mirror of
https://github.com/langgenius/dify.git
synced 2025-10-31 02:42:59 +00:00
63 lines
1.9 KiB
Python
63 lines
1.9 KiB
Python
import json
|
|
import os
|
|
from unittest.mock import patch
|
|
|
|
from langchain.schema import ChatGeneration, AIMessage
|
|
|
|
from core.model_providers.models.entity.message import PromptMessage, MessageType
|
|
from core.model_providers.models.entity.model_params import ModelKwargs
|
|
from core.model_providers.models.llm.anthropic_model import AnthropicModel
|
|
from core.model_providers.providers.anthropic_provider import AnthropicProvider
|
|
from models.provider import Provider, ProviderType
|
|
|
|
|
|
def get_mock_provider(valid_api_key):
|
|
return Provider(
|
|
id='provider_id',
|
|
tenant_id='tenant_id',
|
|
provider_name='anthropic',
|
|
provider_type=ProviderType.CUSTOM.value,
|
|
encrypted_config=json.dumps({'anthropic_api_key': valid_api_key}),
|
|
is_valid=True,
|
|
)
|
|
|
|
|
|
def get_mock_model(model_name):
|
|
model_kwargs = ModelKwargs(
|
|
max_tokens=10,
|
|
temperature=0
|
|
)
|
|
valid_api_key = os.environ['ANTHROPIC_API_KEY']
|
|
model_provider = AnthropicProvider(provider=get_mock_provider(valid_api_key))
|
|
return AnthropicModel(
|
|
model_provider=model_provider,
|
|
name=model_name,
|
|
model_kwargs=model_kwargs
|
|
)
|
|
|
|
|
|
def decrypt_side_effect(tenant_id, encrypted_api_key):
|
|
return encrypted_api_key
|
|
|
|
|
|
@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
|
|
def test_get_num_tokens(mock_decrypt):
|
|
model = get_mock_model('claude-2')
|
|
rst = model.get_num_tokens([
|
|
PromptMessage(type=MessageType.HUMAN, content='Who is your manufacturer?')
|
|
])
|
|
assert rst == 6
|
|
|
|
|
|
@patch('core.helper.encrypter.decrypt_token', side_effect=decrypt_side_effect)
|
|
def test_run(mock_decrypt, mocker):
|
|
mocker.patch('core.model_providers.providers.base.BaseModelProvider.update_last_used', return_value=None)
|
|
|
|
model = get_mock_model('claude-2')
|
|
messages = [PromptMessage(content='Human: 1 + 1=? \nAssistant: ')]
|
|
rst = model.run(
|
|
messages,
|
|
stop=['\nHuman:'],
|
|
)
|
|
assert len(rst.content) > 0
|