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Add vertex scheduled test (#10958)
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7
.github/workflows/scheduled_test.yml
vendored
7
.github/workflows/scheduled_test.yml
vendored
@ -34,12 +34,19 @@ jobs:
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working-directory: libs/langchain
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cache-key: scheduled
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- name: 'Authenticate to Google Cloud'
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id: 'auth'
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uses: 'google-github-actions/auth@v1'
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with:
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credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
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- name: Install dependencies
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working-directory: libs/langchain
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shell: bash
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run: |
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echo "Running scheduled tests, installing dependencies with poetry..."
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poetry install --with=test_integration
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poetry run pip install google-cloud-aiplatform
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- name: Run tests
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shell: bash
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@ -18,6 +18,14 @@ from langchain.schema import LLMResult
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from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage
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@pytest.mark.parametrize("model_name", [None, "codechat-bison", "chat-bison"])
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def test_vertexai_instantiation(model_name: str) -> None:
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model = ChatVertexAI(model_name=model_name)
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assert model._llm_type == "vertexai"
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assert model.model_name == model.client._model_id
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@pytest.mark.scheduled
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@pytest.mark.parametrize("model_name", [None, "codechat-bison", "chat-bison"])
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def test_vertexai_single_call(model_name: str) -> None:
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if model_name:
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@ -28,10 +36,9 @@ def test_vertexai_single_call(model_name: str) -> None:
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response = model([message])
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assert isinstance(response, AIMessage)
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assert isinstance(response.content, str)
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assert model._llm_type == "vertexai"
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assert model.model_name == model.client._model_id
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@pytest.mark.scheduled
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@pytest.mark.asyncio
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async def test_vertexai_agenerate() -> None:
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model = ChatVertexAI(temperature=0)
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@ -44,6 +51,7 @@ async def test_vertexai_agenerate() -> None:
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assert response.generations[0][0] == sync_response.generations[0][0]
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@pytest.mark.scheduled
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def test_vertexai_single_call_with_context() -> None:
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model = ChatVertexAI()
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raw_context = (
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@ -60,6 +68,7 @@ def test_vertexai_single_call_with_context() -> None:
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assert isinstance(response.content, str)
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@pytest.mark.scheduled
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def test_vertexai_single_call_with_examples() -> None:
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model = ChatVertexAI()
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raw_context = "My name is Ned. You are my personal assistant."
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@ -74,6 +83,7 @@ def test_vertexai_single_call_with_examples() -> None:
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assert isinstance(response.content, str)
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@pytest.mark.scheduled
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@pytest.mark.parametrize("model_name", [None, "codechat-bison", "chat-bison"])
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def test_vertexai_single_call_with_history(model_name: str) -> None:
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if model_name:
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@ -118,7 +128,7 @@ def test_parse_chat_history_correct() -> None:
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]
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def test_vertexai_single_call_failes_no_message() -> None:
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def test_vertexai_single_call_fails_no_message() -> None:
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chat = ChatVertexAI()
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with pytest.raises(ValueError) as exc_info:
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_ = chat([])
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@ -15,20 +15,26 @@ from langchain.llms import VertexAI, VertexAIModelGarden
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from langchain.schema import LLMResult
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def test_vertex_call() -> None:
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llm = VertexAI(temperature=0)
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output = llm("Say foo:")
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assert isinstance(output, str)
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def test_vertex_initialization() -> None:
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llm = VertexAI()
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assert llm._llm_type == "vertexai"
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assert llm.model_name == llm.client._model_id
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def test_vertex_call() -> None:
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llm = VertexAI(temperature=0)
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output = llm("Say foo:")
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assert isinstance(output, str)
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@pytest.mark.scheduled
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def test_vertex_generate() -> None:
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llm = VertexAI(temperate=0)
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output = llm.generate(["Please say foo:"])
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assert isinstance(output, LLMResult)
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@pytest.mark.scheduled
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@pytest.mark.asyncio
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async def test_vertex_agenerate() -> None:
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llm = VertexAI(temperate=0)
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@ -36,7 +42,8 @@ async def test_vertex_agenerate() -> None:
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assert isinstance(output, LLMResult)
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def test_vertext_stream() -> None:
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@pytest.mark.scheduled
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def test_vertex_stream() -> None:
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llm = VertexAI(temperate=0)
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outputs = list(llm.stream("Please say foo:"))
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assert isinstance(outputs[0], str)
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@ -63,7 +70,6 @@ def test_model_garden() -> None:
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project = os.environ["PROJECT"]
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llm = VertexAIModelGarden(endpoint_id=endpoint_id, project=project)
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output = llm("What is the meaning of life?")
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print(output)
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assert isinstance(output, str)
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assert llm._llm_type == "vertexai_model_garden"
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