feat: add MiniMax as LLM provider with M2.7 default#1568
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octo-patch wants to merge 2 commits intomicrosoft:mainfrom
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feat: add MiniMax as LLM provider with M2.7 default#1568octo-patch wants to merge 2 commits intomicrosoft:mainfrom
octo-patch wants to merge 2 commits intomicrosoft:mainfrom
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Add MiniMax (MiniMax-M2.5, MiniMax-M2.5-highspeed) as a new LLM provider option alongside OpenAI and Azure OpenAI. MiniMax offers an OpenAI-compatible API with up to 204K context length. Changes: - Add MiniMax provider detection and API endpoint construction in awesome_chat.py with priority: local > azure > minimax > openai - Handle MiniMax temperature constraint (must be > 0) by adjusting zero values to 0.01 - Add MiniMax model encodings and context lengths in get_token_ids.py - Create config.minimax.yaml template for MiniMax configuration - Update README.md with MiniMax setup instructions
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@microsoft-github-policy-service agree |
- Add MiniMax-M2.7 and MiniMax-M2.7-highspeed to model list - Set MiniMax-M2.7 as default model in config and docs - Keep all previous models (M2.5, M2.5-highspeed) as alternatives - Update token encodings and max context length for new models
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Summary
Add MiniMax as a new LLM provider for JARVIS/HuggingGPT, alongside the existing OpenAI and Azure OpenAI options. MiniMax provides an OpenAI-compatible chat completions API with models offering up to 204K context length.
Changes
awesome_chat.py): Added MiniMax to the provider priority chain (local > azure > minimax > openai) with proper API endpoint construction, key resolution (config file orMINIMAX_API_KEYenv var), and temperature clampingget_token_ids.py): Registered MiniMax-M2.7, MiniMax-M2.7-highspeed, MiniMax-M2.5, and MiniMax-M2.5-highspeed with cl100k_base encoding and 204K context windowconfig.minimax.yaml): Pre-configured YAML with MiniMax-M2.7 as default modelREADME.md): Added MiniMax as a supported LLM provider with setup instructionsDefault Model
MiniMax-M2.7 — Latest flagship model with enhanced reasoning and coding capabilities.
Testing