "GEMINI_MODEL": "gemini-test-model"},
+        clear=True,
+    ), mock.patch.dict(sys.modules, {"deepeval.models": fake_module}):
+        model = ai_utils.get_deepeval_model()
+
+    assert isinstance(model, FakeGeminiModel)
+    assert model.kwargs == {
+        "model": "gemini-test-model",
+        "api_key": "test-key",
+        "temperature": 0,
+    }