Files
mem0/tests/llms/test_together.py
kartik-mem0 2ef6291307 fix(llms,embeddings): honor TOGETHER_API_BASE for Together LLM and embedder
The Python Together LLM and embedder ignored TOGETHER_API_BASE, unlike
their TypeScript siblings, so users behind a gateway or proxy could not
redirect Together traffic. Add together_base_url to a new TogetherConfig
(LLM side) and to BaseEmbedderConfig (embedder side, matching the existing
openai_base_url/huggingface_base_url pattern), and resolve base_url with
explicit config value > TOGETHER_API_BASE env var > hardcoded default in
both mem0/llms/together.py and mem0/embeddings/together.py. Also register
TogetherConfig in LlmFactory.provider_to_class so config dicts routed
through Memory pick it up.

Closes #6587
2026-08-13 19:41:09 +05:30

138 lines
5.1 KiB
Python

from unittest.mock import Mock, patch
import pytest
from mem0.configs.llms.base import BaseLlmConfig
from mem0.configs.llms.together import TogetherConfig
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_together_llm_base_url(monkeypatch):
# case1: default config uses Together's official base url
monkeypatch.delenv("TOGETHER_API_BASE", raising=False)
config = BaseLlmConfig(
model="mistralai/Mixtral-8x7B-Instruct-v0.1", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
)
llm = TogetherLLM(config)
assert str(llm.client.base_url) == "https://api.together.ai/v1/"
# case2: with env variable TOGETHER_API_BASE
provider_base_url = "https://api.provider.com/v1/"
monkeypatch.setenv("TOGETHER_API_BASE", provider_base_url)
config = TogetherConfig(
model="mistralai/Mixtral-8x7B-Instruct-v0.1", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
)
llm = TogetherLLM(config)
assert str(llm.client.base_url) == provider_base_url
# case3: with config.together_base_url (explicit config beats env var)
config_base_url = "https://api.config.com/v1/"
config = TogetherConfig(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
temperature=0.7,
max_tokens=100,
top_p=1.0,
api_key="api_key",
together_base_url=config_base_url,
)
llm = TogetherLLM(config)
assert str(llm.client.base_url) == config_base_url
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