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anthropic[patch]: integration test update (#18823)

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Erick Friis 2024-03-08 13:47:31 -08:00 committed by GitHub
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1 changed files with 8 additions and 3 deletions
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11
libs/partners/anthropic/tests/integration_tests/test_experimental.py
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@ -10,6 +10,7 @@ from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_anthropic.experimental import ChatAnthropicTools from langchain_anthropic.experimental import ChatAnthropicTools
MODEL_NAME = "claude-3-sonnet-20240229" MODEL_NAME = "claude-3-sonnet-20240229"
BIG_MODEL_NAME = "claude-3-opus-20240229"
##################################### #####################################
### Test Basic features, no tools ### ### Test Basic features, no tools ###
@ -108,7 +109,9 @@ def test_tools() -> None:
name: str name: str
age: int age: int
llm = ChatAnthropicTools(model_name=MODEL_NAME).bind_tools([Person]) llm = ChatAnthropicTools(model_name=BIG_MODEL_NAME, temperature=0).bind_tools(
[Person]
)
result = llm.invoke("Erick is 27 years old") result = llm.invoke("Erick is 27 years old")
assert result.content == "", f"content should be empty, not {result.content}" assert result.content == "", f"content should be empty, not {result.content}"
assert "tool_calls" in result.additional_kwargs assert "tool_calls" in result.additional_kwargs
@ -126,7 +129,9 @@ def test_with_structured_output() -> None:
name: str name: str
age: int age: int
chain = ChatAnthropicTools(model_name=MODEL_NAME).with_structured_output(Person) chain = ChatAnthropicTools(
model_name=BIG_MODEL_NAME, temperature=0
).with_structured_output(Person)
result = chain.invoke("Erick is 27 years old") result = chain.invoke("Erick is 27 years old")
assert isinstance(result, Person) assert isinstance(result, Person)
assert result.name == "Erick" assert result.name == "Erick"
@ -167,7 +172,7 @@ def test_anthropic_complex_structured_output() -> None:
] ]
) )
llm = ChatAnthropicTools(temperature=0, model_name="claude-3-sonnet-20240229") llm = ChatAnthropicTools(temperature=0, model_name=BIG_MODEL_NAME)
extraction_chain = prompt | llm.with_structured_output(Email) extraction_chain = prompt | llm.with_structured_output(Email)