google-genai[patch], community[patch]: Added support for new Google GenerativeAI models (#14530)

Replace this entire comment with:
  - **Description:** added support for new Google GenerativeAI models
  - **Twitter handle:** lkuligin

---------

Co-authored-by: Erick Friis <erick@langchain.dev>

libs/community/tests/integration_tests/llms/test_google_palm.py

@@ -1,4 +1,4 @@
-"""Test Google PaLM Text API wrapper.
+"""Test Google GenerativeAI API wrapper.
 
 Note: This test must be run with the GOOGLE_API_KEY environment variable set to a
       valid API key.
@@ -6,35 +6,68 @@ Note: This test must be run with the GOOGLE_API_KEY environment variable set to
 
 from pathlib import Path
 
+import pytest
 from langchain_core.outputs import LLMResult
 
 from langchain_community.llms.google_palm import GooglePalm
 from langchain_community.llms.loading import load_llm
 
+model_names = [None, "models/text-bison-001", "gemini-pro"]
 
-def test_google_palm_call() -> None:
-    """Test valid call to Google PaLM text API."""
-    llm = GooglePalm(max_output_tokens=10)
+
+@pytest.mark.parametrize(
+    "model_name",
+    model_names,
+)
+def test_google_generativeai_call(model_name: str) -> None:
+    """Test valid call to Google GenerativeAI text API."""
+    if model_name:
+        llm = GooglePalm(max_output_tokens=10, model_name=model_name)
+    else:
+        llm = GooglePalm(max_output_tokens=10)
     output = llm("Say foo:")
     assert isinstance(output, str)
     assert llm._llm_type == "google_palm"
-    assert llm.model_name == "models/text-bison-001"
+    if model_name and "gemini" in model_name:
+        assert llm.client.model_name == "models/gemini-pro"
+    else:
+        assert llm.model_name == "models/text-bison-001"
 
 
-def test_google_palm_generate() -> None:
-    llm = GooglePalm(temperature=0.3, n=2)
+@pytest.mark.parametrize(
+    "model_name",
+    model_names,
+)
+def test_google_generativeai_generate(model_name: str) -> None:
+    n = 1 if model_name == "gemini-pro" else 2
+    if model_name:
+        llm = GooglePalm(temperature=0.3, n=n, model_name=model_name)
+    else:
+        llm = GooglePalm(temperature=0.3, n=n)
     output = llm.generate(["Say foo:"])
     assert isinstance(output, LLMResult)
     assert len(output.generations) == 1
-    assert len(output.generations[0]) == 2
+    assert len(output.generations[0]) == n
 
 
-def test_google_palm_get_num_tokens() -> None:
+def test_google_generativeai_get_num_tokens() -> None:
     llm = GooglePalm()
     output = llm.get_num_tokens("How are you?")
     assert output == 4
 
 
+async def test_google_generativeai_agenerate() -> None:
+    llm = GooglePalm(temperature=0, model_name="gemini-pro")
+    output = await llm.agenerate(["Please say foo:"])
+    assert isinstance(output, LLMResult)
+
+
+def test_generativeai_stream() -> None:
+    llm = GooglePalm(temperature=0, model_name="gemini-pro")
+    outputs = list(llm.stream("Please say foo:"))
+    assert isinstance(outputs[0], str)
+
+
 def test_saving_loading_llm(tmp_path: Path) -> None:
     """Test saving/loading a Google PaLM LLM."""
     llm = GooglePalm(max_output_tokens=10)