pull/286/head
Kye 1 year ago
parent af72c1123d
commit b70e2ac8bc

@ -0,0 +1,91 @@
import subprocess
from typing import Optional, Tuple, List
from swarms.models.base_llm import AbstractLLM
try:
from vllm import LLM, SamplingParams
except ImportError as error:
print(f"[ERROR] [vLLM] {error}")
subprocess.run(["pip", "install", "vllm"])
raise error
class vLLM(AbstractLLM):
"""vLLM model
Args:
model_name (str, optional): _description_. Defaults to "facebook/opt-13b".
tensor_parallel_size (int, optional): _description_. Defaults to 4.
trust_remote_code (bool, optional): _description_. Defaults to False.
revision (str, optional): _description_. Defaults to None.
temperature (float, optional): _description_. Defaults to 0.5.
top_p (float, optional): _description_. Defaults to 0.95.
*args: _description_.
**kwargs: _description_.
Methods:
run: run the vLLM model
Raises:
error: _description_
Examples:
>>> from swarms.models.vllm import vLLM
>>> vllm = vLLM()
>>> vllm.run("Hello world!")
"""
def __init__(
self,
model_name: str = "facebook/opt-13b",
tensor_parallel_size: int = 4,
trust_remote_code: bool = False,
revision: str = None,
temperature: float = 0.5,
top_p: float = 0.95,
*args,
**kwargs,
):
super().__init__(*args, **kwargs)
self.model_name = model_name
self.tensor_parallel_size = tensor_parallel_size
self.trust_remote_code = trust_remote_code
self.revision = revision
self.top_p = top_p
# LLM model
self.llm = LLM(
model_name=self.model_name,
tensor_parallel_size=self.tensor_parallel_size,
trust_remote_code=self.trust_remote_code,
revision=self.revision,
*args,
**kwargs,
)
# Sampling parameters
self.sampling_params = SamplingParams(
temperature=temperature, top_p=top_p, *args, **kwargs
)
def run(self, task: str = None, *args, **kwargs):
"""Run the vLLM model
Args:
task (str, optional): _description_. Defaults to None.
Raises:
error: _description_
Returns:
_type_: _description_
"""
try:
outputs = self.llm.generate(task, self.sampling_params)
return outputs
except Exception as error:
print(f"[ERROR] [vLLM] [run] {error}")
raise error

@ -0,0 +1,141 @@
import pytest
from swarms.models.vllm import vLLM
# Fixture for initializing vLLM
@pytest.fixture
def vllm_instance():
return vLLM()
# Test the default initialization of vLLM
def test_vllm_default_init(vllm_instance):
assert isinstance(vllm_instance, vLLM)
assert vllm_instance.model_name == "facebook/opt-13b"
assert vllm_instance.tensor_parallel_size == 4
assert not vllm_instance.trust_remote_code
assert vllm_instance.revision is None
assert vllm_instance.temperature == 0.5
assert vllm_instance.top_p == 0.95
# Test custom initialization of vLLM
def test_vllm_custom_init():
vllm_instance = vLLM(
model_name="custom_model",
tensor_parallel_size=8,
trust_remote_code=True,
revision="123",
temperature=0.7,
top_p=0.9,
)
assert isinstance(vllm_instance, vLLM)
assert vllm_instance.model_name == "custom_model"
assert vllm_instance.tensor_parallel_size == 8
assert vllm_instance.trust_remote_code
assert vllm_instance.revision == "123"
assert vllm_instance.temperature == 0.7
assert vllm_instance.top_p == 0.9
# Test the run method of vLLM
def test_vllm_run(vllm_instance):
task = "Hello, vLLM!"
result = vllm_instance.run(task)
assert isinstance(result, str)
assert len(result) > 0
# Test run method with different temperature and top_p values
@pytest.mark.parametrize(
"temperature, top_p", [(0.2, 0.8), (0.8, 0.2)]
)
def test_vllm_run_with_params(vllm_instance, temperature, top_p):
task = "Temperature and Top-P Test"
result = vllm_instance.run(
task, temperature=temperature, top_p=top_p
)
assert isinstance(result, str)
assert len(result) > 0
# Test run method with a specific model revision
def test_vllm_run_with_revision(vllm_instance):
task = "Specific Model Revision Test"
result = vllm_instance.run(task, revision="abc123")
assert isinstance(result, str)
assert len(result) > 0
# Test run method with a specific model name
def test_vllm_run_with_custom_model(vllm_instance):
task = "Custom Model Test"
custom_model_name = "my_custom_model"
result = vllm_instance.run(task, model_name=custom_model_name)
assert isinstance(result, str)
assert len(result) > 0
assert vllm_instance.model_name == custom_model_name
# Test run method with invalid task input
def test_vllm_run_invalid_task(vllm_instance):
invalid_task = None
with pytest.raises(ValueError):
vllm_instance.run(invalid_task)
# Test run method with a very high temperature value
def test_vllm_run_high_temperature(vllm_instance):
task = "High Temperature Test"
high_temperature = 10.0
result = vllm_instance.run(task, temperature=high_temperature)
assert isinstance(result, str)
assert len(result) > 0
# Test run method with a very low top_p value
def test_vllm_run_low_top_p(vllm_instance):
task = "Low Top-P Test"
low_top_p = 0.01
result = vllm_instance.run(task, top_p=low_top_p)
assert isinstance(result, str)
assert len(result) > 0
# Test run method with an empty task
def test_vllm_run_empty_task(vllm_instance):
empty_task = ""
result = vllm_instance.run(empty_task)
assert isinstance(result, str)
assert len(result) == 0
# Test initialization with invalid parameters
def test_vllm_invalid_init():
with pytest.raises(ValueError):
vllm_instance = vLLM(
model_name=None,
tensor_parallel_size=-1,
trust_remote_code="invalid",
revision=123,
temperature=-0.1,
top_p=1.1,
)
# Test running vLLM with a large number of parallel heads
def test_vllm_large_parallel_heads():
vllm_instance = vLLM(tensor_parallel_size=16)
task = "Large Parallel Heads Test"
result = vllm_instance.run(task)
assert isinstance(result, str)
assert len(result) > 0
# Test running vLLM with trust_remote_code set to True
def test_vllm_trust_remote_code():
vllm_instance = vLLM(trust_remote_code=True)
task = "Trust Remote Code Test"
result = vllm_instance.run(task)
assert isinstance(result, str)
assert len(result) > 0
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