feat: add MiniMax as first-class LLM provider#297
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octo-patch wants to merge 1 commit intoPySpur-Dev:mainfrom
Open
feat: add MiniMax as first-class LLM provider#297octo-patch wants to merge 1 commit intoPySpur-Dev:mainfrom
octo-patch wants to merge 1 commit intoPySpur-Dev:mainfrom
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Add MiniMax AI (M2.7, M2.5, M2.5-highspeed) as a built-in LLM provider, routed via OpenAI-compatible API through litellm. Changes: - Register MiniMax in LLMProvider enum and LLMModels with correct constraints (temperature 0-1, JSON output support, 8192 max tokens) - Add MiniMax routing in completion_with_backoff to use OpenAI-compatible handler with configurable MINIMAX_API_BASE - Exclude minimax/ prefix from Azure OpenAI fallback routing - Add MiniMax provider config in key_management for Settings UI - Add MiniMax icon mapping in frontend SettingsModal - Add MINIMAX_API_KEY to .env.example - Fix NoneType error in generate_text when litellm doesn't recognize provider by falling back to OpenAI params for OpenAI-compatible providers - Add 38 unit tests + 3 integration tests
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Summary
Changes
_model_info.pyMINIMAXtoLLMProviderenum, register 3 models inLLMModelswith correct constraints_utils.pyminimax/routing incompletion_with_backoff(OpenAI-compat with configurable base URL), exclude from Azure fallback, fix NoneType error for custom providers ingenerate_textkey_management.pyMINIMAX_API_KEY) for Settings UISettingsModal.tsx.env.exampleMINIMAX_API_KEYplaceholderREADME.mdConfiguration
Set
MINIMAX_API_KEYin the Settings UI or.envfile. Optionally setMINIMAX_API_BASEfor custom endpoints (defaults tohttps://api.minimax.io/v1).Test plan