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

216 lines
7.7 KiB
Python

import os
from unittest.mock import Mock, patch
import pytest
from mem0.configs.llms.base import BaseLlmConfig
from mem0.configs.llms.xai import XAIConfig
from mem0.llms.xai import XAILLM
from mem0.utils.factory import LlmFactory
@pytest.fixture
def mock_xai_client():
with patch("mem0.llms.xai.OpenAI") as mock_openai:
mock_client = Mock()
mock_openai.return_value = mock_client
yield mock_client
def test_xai_llm_base_url():
# case1: default
config = XAIConfig(model="grok-4.3", api_key="api_key")
llm = XAILLM(config)
assert str(llm.client.base_url) == "https://api.x.ai/v1/"
# case2: XAI_API_BASE env var
os.environ["XAI_API_BASE"] = "https://api.provider.com/v1"
config = XAIConfig(model="grok-4.3", api_key="api_key")
llm = XAILLM(config)
assert str(llm.client.base_url) == "https://api.provider.com/v1/"
# case3: config.xai_base_url wins over env
config = XAIConfig(
model="grok-4.3",
api_key="api_key",
xai_base_url="https://api.config.com/v1",
)
llm = XAILLM(config)
assert str(llm.client.base_url) == "https://api.config.com/v1/"
def test_xai_defaults_to_current_grok_model():
# No model supplied -> provider falls back to the current default (grok-4.3).
llm = XAILLM(XAIConfig(api_key="k"))
assert llm.config.model == "grok-4.3"
def test_xai_accepts_base_llm_config():
# Used to AttributeError on self.config.xai_base_url because the factory
# wired XAI with plain BaseLlmConfig.
llm = XAILLM(BaseLlmConfig(model="grok-4.3", api_key="k"))
assert isinstance(llm.config, XAIConfig)
assert llm.config.xai_base_url is None
def test_generate_response_without_tools(mock_xai_client):
config = XAIConfig(model="grok-4.3", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key")
llm = XAILLM(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_xai_client.chat.completions.create.return_value = mock_response
response = llm.generate_response(messages)
mock_xai_client.chat.completions.create.assert_called_once_with(
model="grok-4.3",
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_xai_client):
config = XAIConfig(model="grok-4.3", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key")
llm = XAILLM(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_xai_client.chat.completions.create.return_value = mock_response
response = llm.generate_response(messages, tools=tools)
mock_xai_client.chat.completions.create.assert_called_once_with(
model="grok-4.3",
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 response["tool_calls"] == [{"name": "add_memory", "arguments": {"data": "Today is a sunny day."}}]
def test_empty_tools_list_not_forwarded(mock_xai_client):
# tools=[] would otherwise get rejected by some OpenAI-compatible backends
config = XAIConfig(model="grok-4.3", api_key="api_key")
llm = XAILLM(config)
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="hello"))]
mock_xai_client.chat.completions.create.return_value = mock_response
response = llm.generate_response([{"role": "user", "content": "hi"}], tools=[])
call_kwargs = mock_xai_client.chat.completions.create.call_args.kwargs
assert "tools" not in call_kwargs
assert "tool_choice" not in call_kwargs
assert response == "hello"
def test_tools_requested_but_model_returns_no_calls(mock_xai_client):
# Model can decline to call any tool even when offered
config = XAIConfig(model="grok-4.3", api_key="api_key")
llm = XAILLM(config)
tools = [{"type": "function", "function": {"name": "f", "parameters": {"type": "object", "properties": {}}}}]
mock_message = Mock(content="just a chat reply")
mock_message.tool_calls = None
mock_xai_client.chat.completions.create.return_value = Mock(choices=[Mock(message=mock_message)])
response = llm.generate_response([{"role": "user", "content": "x"}], tools=tools)
assert response == {"content": "just a chat reply", "tool_calls": []}
def test_generate_response_with_response_format(mock_xai_client):
config = XAIConfig(model="grok-4.3", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key")
llm = XAILLM(config)
messages = [
{"role": "system", "content": "You are a memory extraction assistant."},
{"role": "user", "content": "I like hiking on weekends."},
]
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content='{"facts": ["User likes hiking on weekends"]}'))]
mock_xai_client.chat.completions.create.return_value = mock_response
response = llm.generate_response(messages, response_format={"type": "json_object"})
mock_xai_client.chat.completions.create.assert_called_once_with(
model="grok-4.3",
messages=messages,
temperature=0.7,
max_tokens=100,
top_p=1.0,
response_format={"type": "json_object"},
)
assert response == '{"facts": ["User likes hiking on weekends"]}'
def test_generate_response_without_response_format(mock_xai_client):
config = XAIConfig(model="grok-4.3", api_key="api_key")
llm = XAILLM(config)
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="hi"))]
mock_xai_client.chat.completions.create.return_value = mock_response
llm.generate_response([{"role": "user", "content": "hi"}])
call_kwargs = mock_xai_client.chat.completions.create.call_args.kwargs
assert "response_format" not in call_kwargs
def test_factory_creates_xai_from_dict():
with patch("mem0.llms.xai.OpenAI") as mock_openai:
mock_openai.return_value = Mock()
llm = LlmFactory.create(
"xai",
{"model": "grok-4.3", "api_key": "k", "xai_base_url": "https://example.com/v1"},
)
assert isinstance(llm, XAILLM)
assert isinstance(llm.config, XAIConfig)
assert llm.config.xai_base_url == "https://example.com/v1"
def test_factory_creates_xai_from_base_config():
# Legacy callers still hand the factory a plain BaseLlmConfig
with patch("mem0.llms.xai.OpenAI") as mock_openai:
mock_openai.return_value = Mock()
llm = LlmFactory.create("xai", BaseLlmConfig(model="grok-4.3", api_key="k"))
assert isinstance(llm.config, XAIConfig)