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

82 lines
3.1 KiB
Python

"""Test HuggingFace Endpoints."""
from pathlib import Path
import pytest
from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
from langchain_community.llms.loading import load_llm
from tests.integration_tests.llms.utils import assert_llm_equality
def test_huggingface_endpoint_call_error() -> None:
"""Test valid call to HuggingFace that errors."""
llm = HuggingFaceEndpoint(endpoint_url="", model_kwargs={"max_new_tokens": -1}) # type: ignore[call-arg]
with pytest.raises(ValueError):
llm.invoke("Say foo:")
def test_saving_loading_endpoint_llm(tmp_path: Path) -> None:
"""Test saving/loading an HuggingFaceHub LLM."""
llm = HuggingFaceEndpoint( # type: ignore[call-arg]
endpoint_url="", task="text-generation", model_kwargs={"max_new_tokens": 10}
)
llm.save(file_path=tmp_path / "hf.yaml")
loaded_llm = load_llm(tmp_path / "hf.yaml")
assert_llm_equality(llm, loaded_llm)
def test_huggingface_text_generation() -> None:
"""Test valid call to HuggingFace text generation model."""
llm = HuggingFaceEndpoint(repo_id="gpt2", model_kwargs={"max_new_tokens": 10}) # type: ignore[call-arg]
output = llm.invoke("Say foo:")
print(output) # noqa: T201
assert isinstance(output, str)
def test_huggingface_text2text_generation() -> None:
"""Test valid call to HuggingFace text2text model."""
llm = HuggingFaceEndpoint(repo_id="google/flan-t5-xl") # type: ignore[call-arg]
output = llm.invoke("The capital of New York is")
assert output == "Albany"
def test_huggingface_summarization() -> None:
"""Test valid call to HuggingFace summarization model."""
llm = HuggingFaceEndpoint(repo_id="facebook/bart-large-cnn") # type: ignore[call-arg]
output = llm.invoke("Say foo:")
assert isinstance(output, str)
def test_huggingface_call_error() -> None:
"""Test valid call to HuggingFace that errors."""
llm = HuggingFaceEndpoint(repo_id="gpt2", model_kwargs={"max_new_tokens": -1}) # type: ignore[call-arg]
with pytest.raises(ValueError):
llm.invoke("Say foo:")
def test_saving_loading_llm(tmp_path: Path) -> None:
"""Test saving/loading an HuggingFaceEndpoint LLM."""
llm = HuggingFaceEndpoint(repo_id="gpt2", model_kwargs={"max_new_tokens": 10}) # type: ignore[call-arg]
llm.save(file_path=tmp_path / "hf.yaml")
loaded_llm = load_llm(tmp_path / "hf.yaml")
assert_llm_equality(llm, loaded_llm)
def test_invocation_params_stop_sequences() -> None:
llm = HuggingFaceEndpoint() # type: ignore[call-arg]
assert llm._default_params["stop_sequences"] == []
runtime_stop = None
assert llm._invocation_params(runtime_stop)["stop_sequences"] == []
assert llm._default_params["stop_sequences"] == []
runtime_stop = ["stop"]
assert llm._invocation_params(runtime_stop)["stop_sequences"] == ["stop"]
assert llm._default_params["stop_sequences"] == []
llm = HuggingFaceEndpoint(stop_sequences=["."]) # type: ignore[call-arg]
runtime_stop = ["stop"]
assert llm._invocation_params(runtime_stop)["stop_sequences"] == [".", "stop"]
assert llm._default_params["stop_sequences"] == ["."]