feat: upgrade MiniMax default model to M3#438
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MiniMax offers OpenAI-compatible API with models like MiniMax-M2.5 and MiniMax-M2.5-highspeed (204K context window). This commit adds: - MiniMax provider section in README (setup guide, cost estimation) - Example config file (configs/minimax_config.yaml) - Updated test env to support MiniMax API key validation Co-Authored-By: octo-patch <octo-patch@users.noreply.github.com>
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- Update MiniMax-M2.7 and MiniMax-M2.7-highspeed as default models - Update config, README, and docs references - Keep all previous models as alternatives
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- Add MiniMax-M3 to model list and set as default - Keep MiniMax-M2.7 and MiniMax-M2.7-highspeed as alternatives - Update README and configs/README.md with M3 references Co-Authored-By: Octopus <liyuan851277048@icloud.com>
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Summary
Upgrade MiniMax model configuration to use M3 as the default model, with M2.7 and M2.7-highspeed retained as alternatives.
Changes
configs/minimax_config.yamlmodel list and header commentREADME.mdprovider section, cost estimation, and config exampleconfigs/README.mddescription for the MiniMax configWhy
MiniMax-M3 is the latest MiniMax flagship model, with a 512K context window, up to 128K output, and image input support, making it a strong fit for code evolution tasks.
Testing
tests/test_valid_configs.pypasses (config loads with the new model list)load_config("configs/minimax_config.yaml")returns models[MiniMax-M3, MiniMax-M2.7, MiniMax-M2.7-highspeed]