f5c4ab50f4
* auto fixes * auto fix pt2 and transitive deps and undefined var checking locals() * manual fixes (ignored or letta-code fixed) * fix circular import * remove all ignores, add FastAPI rules and Ruff rules * add ty and precommit * ruff stuff * ty check fixes * ty check fixes pt 2 * error on invalid
274 lines
11 KiB
Python
274 lines
11 KiB
Python
"""Unit tests for MiniMax client."""
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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from letta.llm_api.minimax_client import MiniMaxClient
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from letta.schemas.enums import AgentType
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from letta.schemas.llm_config import LLMConfig
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# MiniMax API base URL
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MINIMAX_BASE_URL = "https://api.minimax.io/anthropic"
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class TestMiniMaxClient:
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"""Tests for MiniMaxClient."""
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def setup_method(self):
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"""Set up test fixtures."""
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self.client = MiniMaxClient(put_inner_thoughts_first=True)
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self.llm_config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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)
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def test_is_reasoning_model_always_true(self):
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"""All MiniMax models support native interleaved thinking."""
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assert self.client.is_reasoning_model(self.llm_config) is True
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# Test with different models
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for model_name in ["MiniMax-M2.1", "MiniMax-M2.1-lightning", "MiniMax-M2"]:
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config = LLMConfig(
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model=model_name,
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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)
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assert self.client.is_reasoning_model(config) is True
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def test_requires_auto_tool_choice(self):
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"""MiniMax supports all tool choice modes."""
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assert self.client.requires_auto_tool_choice(self.llm_config) is False
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def test_supports_structured_output(self):
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"""MiniMax doesn't currently advertise structured output support."""
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assert self.client.supports_structured_output(self.llm_config) is False
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@patch("letta.llm_api.minimax_client.model_settings")
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def test_get_anthropic_client_with_api_key(self, mock_settings):
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"""Test client creation with API key."""
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mock_settings.minimax_api_key = "test-api-key"
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with patch("letta.llm_api.minimax_client.anthropic") as mock_anthropic:
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mock_anthropic.Anthropic.return_value = MagicMock()
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# Mock BYOK to return no override
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self.client.get_byok_overrides = MagicMock(return_value=(None, None, None))
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self.client._get_anthropic_client(self.llm_config, async_client=False)
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mock_anthropic.Anthropic.assert_called_once_with(
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api_key="test-api-key",
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base_url=MINIMAX_BASE_URL,
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)
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@patch("letta.llm_api.minimax_client.model_settings")
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def test_get_anthropic_client_async(self, mock_settings):
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"""Test async client creation."""
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mock_settings.minimax_api_key = "test-api-key"
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with patch("letta.llm_api.minimax_client.anthropic") as mock_anthropic:
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mock_anthropic.AsyncAnthropic.return_value = MagicMock()
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# Mock BYOK to return no override
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self.client.get_byok_overrides = MagicMock(return_value=(None, None, None))
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self.client._get_anthropic_client(self.llm_config, async_client=True)
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mock_anthropic.AsyncAnthropic.assert_called_once_with(
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api_key="test-api-key",
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base_url=MINIMAX_BASE_URL,
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)
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class TestMiniMaxClientTemperatureClamping:
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"""Tests for temperature clamping in build_request_data."""
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def setup_method(self):
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"""Set up test fixtures."""
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self.client = MiniMaxClient(put_inner_thoughts_first=True)
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self.llm_config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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temperature=0.7,
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)
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@patch.object(MiniMaxClient, "build_request_data")
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def test_temperature_clamping_is_applied(self, mock_build):
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"""Verify build_request_data is called for temperature clamping."""
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# This is a basic test to ensure the method exists and can be called
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mock_build.return_value = {"temperature": 0.7}
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self.client.build_request_data(
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agent_type=AgentType.letta_v1_agent,
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messages=[],
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llm_config=self.llm_config,
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)
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mock_build.assert_called_once()
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def test_temperature_zero_clamped(self):
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"""Test that temperature=0 is clamped to 0.01."""
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config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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temperature=0,
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)
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# Mock the parent class method to return a basic dict
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with patch.object(MiniMaxClient.__bases__[0], "build_request_data") as mock_parent:
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mock_parent.return_value = {"temperature": 0, "model": "MiniMax-M2.1"}
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result = self.client.build_request_data(
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agent_type=AgentType.letta_v1_agent,
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messages=[],
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llm_config=config,
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)
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# Temperature should be clamped to 0.01
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assert result["temperature"] == 0.01
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def test_temperature_negative_clamped(self):
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"""Test that negative temperature is clamped to 0.01."""
