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feat: add MiniMax as a first-class LLM provider (M3 default)#88

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octo-patch wants to merge 2 commits into
ricklamers:mainfrom
octo-patch:feature/add-minimax-provider
Open

feat: add MiniMax as a first-class LLM provider (M3 default)#88
octo-patch wants to merge 2 commits into
ricklamers: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 third LLM provider alongside OpenAI and Azure OpenAI. MiniMax models (M3, M2.7, M2.7-highspeed) are supported via the OpenAI-compatible API, integrating cleanly with the existing openai library.

Changes

  • Provider detection: OPENAI_API_TYPE=minimax or auto-detection when MINIMAX_API_KEY is set without OPENAI_API_KEY
  • API routing: MiniMax endpoint (https://api.minimax.io/v1) configured as the default base URL; uses standard model parameter
  • Temperature clamping: Ensures temperature stays within MiniMax's supported range (0, 1]
  • Default models: MiniMax-M3 (default), MiniMax-M2.7, and MiniMax-M2.7-highspeed, customizable via MINIMAX_MODELS env var
  • Config template: .env.minimax-example with all MiniMax configuration options
  • Documentation: README section with setup instructions
  • Tests: Unit tests + integration tests covering provider detection, model routing, API configuration, temperature clamping, and the M3 default

About MiniMax-M3

MiniMax-M3 is the latest MiniMax model: 512K context window, up to 128K output, and image input support. It is now the default; MiniMax-M2.7 and MiniMax-M2.7-highspeed remain available for users who want to pin to the previous generation.

Files Changed

File Description
gpt_code_ui/webapp/main.py MiniMax provider detection, API config, model routing, temp clamping, M3 default
.env.minimax-example MiniMax configuration template (M3 first in MINIMAX_MODELS example)
README.md MiniMax setup documentation (mentions M3 default)
tests/__init__.py Test package init
tests/test_minimax_provider.py Unit tests (now asserts M3 is in defaults and first)
tests/test_minimax_integration.py Integration tests (requires MINIMAX_API_KEY); covers M3, M2.7, M2.7-highspeed

Test Plan

  • All unit tests pass (python -m unittest tests.test_minimax_provider)
  • Integration tests cover M3 as the default
  • Existing OpenAI and Azure provider paths unchanged
  • Manual test: set OPENAI_API_TYPE=minimax and run gptcode; verify M3 is the default model in the UI

PR Bot and others added 2 commits March 22, 2026 18:46
Add MiniMax AI (M2.7, M2.7-highspeed) as a third provider option
alongside OpenAI and Azure OpenAI. MiniMax uses an OpenAI-compatible
API, so it integrates cleanly with the existing openai library.

Changes:
- Provider detection via OPENAI_API_TYPE=minimax or auto-detection
  when MINIMAX_API_KEY is set without OPENAI_API_KEY
- Temperature clamping to MiniMax's (0, 1] range
- Default model list: MiniMax-M2.7 and MiniMax-M2.7-highspeed
- .env.minimax-example configuration template
- README section with MiniMax setup instructions
- 14 unit tests + 3 integration tests
- Add MiniMax-M3 to model list and set as default (first entry)
- Keep MiniMax-M2.7 and MiniMax-M2.7-highspeed as alternatives
- Update README to describe M3 (512K context, 128K output, image input)
- Update tests to cover M3 in defaults and integration
@octo-patch octo-patch changed the title feat: add MiniMax as a first-class LLM provider feat: add MiniMax as a first-class LLM provider (M3 default) Jun 7, 2026
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