feat: upgrade MiniMax provider with M2.7 models and OpenAI-compatible API

[octo-patch]

Summary

Upgrade the MiniMax LLM provider integration to support the latest models and API endpoint:

• New MiniMaxAPI class with full-featured OpenAI-compatible API support via https://api.minimax.io/v1/chat/completions
• Latest models: MiniMax-M2.7, MiniMax-M2.5, MiniMax-M2.5-highspeed (up to 204K context)
• Environment variable support: MINIMAX_API_KEY with multi-key rotation
• Temperature clamping: Automatically clamps to MiniMax range [0, 1.0]
• Reasoning content handling: think_tag support for M2.5/M2.7 thinking models, inline <think>...</think> tag stripping
• System prompt support
• Model config files for easy evaluation setup
• 20 unit tests + 3 integration tests

The existing MiniMax and MiniMaxChatCompletionV2 classes are preserved for backward compatibility, with the default API URL updated from api.minimax.chat to api.minimax.io.

Changes

File	Change
opencompass/models/minimax_api.py	Add MiniMaxAPI class, update default URL
opencompass/models/__init__.py	Export MiniMaxAPI
opencompass/configs/models/minimax/	Config files for M2.7, M2.5, M2.5-highspeed
tests/models/test_minimax_api.py	20 unit tests + 3 integration tests

Usage

from opencompass.models import MiniMaxAPI

model = MiniMaxAPI(
    path="MiniMax-M2.7",
    key="ENV",  # reads from MINIMAX_API_KEY
    temperature=0.7,
)
results = model.generate(["What is 2+2?"], max_out_len=500)

Test plan

• 20 unit tests covering initialization, key rotation, temperature clamping, think tag handling, system prompt, retry logic
• 3 integration tests with real MiniMax API (M2.7, M2.5-highspeed, temperature)
• CI pipeline validation