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config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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temperature=-0.5,
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)
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with patch.object(MiniMaxClient.__bases__[0], "build_request_data") as mock_parent:
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mock_parent.return_value = {"temperature": -0.5, "model": "MiniMax-M2.1"}
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result = self.client.build_request_data(
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agent_type=AgentType.letta_v1_agent,
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messages=[],
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llm_config=config,
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)
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assert result["temperature"] == 0.01
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def test_temperature_above_one_clamped(self):
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"""Test that temperature > 1.0 is clamped to 1.0."""
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config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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temperature=1.5,
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)
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with patch.object(MiniMaxClient.__bases__[0], "build_request_data") as mock_parent:
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mock_parent.return_value = {"temperature": 1.5, "model": "MiniMax-M2.1"}
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result = self.client.build_request_data(
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agent_type=AgentType.letta_v1_agent,
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messages=[],
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llm_config=config,
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)
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assert result["temperature"] == 1.0
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def test_temperature_valid_not_modified(self):
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"""Test that valid temperature values are not modified."""
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config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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temperature=0.7,
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)
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with patch.object(MiniMaxClient.__bases__[0], "build_request_data") as mock_parent:
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mock_parent.return_value = {"temperature": 0.7, "model": "MiniMax-M2.1"}
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result = self.client.build_request_data(
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agent_type=AgentType.letta_v1_agent,
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messages=[],
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llm_config=config,
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)
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assert result["temperature"] == 0.7
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class TestMiniMaxClientUsesNonBetaAPI:
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"""Tests to verify MiniMax client uses non-beta API."""
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def test_request_uses_messages_not_beta(self):
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"""Verify request() uses client.messages.create, not client.beta.messages.create."""
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client = MiniMaxClient(put_inner_thoughts_first=True)
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llm_config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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)
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with patch.object(client, "_get_anthropic_client") as mock_get_client:
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mock_anthropic_client = MagicMock()
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mock_response = MagicMock()
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mock_response.model_dump.return_value = {"content": [{"type": "text", "text": "Hello"}]}
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mock_anthropic_client.messages.create.return_value = mock_response
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mock_get_client.return_value = mock_anthropic_client
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client.request({"model": "MiniMax-M2.1"}, llm_config)
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# Verify messages.create was called (not beta.messages.create)
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mock_anthropic_client.messages.create.assert_called_once()
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# Verify beta was NOT accessed
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assert not hasattr(mock_anthropic_client, "beta") or not mock_anthropic_client.beta.messages.create.called
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@pytest.mark.asyncio
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async def test_request_async_uses_messages_not_beta(self):
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"""Verify request_async() uses client.messages.create, not client.beta.messages.create."""
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client = MiniMaxClient(put_inner_thoughts_first=True)
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llm_config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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)
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with patch.object(client, "_get_anthropic_client_async") as mock_get_client:
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mock_anthropic_client = AsyncMock()
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mock_response = MagicMock()
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mock_response.model_dump.return_value = {"content": [{"type": "text", "text": "Hello"}]}
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mock_anthropic_client.messages.create.return_value = mock_response
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mock_get_client.return_value = mock_anthropic_client
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await client.request_async({"model": "MiniMax-M2.1"}, llm_config)
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# Verify messages.create was called (not beta.messages.create)
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mock_anthropic_client.messages.create.assert_called_once()
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@pytest.mark.asyncio
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async def test_stream_async_uses_messages_not_beta(self):
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"""Verify stream_async() uses client.messages.create, not client.beta.messages.create."""
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client = MiniMaxClient(put_inner_thoughts_first=True)
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llm_config = LLMConfig(
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model="MiniMax-M2.1",
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model_endpoint_type="minimax",
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model_endpoint=MINIMAX_BASE_URL,
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context_window=200000,
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)
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with patch.object(client, "_get_anthropic_client_async") as mock_get_client:
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mock_anthropic_client = AsyncMock()
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mock_stream = AsyncMock()
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mock_anthropic_client.messages.create.return_value = mock_stream
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mock_get_client.return_value = mock_anthropic_client
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await client.stream_async({"model": "MiniMax-M2.1"}, llm_config)
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# Verify messages.create was called (not beta.messages.create)
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mock_anthropic_client.messages.create.assert_called_once()
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# Verify stream=True was set
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call_kwargs = mock_anthropic_client.messages.create.call_args[1]
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assert call_kwargs.get("stream") is True
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