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chore: import upstream snapshot with attribution
2026-07-13 13:03:45 +08:00

105 lines
3.9 KiB
Python

from unittest.mock import Mock, patch
import pytest
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.together import TogetherLLM
@pytest.fixture
def mock_together_client():
with patch("mem0.llms.together.Together") as mock_together:
mock_client = Mock()
mock_together.return_value = mock_client
yield mock_client
def test_generate_response_without_tools(mock_together_client):
config = BaseLlmConfig(model="mistralai/Mixtral-8x7B-Instruct-v0.1", temperature=0.7, max_tokens=100, top_p=1.0)
llm = TogetherLLM(config)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello, how are you?"},
]
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="I'm doing well, thank you for asking!"))]
mock_together_client.chat.completions.create.return_value = mock_response
response = llm.generate_response(messages)
mock_together_client.chat.completions.create.assert_called_once_with(
model="mistralai/Mixtral-8x7B-Instruct-v0.1", messages=messages, temperature=0.7, max_tokens=100, top_p=1.0
)
assert response == "I'm doing well, thank you for asking!"
def test_generate_response_with_tools(mock_together_client):
config = BaseLlmConfig(model="mistralai/Mixtral-8x7B-Instruct-v0.1", temperature=0.7, max_tokens=100, top_p=1.0)
llm = TogetherLLM(config)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Add a new memory: Today is a sunny day."},
]
tools = [
{
"type": "function",
"function": {
"name": "add_memory",
"description": "Add a memory",
"parameters": {
"type": "object",
"properties": {"data": {"type": "string", "description": "Data to add to memory"}},
"required": ["data"],
},
},
}
]
mock_response = Mock()
mock_message = Mock()
mock_message.content = "I've added the memory for you."
mock_tool_call = Mock()
mock_tool_call.function.name = "add_memory"
mock_tool_call.function.arguments = '{"data": "Today is a sunny day."}'
mock_message.tool_calls = [mock_tool_call]
mock_response.choices = [Mock(message=mock_message)]
mock_together_client.chat.completions.create.return_value = mock_response
response = llm.generate_response(messages, tools=tools)
mock_together_client.chat.completions.create.assert_called_once_with(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
messages=messages,
temperature=0.7,
max_tokens=100,
top_p=1.0,
tools=tools,
tool_choice="auto",
)
assert response["content"] == "I've added the memory for you."
assert len(response["tool_calls"]) == 1
assert response["tool_calls"][0]["name"] == "add_memory"
assert response["tool_calls"][0]["arguments"] == {"data": "Today is a sunny day."}
def test_generate_response_forwards_extra_kwargs(mock_together_client):
"""Per the LLMBase contract, extra provider-specific kwargs must be accepted and
forwarded to the Together client (matching openai/deepseek/vllm/xai behavior)."""
config = BaseLlmConfig(model="mistralai/Mixtral-8x7B-Instruct-v0.1", temperature=0.7, max_tokens=100, top_p=1.0)
llm = TogetherLLM(config)
messages = [{"role": "user", "content": "Hello"}]
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="Hi"))]
mock_together_client.chat.completions.create.return_value = mock_response
response = llm.generate_response(messages, frequency_penalty=0.5)
assert response == "Hi"
call_kwargs = mock_together_client.chat.completions.create.call_args.kwargs
assert call_kwargs["frequency_penalty"] == 0.5