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langchain/libs/community/tests/integration_tests/llms/test_fireworks.py

138 lines
3.9 KiB
Python

"""Test Fireworks AI API Wrapper."""
from typing import Generator
import pytest
from langchain_core.outputs import LLMResult
from langchain_community.llms.fireworks import Fireworks
@pytest.fixture
def llm() -> Fireworks:
return Fireworks(model_kwargs={"temperature": 0, "max_tokens": 512})
@pytest.mark.scheduled
def test_fireworks_call(llm: Fireworks) -> None:
"""Test valid call to fireworks."""
output = llm("How is the weather in New York today?")
assert isinstance(output, str)
@pytest.mark.scheduled
def test_fireworks_model_param() -> None:
"""Tests model parameters for Fireworks"""
llm = Fireworks(model="foo")
assert llm.model == "foo"
@pytest.mark.scheduled
def test_fireworks_invoke(llm: Fireworks) -> None:
"""Tests completion with invoke"""
output = llm.invoke("How is the weather in New York today?", stop=[","])
assert isinstance(output, str)
assert output[-1] == ","
@pytest.mark.scheduled
async def test_fireworks_ainvoke(llm: Fireworks) -> None:
"""Tests completion with invoke"""
output = await llm.ainvoke("How is the weather in New York today?", stop=[","])
assert isinstance(output, str)
assert output[-1] == ","
@pytest.mark.scheduled
def test_fireworks_batch(llm: Fireworks) -> None:
"""Tests completion with invoke"""
llm = Fireworks()
output = llm.batch(
[
"How is the weather in New York today?",
"How is the weather in New York today?",
],
stop=[","],
)
for token in output:
assert isinstance(token, str)
assert token[-1] == ","
@pytest.mark.scheduled
async def test_fireworks_abatch(llm: Fireworks) -> None:
"""Tests completion with invoke"""
output = await llm.abatch(
[
"How is the weather in New York today?",
"How is the weather in New York today?",
],
stop=[","],
)
for token in output:
assert isinstance(token, str)
assert token[-1] == ","
@pytest.mark.scheduled
def test_fireworks_multiple_prompts(
llm: Fireworks,
) -> None:
"""Test completion with multiple prompts."""
output = llm.generate(["How is the weather in New York today?", "I'm pickle rick"])
assert isinstance(output, LLMResult)
assert isinstance(output.generations, list)
assert len(output.generations) == 2
@pytest.mark.scheduled
def test_fireworks_streaming(llm: Fireworks) -> None:
"""Test stream completion."""
generator = llm.stream("Who's the best quarterback in the NFL?")
assert isinstance(generator, Generator)
for token in generator:
assert isinstance(token, str)
@pytest.mark.scheduled
def test_fireworks_streaming_stop_words(llm: Fireworks) -> None:
"""Test stream completion with stop words."""
generator = llm.stream("Who's the best quarterback in the NFL?", stop=[","])
assert isinstance(generator, Generator)
last_token = ""
for token in generator:
last_token = token
assert isinstance(token, str)
assert last_token[-1] == ","
@pytest.mark.scheduled
async def test_fireworks_streaming_async(llm: Fireworks) -> None:
"""Test stream completion."""
last_token = ""
async for token in llm.astream(
"Who's the best quarterback in the NFL?", stop=[","]
):
last_token = token
assert isinstance(token, str)
assert last_token[-1] == ","
@pytest.mark.scheduled
async def test_fireworks_async_agenerate(llm: Fireworks) -> None:
"""Test async."""
output = await llm.agenerate(["What is the best city to live in California?"])
assert isinstance(output, LLMResult)
@pytest.mark.scheduled
async def test_fireworks_multiple_prompts_async_agenerate(llm: Fireworks) -> None:
output = await llm.agenerate(
["How is the weather in New York today?", "I'm pickle rick"]
)
assert isinstance(output, LLMResult)
assert isinstance(output.generations, list)
assert len(output.generations) == 2