Python: Add MiniMax AI connector for chat completion#13662
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octo-patch wants to merge 1 commit intomicrosoft:mainfrom
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Python: Add MiniMax AI connector for chat completion#13662octo-patch wants to merge 1 commit intomicrosoft:mainfrom
octo-patch wants to merge 1 commit intomicrosoft:mainfrom
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Add a new AI connector for MiniMax, a cloud-based LLM provider offering OpenAI-compatible API. This follows the same pattern as the existing NVIDIA connector, using the AsyncOpenAI client with a custom base URL. New connector includes: - MiniMaxChatCompletion service with streaming support - MiniMaxSettings for configuration via env vars (MINIMAX_API_KEY, etc.) - MiniMaxChatPromptExecutionSettings with MiniMax-specific constraints - Unit tests for settings, prompt execution settings, and chat completion - README with quick-start guide and available models Supported models: MiniMax-M2.5, MiniMax-M2.5-highspeed (204K context) API endpoint: https://api.minimax.io/v1
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Summary
Details
New files
python/semantic_kernel/connectors/ai/minimax/- Full connector implementationsettings/minimax_settings.py- Configuration via MINIMAX_API_KEY, MINIMAX_BASE_URL, MINIMAX_CHAT_MODEL_ID env varsprompt_execution_settings/minimax_prompt_execution_settings.py- MiniMax-specific settings (temperature constrained to (0.0, 1.0])services/minimax_chat_completion.py- Chat completion with streaming supportservices/minimax_handler.py- Base handler for API communicationREADME.md- Quick-start guideModified files
python/semantic_kernel/connectors/ai/README.md- Added MiniMax to connector tableTests
python/tests/unit/connectors/ai/minimax/- Unit tests for settings, prompt execution settings, and chat completion (16 tests, all passing)Supported Models
Motivation
MiniMax is a growing AI provider with OpenAI-compatible APIs. Adding this connector allows Semantic Kernel users to easily integrate MiniMax models into their applications.