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Replace this entire comment with: - **Description:** added support for new Google GenerativeAI models - **Twitter handle:** lkuligin --------- Co-authored-by: Erick Friis <erick@langchain.dev>
66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
"""Test Google GenerativeAI API wrapper.
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Note: This test must be run with the GOOGLE_API_KEY environment variable set to a
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valid API key.
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"""
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import pytest
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from langchain_core.outputs import LLMResult
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from langchain_google_genai.llms import GoogleGenerativeAI
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model_names = [None, "models/text-bison-001", "gemini-pro"]
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@pytest.mark.parametrize(
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"model_name",
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model_names,
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)
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def test_google_generativeai_call(model_name: str) -> None:
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"""Test valid call to Google GenerativeAI text API."""
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if model_name:
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llm = GoogleGenerativeAI(max_output_tokens=10, model=model_name)
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else:
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llm = GoogleGenerativeAI(max_output_tokens=10)
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output = llm("Say foo:")
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assert isinstance(output, str)
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assert llm._llm_type == "google_palm"
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if model_name and "gemini" in model_name:
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assert llm.client.model_name == "models/gemini-pro"
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else:
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assert llm.model == "models/text-bison-001"
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@pytest.mark.parametrize(
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"model_name",
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model_names,
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)
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def test_google_generativeai_generate(model_name: str) -> None:
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n = 1 if model_name == "gemini-pro" else 2
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if model_name:
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llm = GoogleGenerativeAI(temperature=0.3, n=n, model=model_name)
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else:
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llm = GoogleGenerativeAI(temperature=0.3, n=n)
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output = llm.generate(["Say foo:"])
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assert isinstance(output, LLMResult)
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assert len(output.generations) == 1
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assert len(output.generations[0]) == n
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def test_google_generativeai_get_num_tokens() -> None:
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llm = GoogleGenerativeAI()
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output = llm.get_num_tokens("How are you?")
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assert output == 4
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async def test_google_generativeai_agenerate() -> None:
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llm = GoogleGenerativeAI(temperature=0, model="gemini-pro")
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output = await llm.agenerate(["Please say foo:"])
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assert isinstance(output, LLMResult)
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def test_generativeai_stream() -> None:
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llm = GoogleGenerativeAI(temperature=0, model="gemini-pro")
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outputs = list(llm.stream("Please say foo:"))
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assert isinstance(outputs[0], str)
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