langchain/tests/integration_tests/llms/test_anthropic.py
Ankush Gola d3ec00b566
Callbacks Refactor [base] (#3256)
Co-authored-by: Nuno Campos <nuno@boringbits.io>
Co-authored-by: Davis Chase <130488702+dev2049@users.noreply.github.com>
Co-authored-by: Zander Chase <130414180+vowelparrot@users.noreply.github.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2023-04-30 11:14:09 -07:00

64 lines
1.9 KiB
Python

"""Test Anthropic API wrapper."""
from typing import Generator
import pytest
from langchain.callbacks.manager import CallbackManager
from langchain.llms.anthropic import Anthropic
from langchain.schema import LLMResult
from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
def test_anthropic_call() -> None:
"""Test valid call to anthropic."""
llm = Anthropic(model="test")
output = llm("Say foo:")
assert isinstance(output, str)
def test_anthropic_streaming() -> None:
"""Test streaming tokens from anthropic."""
llm = Anthropic(model="test")
generator = llm.stream("I'm Pickle Rick")
assert isinstance(generator, Generator)
for token in generator:
assert isinstance(token["completion"], str)
def test_anthropic_streaming_callback() -> None:
"""Test that streaming correctly invokes on_llm_new_token callback."""
callback_handler = FakeCallbackHandler()
callback_manager = CallbackManager([callback_handler])
llm = Anthropic(
streaming=True,
callback_manager=callback_manager,
verbose=True,
)
llm("Write me a sentence with 100 words.")
assert callback_handler.llm_streams > 1
@pytest.mark.asyncio
async def test_anthropic_async_generate() -> None:
"""Test async generate."""
llm = Anthropic()
output = await llm.agenerate(["How many toes do dogs have?"])
assert isinstance(output, LLMResult)
@pytest.mark.asyncio
async def test_anthropic_async_streaming_callback() -> None:
"""Test that streaming correctly invokes on_llm_new_token callback."""
callback_handler = FakeCallbackHandler()
callback_manager = CallbackManager([callback_handler])
llm = Anthropic(
streaming=True,
callback_manager=callback_manager,
verbose=True,
)
result = await llm.agenerate(["How many toes do dogs have?"])
assert callback_handler.llm_streams > 1
assert isinstance(result, LLMResult)