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Add MiniMax provider with M3 as default model#136

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Add MiniMax provider with M3 as default model#136
octo-patch wants to merge 2 commits into
BeastByteAI:mainfrom
octo-patch:feature/add-minimax-provider

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@octo-patch octo-patch commented Mar 22, 2026

Summary

Add MiniMax AI as a new LLM provider alongside OpenAI, Anthropic, and Vertex AI. MiniMax offers an OpenAI-compatible API. This PR ships MiniMax-M3 as the default model and keeps MiniMax-M2.7 / MiniMax-M2.7-highspeed as alternatives.

Available models

Model Notes
MiniMax-M3 512K context, up to 128K output, image input support (default)
MiniMax-M2.7 Previous-generation model
MiniMax-M2.7-highspeed Previous-generation low-latency variant

Changes

  • LLM layer (skllm/llm/minimax/): credentials, completion (with temperature clamping to [0,1] and think-tag stripping), and mixin modules following the existing Anthropic/GPT pattern
  • Model layer (skllm/models/minimax/): zero-shot / few-shot / CoT classifiers, multi-label classifiers, dynamic few-shot classifiers, summarizer, translator, and NER — all default to MiniMax-M3
  • Config (skllm/config.py): SKLLMConfig.set_minimax_key() / get_minimax_key() for API key management
  • Model constants (skllm/model_constants.py): MINIMAX_MODEL = "MiniMax-M3"
  • README (README.md): Quick-start example uses MiniMax-M3; available-models list is MiniMax-M3, MiniMax-M2.7, MiniMax-M2.7-highspeed

Why

MiniMax-M3 is the latest MiniMax model — 512K context window, up to 128K output, and image-input support. Older entries (MiniMax-M2.5 / MiniMax-M2.5-highspeed) were dropped from the public surface in favor of M3 as default and the still-supported M2.7 line as alternatives.

Test plan

  • Unit tests cover mixins, completion, credentials, config, model constants, and all model class constructors (defaults assert MiniMax-M3)
  • Integration tests verify live API calls using MiniMax-M2.7-highspeed
  • Existing GPT, Anthropic, and utility tests pass without regressions

Add MiniMax AI as a new LLM provider alongside OpenAI, Anthropic, and
Vertex AI. MiniMax offers OpenAI-compatible API with models like
MiniMax-M2.7 and MiniMax-M2.5-highspeed (204K context).

New files:
- skllm/llm/minimax/ - credentials, completion, and mixin modules
- skllm/models/minimax/ - classification (zero-shot, few-shot, CoT),
  text2text (summarization, translation), and tagging (NER)
- tests/llm/minimax/ - 27 unit tests and 6 integration tests

Modified files:
- skllm/config.py - add set_minimax_key()/get_minimax_key()
- skllm/model_constants.py - add MINIMAX_MODEL constant
- README.md - add MiniMax usage example
- Add MiniMax-M3 as the new default model in MINIMAX_MODEL constant
- Keep MiniMax-M2.7 and MiniMax-M2.7-highspeed as alternatives
- Remove older models (M2.5 and M2.5-highspeed) from documentation
- Update default-model docstrings across classifier, summarizer, translator, NER
- Update unit-test assertions for default model
- Update integration tests to use the still-available MiniMax-M2.7-highspeed
@octo-patch octo-patch changed the title Add MiniMax as a first-class LLM provider Add MiniMax provider with M3 as default model Jun 7, 2026
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