langchain/tests/integration_tests/llms/test_huggingface_hub.py
whuwxl 3f0357f94a
Add summarization task type for HuggingFace APIs (#4721)
# Add summarization task type for HuggingFace APIs

Add summarization task type for HuggingFace APIs.
This task type is described by [HuggingFace inference
API](https://huggingface.co/docs/api-inference/detailed_parameters#summarization-task)

My project utilizes LangChain to connect multiple LLMs, including
various HuggingFace models that support the summarization task.
Integrating this task type is highly convenient and beneficial.

Fixes #4720
2023-05-15 16:26:17 -07:00

46 lines
1.5 KiB
Python

"""Test HuggingFace API wrapper."""
from pathlib import Path
import pytest
from langchain.llms.huggingface_hub import HuggingFaceHub
from langchain.llms.loading import load_llm
from tests.integration_tests.llms.utils import assert_llm_equality
def test_huggingface_text_generation() -> None:
"""Test valid call to HuggingFace text generation model."""
llm = HuggingFaceHub(repo_id="gpt2", model_kwargs={"max_new_tokens": 10})
output = llm("Say foo:")
assert isinstance(output, str)
def test_huggingface_text2text_generation() -> None:
"""Test valid call to HuggingFace text2text model."""
llm = HuggingFaceHub(repo_id="google/flan-t5-xl")
output = llm("The capital of New York is")
assert output == "Albany"
def test_huggingface_summarization() -> None:
"""Test valid call to HuggingFace summarization model."""
llm = HuggingFaceHub(repo_id="facebook/bart-large-cnn")
output = llm("Say foo:")
assert isinstance(output, str)
def test_huggingface_call_error() -> None:
"""Test valid call to HuggingFace that errors."""
llm = HuggingFaceHub(model_kwargs={"max_new_tokens": -1})
with pytest.raises(ValueError):
llm("Say foo:")
def test_saving_loading_llm(tmp_path: Path) -> None:
"""Test saving/loading an HuggingFaceHub LLM."""
llm = HuggingFaceHub(repo_id="gpt2", 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)