feat: add MiniMax as inference provider with M2.7 as default#272
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octo-patch wants to merge 3 commits intoConway-Research:mainfrom
Open
feat: add MiniMax as inference provider with M2.7 as default#272octo-patch wants to merge 3 commits intoConway-Research:mainfrom
octo-patch wants to merge 3 commits intoConway-Research:mainfrom
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Add MiniMax (api.minimax.io) as a first-class inference provider alongside
OpenAI, Anthropic, and others. Both MiniMax-M2.5 (reasoning tier) and
MiniMax-M2.5-highspeed (fast tier) are now available for model selection.
Changes:
- Add "minimax" to ModelProvider type and minimaxApiKey to config
- Register MiniMax models in provider-registry defaults (enabled)
- Add MiniMax backend routing in inference client with proper
temperature clamping (MiniMax rejects temperature=0)
- Seed MiniMax models in STATIC_MODEL_BASELINE with correct
parameterStyle ("max_tokens")
- Wire MINIMAX_API_KEY through setup wizard, configure menu,
agent loop env export, and CLI entrypoint
- Add provider-registry tests for MiniMax provider
Co-Authored-By: Claude Opus 4.6 <[email protected]>
The STATIC_MODEL_BASELINE now includes MiniMax models, so the valid provider list must include "minimax".
- Add MiniMax-M2.7 and MiniMax-M2.7-highspeed to model list - Set MiniMax-M2.7 as default model - Keep all previous models (M2.5, M2.5-highspeed) as alternatives - Update related unit tests
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Summary
Adds MiniMax as a first-class inference provider across the automaton's inference stack, with MiniMax-M2.7 as the default model.
Changes
DEFAULT_PROVIDERSwith OpenAI-compatiblehttps://api.minimax.io/v1endpoint, four model entries (M2.7 reasoning, M2.7-highspeed fast, M2.5 reasoning, M2.5-highspeed fast)STATIC_MODEL_BASELINEwith tier/cost metadata, plus M2.5 variants as alternativesmax_tokensparameter styleminimaxApiKeythreaded through config, setup wizard, and CLI promptsWhy
MiniMax-M2.7 is the latest flagship model with enhanced reasoning and coding capabilities. The OpenAI-compatible API makes integration straightforward.
Testing