mirror of
https://github.com/hwchase17/langchain
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481d3855dc
- `llm(prompt)` -> `llm.invoke(prompt)`
- `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`)
- `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt,
config={"callbacks": callbacks})`
- `llm(prompt, **kwargs)` -> `llm.invoke(prompt, **kwargs)`
77 lines
2.3 KiB
Python
77 lines
2.3 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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from pathlib import Path
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import pytest
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from langchain_core.outputs import LLMResult
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from langchain_community.llms.google_palm import GooglePalm
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from langchain_community.llms.loading import load_llm
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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 = GooglePalm(max_output_tokens=10, model_name=model_name)
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else:
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llm = GooglePalm(max_output_tokens=10)
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output = llm.invoke("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_name == "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 = GooglePalm(temperature=0.3, n=n, model_name=model_name)
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else:
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llm = GooglePalm(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 = GooglePalm()
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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 = GooglePalm(temperature=0, model_name="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 = GooglePalm(temperature=0, model_name="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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def test_saving_loading_llm(tmp_path: Path) -> None:
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"""Test saving/loading a Google PaLM LLM."""
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llm = GooglePalm(max_output_tokens=10)
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llm.save(file_path=tmp_path / "google_palm.yaml")
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loaded_llm = load_llm(tmp_path / "google_palm.yaml")
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assert loaded_llm == llm
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