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anthropic: pydantic mypy plugin (#29144)
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@ -13,6 +13,7 @@ license = "MIT"
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[tool.mypy]
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disallow_untyped_defs = "True"
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plugins = ['pydantic.mypy']
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[tool.poetry.urls]
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"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/anthropic"
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@ -153,7 +153,7 @@ async def test_abatch_tags() -> None:
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async def test_async_tool_use() -> None:
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llm = ChatAnthropic( # type: ignore[call-arg]
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llm = ChatAnthropic(
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model=MODEL_NAME,
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)
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@ -249,7 +249,7 @@ def test_system_invoke() -> None:
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def test_anthropic_call() -> None:
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"""Test valid call to anthropic."""
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chat = ChatAnthropic(model=MODEL_NAME) # type: ignore[call-arg]
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chat = ChatAnthropic(model=MODEL_NAME)
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message = HumanMessage(content="Hello")
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response = chat.invoke([message])
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assert isinstance(response, AIMessage)
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@ -258,7 +258,7 @@ def test_anthropic_call() -> None:
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def test_anthropic_generate() -> None:
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"""Test generate method of anthropic."""
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chat = ChatAnthropic(model=MODEL_NAME) # type: ignore[call-arg]
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chat = ChatAnthropic(model=MODEL_NAME)
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chat_messages: List[List[BaseMessage]] = [
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[HumanMessage(content="How many toes do dogs have?")]
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]
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@ -274,7 +274,7 @@ def test_anthropic_generate() -> None:
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def test_anthropic_streaming() -> None:
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"""Test streaming tokens from anthropic."""
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chat = ChatAnthropic(model=MODEL_NAME) # type: ignore[call-arg]
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chat = ChatAnthropic(model=MODEL_NAME)
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message = HumanMessage(content="Hello")
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response = chat.stream([message])
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for token in response:
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@ -286,7 +286,7 @@ def test_anthropic_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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chat = ChatAnthropic( # type: ignore[call-arg]
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chat = ChatAnthropic(
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model=MODEL_NAME,
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callback_manager=callback_manager,
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verbose=True,
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@ -302,7 +302,7 @@ async def test_anthropic_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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chat = ChatAnthropic( # type: ignore[call-arg]
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chat = ChatAnthropic(
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model=MODEL_NAME,
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callback_manager=callback_manager,
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verbose=True,
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@ -318,7 +318,7 @@ async def test_anthropic_async_streaming_callback() -> None:
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def test_anthropic_multimodal() -> None:
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"""Test that multimodal inputs are handled correctly."""
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chat = ChatAnthropic(model=MODEL_NAME) # type: ignore[call-arg]
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chat = ChatAnthropic(model=MODEL_NAME)
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messages: list[BaseMessage] = [
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HumanMessage(
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content=[
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@ -369,7 +369,7 @@ async def test_astreaming() -> None:
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def test_tool_use() -> None:
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llm = ChatAnthropic(model=MODEL_NAME) # type: ignore[call-arg]
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llm = ChatAnthropic(model=MODEL_NAME)
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llm_with_tools = llm.bind_tools(
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[
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{
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@ -452,7 +452,7 @@ def test_anthropic_with_empty_text_block() -> None:
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"""Type the given letter."""
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return "OK"
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model = ChatAnthropic(model="claude-3-opus-20240229", temperature=0).bind_tools( # type: ignore[call-arg]
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model = ChatAnthropic(model="claude-3-opus-20240229", temperature=0).bind_tools(
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[type_letter]
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)
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@ -490,7 +490,7 @@ def test_anthropic_with_empty_text_block() -> None:
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def test_with_structured_output() -> None:
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llm = ChatAnthropic( # type: ignore[call-arg]
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llm = ChatAnthropic(
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model="claude-3-opus-20240229",
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)
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@ -510,7 +510,7 @@ def test_with_structured_output() -> None:
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def test_get_num_tokens_from_messages() -> None:
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llm = ChatAnthropic(model="claude-3-5-sonnet-20241022") # type: ignore[call-arg]
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llm = ChatAnthropic(model="claude-3-5-sonnet-20241022")
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# Test simple case
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messages = [
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@ -571,7 +571,7 @@ class GetWeather(BaseModel):
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@pytest.mark.parametrize("tool_choice", ["GetWeather", "auto", "any"])
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def test_anthropic_bind_tools_tool_choice(tool_choice: str) -> None:
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chat_model = ChatAnthropic( # type: ignore[call-arg]
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chat_model = ChatAnthropic(
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model=MODEL_NAME,
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)
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chat_model_with_tools = chat_model.bind_tools([GetWeather], tool_choice=tool_choice)
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@ -583,7 +583,7 @@ def test_pdf_document_input() -> None:
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url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
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data = b64encode(requests.get(url).content).decode()
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result = ChatAnthropic(model_name=MODEL_NAME).invoke( # type: ignore[call-arg]
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result = ChatAnthropic(model=MODEL_NAME).invoke(
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[
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HumanMessage(
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[
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