2023-11-14 20:10:18 +00:00
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"""Test AzureOpenAI wrapper."""
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import os
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from typing import Any, Generator
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import pytest
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2023-12-11 21:53:30 +00:00
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from langchain_core.callbacks import CallbackManager
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2023-11-21 16:35:29 +00:00
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from langchain_core.outputs import LLMResult
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2023-11-14 20:10:18 +00:00
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2023-12-11 21:53:30 +00:00
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from langchain_community.llms import AzureOpenAI
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2023-11-14 20:10:18 +00:00
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from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
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OPENAI_API_VERSION = os.environ.get("AZURE_OPENAI_API_VERSION", "")
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OPENAI_API_BASE = os.environ.get("AZURE_OPENAI_API_BASE", "")
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OPENAI_API_KEY = os.environ.get("AZURE_OPENAI_API_KEY", "")
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2023-12-08 18:23:02 +00:00
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DEPLOYMENT_NAME = os.environ.get(
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"AZURE_OPENAI_DEPLOYMENT_NAME",
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os.environ.get("AZURE_OPENAI_LLM_DEPLOYMENT_NAME", ""),
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)
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2023-11-14 20:10:18 +00:00
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def _get_llm(**kwargs: Any) -> AzureOpenAI:
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return AzureOpenAI(
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deployment_name=DEPLOYMENT_NAME,
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openai_api_version=OPENAI_API_VERSION,
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openai_api_base=OPENAI_API_BASE,
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openai_api_key=OPENAI_API_KEY,
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**kwargs,
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)
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@pytest.fixture
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def llm() -> AzureOpenAI:
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return _get_llm(
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max_tokens=10,
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)
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@pytest.mark.scheduled
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def test_openai_call(llm: AzureOpenAI) -> None:
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"""Test valid call to openai."""
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2024-04-24 23:39:23 +00:00
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output = llm.invoke("Say something nice:")
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2023-11-14 20:10:18 +00:00
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assert isinstance(output, str)
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@pytest.mark.scheduled
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def test_openai_streaming(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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generator = llm.stream("I'm Pickle Rick")
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assert isinstance(generator, Generator)
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full_response = ""
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for token in generator:
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assert isinstance(token, str)
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full_response += token
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assert full_response
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@pytest.mark.scheduled
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async def test_openai_astream(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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async for token in llm.astream("I'm Pickle Rick"):
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assert isinstance(token, str)
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@pytest.mark.scheduled
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async def test_openai_abatch(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
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for token in result:
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assert isinstance(token, str)
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async def test_openai_abatch_tags(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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result = await llm.abatch(
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["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
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)
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for token in result:
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assert isinstance(token, str)
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@pytest.mark.scheduled
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def test_openai_batch(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
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for token in result:
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assert isinstance(token, str)
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@pytest.mark.scheduled
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async def test_openai_ainvoke(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
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assert isinstance(result, str)
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@pytest.mark.scheduled
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def test_openai_invoke(llm: AzureOpenAI) -> None:
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"""Test streaming tokens from AzureOpenAI."""
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result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
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assert isinstance(result, str)
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@pytest.mark.scheduled
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def test_openai_multiple_prompts(llm: AzureOpenAI) -> None:
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"""Test completion with multiple prompts."""
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output = llm.generate(["I'm Pickle Rick", "I'm Pickle Rick"])
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assert isinstance(output, LLMResult)
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assert isinstance(output.generations, list)
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assert len(output.generations) == 2
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def test_openai_streaming_best_of_error() -> None:
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"""Test validation for streaming fails if best_of is not 1."""
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with pytest.raises(ValueError):
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_get_llm(best_of=2, streaming=True)
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def test_openai_streaming_n_error() -> None:
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"""Test validation for streaming fails if n is not 1."""
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with pytest.raises(ValueError):
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_get_llm(n=2, streaming=True)
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def test_openai_streaming_multiple_prompts_error() -> None:
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"""Test validation for streaming fails if multiple prompts are given."""
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with pytest.raises(ValueError):
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_get_llm(streaming=True).generate(["I'm Pickle Rick", "I'm Pickle Rick"])
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@pytest.mark.scheduled
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def test_openai_streaming_call() -> None:
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"""Test valid call to openai."""
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llm = _get_llm(max_tokens=10, streaming=True)
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2024-04-24 23:39:23 +00:00
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output = llm.invoke("Say foo:")
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2023-11-14 20:10:18 +00:00
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assert isinstance(output, str)
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def test_openai_streaming_callback() -> None:
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"""Test that streaming correctly invokes on_llm_new_token callback."""
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callback_handler = FakeCallbackHandler()
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callback_manager = CallbackManager([callback_handler])
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llm = _get_llm(
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max_tokens=10,
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streaming=True,
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temperature=0,
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callback_manager=callback_manager,
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verbose=True,
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)
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llm.invoke("Write me a sentence with 100 words.")
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2023-11-14 20:10:18 +00:00
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assert callback_handler.llm_streams == 11
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@pytest.mark.scheduled
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async def test_openai_async_generate() -> None:
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"""Test async generation."""
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llm = _get_llm(max_tokens=10)
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output = await llm.agenerate(["Hello, how are you?"])
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assert isinstance(output, LLMResult)
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async def test_openai_async_streaming_callback() -> None:
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"""Test that streaming correctly invokes on_llm_new_token callback."""
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callback_handler = FakeCallbackHandler()
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callback_manager = CallbackManager([callback_handler])
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llm = _get_llm(
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max_tokens=10,
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streaming=True,
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temperature=0,
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callback_manager=callback_manager,
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verbose=True,
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)
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result = await llm.agenerate(["Write me a sentence with 100 words."])
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assert callback_handler.llm_streams == 11
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assert isinstance(result, LLMResult)
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