dify/api/tests/integration_tests/model_runtime/huggingface_tei/test_embeddings.py

import os

import pytest

from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.huggingface_tei.text_embedding.text_embedding import (
    HuggingfaceTeiTextEmbeddingModel,
    TeiHelper,
)
from tests.integration_tests.model_runtime.__mock.huggingface_tei import MockTEIClass

MOCK = os.getenv('MOCK_SWITCH', 'false').lower() == 'true'


@pytest.fixture
def setup_tei_mock(request, monkeypatch: pytest.MonkeyPatch):
    if MOCK:
        monkeypatch.setattr(TeiHelper, 'get_tei_extra_parameter', MockTEIClass.get_tei_extra_parameter)
        monkeypatch.setattr(TeiHelper, 'invoke_tokenize', MockTEIClass.invoke_tokenize)
        monkeypatch.setattr(TeiHelper, 'invoke_embeddings', MockTEIClass.invoke_embeddings)
        monkeypatch.setattr(TeiHelper, 'invoke_rerank', MockTEIClass.invoke_rerank)
    yield

    if MOCK:
        monkeypatch.undo()


@pytest.mark.parametrize('setup_tei_mock', [['none']], indirect=True)
def test_validate_credentials(setup_tei_mock):
    model = HuggingfaceTeiTextEmbeddingModel()
    # model name is only used in mock
    model_name = 'embedding'

    if MOCK:
        # TEI Provider will check model type by API endpoint, at real server, the model type is correct.
        # So we dont need to check model type here. Only check in mock
        with pytest.raises(CredentialsValidateFailedError):
            model.validate_credentials(
                model='reranker',
                credentials={
                    'server_url': os.environ.get('TEI_EMBEDDING_SERVER_URL', ""),
                }
            )

    model.validate_credentials(
        model=model_name,
        credentials={
            'server_url': os.environ.get('TEI_EMBEDDING_SERVER_URL', ""),
        }
    )

@pytest.mark.parametrize('setup_tei_mock', [['none']], indirect=True)
def test_invoke_model(setup_tei_mock):
    model = HuggingfaceTeiTextEmbeddingModel()
    model_name = 'embedding'

    result = model.invoke(
        model=model_name,
        credentials={
            'server_url': os.environ.get('TEI_EMBEDDING_SERVER_URL', ""),
        },
        texts=[
            "hello",
            "world"
        ],
        user="abc-123"
    )

    assert isinstance(result, TextEmbeddingResult)
    assert len(result.embeddings) == 2
    assert result.usage.total_tokens > 0