fleet-memory/hindsight-api/tests/test_minimax_provider.py
Ethan Clarke 2344484f77
feat: add MiniMax LLM provider support (#550)
Add MiniMax as a supported LLM provider via the OpenAI-compatible interface.

- Register MiniMax in the provider factory and valid providers list
- Set default base URL to https://api.minimax.io/v1
- Set default model to MiniMax-M2.5 in PROVIDER_DEFAULT_MODELS
- Add temperature clamping for MiniMax (must be >0, ≤1.0)
- Add API key validation (MiniMax requires an API key)
- Add MiniMax configuration example to .env.example
- Update documentation (models.md, configuration.md, embed.md, CLAUDE.md, README.md)
- Add unit and integration tests for MiniMax provider

Co-authored-by: octo-patch <octo-patch@users.noreply.github.com>
2026-03-13 10:17:55 +01:00

200 lines
6 KiB
Python

"""Tests for MiniMax provider integration.
Validates that MiniMax is correctly registered as an OpenAI-compatible provider
with proper base URL, temperature clamping, and default model configuration.
"""
import os
import pytest
from hindsight_api.engine.llm_wrapper import LLMProvider, create_llm
def test_minimax_provider_creation():
"""Test that MiniMax provider can be instantiated correctly."""
llm = LLMProvider(
provider="minimax",
api_key="test-key",
base_url="",
model="MiniMax-M2.5",
)
assert llm.provider == "minimax"
assert llm.model == "MiniMax-M2.5"
assert llm.base_url == "https://api.minimax.io/v1"
def test_minimax_default_base_url():
"""Test that MiniMax uses the correct default base URL when none is provided."""
llm = LLMProvider(
provider="minimax",
api_key="test-key",
base_url="",
model="MiniMax-M2.5",
)
assert llm.base_url == "https://api.minimax.io/v1"
def test_minimax_custom_base_url():
"""Test that a custom base URL overrides the default."""
llm = LLMProvider(
provider="minimax",
api_key="test-key",
base_url="https://custom.api.example.com/v1",
model="MiniMax-M2.5",
)
assert llm.base_url == "https://custom.api.example.com/v1"
def test_minimax_factory_function():
"""Test that the create_llm factory function creates MiniMax provider correctly."""
llm = create_llm(
provider="minimax",
api_key="test-key",
base_url="",
model="MiniMax-M2.5",
)
assert llm is not None
def test_minimax_requires_api_key():
"""Test that MiniMax provider requires an API key."""
with pytest.raises(ValueError, match="API key"):
LLMProvider(
provider="minimax",
api_key="",
base_url="",
model="MiniMax-M2.5",
)
def test_minimax_default_model_config():
"""Test that MiniMax has a default model in PROVIDER_DEFAULT_MODELS."""
from hindsight_api.config import PROVIDER_DEFAULT_MODELS
assert "minimax" in PROVIDER_DEFAULT_MODELS
assert PROVIDER_DEFAULT_MODELS["minimax"] == "MiniMax-M2.5"
def test_minimax_config_default_model():
"""Test that MiniMax default model is used when model is not explicitly set."""
from hindsight_api.config import HindsightConfig, clear_config_cache
original_provider = os.environ.get("HINDSIGHT_API_LLM_PROVIDER")
original_model = os.environ.get("HINDSIGHT_API_LLM_MODEL")
try:
clear_config_cache()
os.environ["HINDSIGHT_API_LLM_PROVIDER"] = "minimax"
if "HINDSIGHT_API_LLM_MODEL" in os.environ:
del os.environ["HINDSIGHT_API_LLM_MODEL"]
config = HindsightConfig.from_env()
assert config.llm_provider == "minimax"
assert config.llm_model == "MiniMax-M2.5"
finally:
clear_config_cache()
if original_provider:
os.environ["HINDSIGHT_API_LLM_PROVIDER"] = original_provider
elif "HINDSIGHT_API_LLM_PROVIDER" in os.environ:
del os.environ["HINDSIGHT_API_LLM_PROVIDER"]
if original_model:
os.environ["HINDSIGHT_API_LLM_MODEL"] = original_model
elif "HINDSIGHT_API_LLM_MODEL" in os.environ:
del os.environ["HINDSIGHT_API_LLM_MODEL"]
def test_minimax_temperature_clamping():
"""Test that MiniMax temperature is clamped to (0.0, 1.0] range."""
from hindsight_api.engine.providers.openai_compatible_llm import OpenAICompatibleLLM
llm = OpenAICompatibleLLM(
provider="minimax",
api_key="test-key",
base_url="https://api.minimax.io/v1",
model="MiniMax-M2.5",
)
# Verify the provider is correctly set up for temperature clamping
assert llm.provider == "minimax"
@pytest.mark.asyncio
async def test_minimax_integration():
"""Integration test: verify MiniMax provider works with actual API.
Requires MINIMAX_API_KEY environment variable to be set.
"""
api_key = os.environ.get("MINIMAX_API_KEY")
if not api_key:
pytest.skip("MINIMAX_API_KEY not set")
llm = LLMProvider(
provider="minimax",
api_key=api_key,
base_url="",
model="MiniMax-M2.5",
)
# Test verify_connection
await llm.verify_connection()
# Test basic call
response = await llm.call(
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is 2+2? Answer in one word."},
],
max_completion_tokens=50,
)
assert response is not None
assert len(response) > 0
@pytest.mark.asyncio
async def test_minimax_tool_calling():
"""Integration test: verify MiniMax provider supports tool calling.
Requires MINIMAX_API_KEY environment variable to be set.
"""
api_key = os.environ.get("MINIMAX_API_KEY")
if not api_key:
pytest.skip("MINIMAX_API_KEY not set")
llm = LLMProvider(
provider="minimax",
api_key=api_key,
base_url="",
model="MiniMax-M2.5",
)
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"},
},
"required": ["location"],
},
},
}
]
result = await llm.call_with_tools(
messages=[
{"role": "system", "content": "You are a helpful assistant with access to tools."},
{"role": "user", "content": "What's the weather like in Paris?"},
],
tools=tools,
max_completion_tokens=500,
)
assert result is not None
assert hasattr(result, "tool_calls")
assert len(result.tool_calls) > 0
assert result.tool_calls[0].name == "get_weather"