Add MiniMax as LLM provider for web agent evaluation

[octo-patch]

Summary

• Add MiniMax (M2.7 / M2.5 / M2.5-highspeed) as a third LLM provider alongside OpenAI and HuggingFace
• Uses the OpenAI-compatible Chat Completions API via direct HTTP requests (avoids interfering with the existing openai==0.27.0 global state)
• Includes temperature clamping, think tag stripping, async batch support, and retry with exponential backoff
• 28 unit tests + 3 integration tests covering config, dispatch, tokenizer, prompt construction, and API calls

Changes

File	Description
llms/providers/minimax_utils.py	New MiniMax provider module (sync + async generation)
llms/lm_config.py	Add minimax branch in construct_llm_config()
llms/utils.py	Add minimax dispatch in call_llm()
llms/tokenizers.py	Add minimax tokenizer (cl100k_base encoding)
llms/init.py	Export generate_from_minimax_chat_completion
agent/prompts/prompt_constructor.py	Support minimax in prompt formatting (same chat format as OpenAI)
README.md	Add MiniMax usage examples and supported providers table
tests/test_minimax_provider.py	28 unit tests
tests/test_minimax_integration.py	3 integration tests (require MINIMAX_API_KEY)

Usage

export MINIMAX_API_KEY=your_key
python run.py --provider minimax --model MiniMax-M2.7 --mode chat --temperature 0.8 --result_dir results_minimax

Test plan

• All 28 unit tests pass (pytest tests/test_minimax_provider.py)
• All 3 integration tests pass against real MiniMax API
• Existing OpenAI/HuggingFace providers unaffected (no changes to their code paths)
• End-to-end evaluation with MiniMax on WebArena tasks