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