feat: add MiniMax as LLM provider

[octo-patch]

Summary

• Add MiniMax AI as a first-class LLM provider (MiniMax-M2.7, MiniMax-M2.7-highspeed) via OpenAI-compatible API at api.minimax.io/v1
• Add MINIMAX elif branch in get_llm() factory using ChatOpenAI with custom base_url
• Add MiniMax model config examples in backend/example.env and default model entries in frontend/src/utils/Constants.ts
• Update README to list MiniMax as a supported LLM

Changes

File	Change
backend/src/llm.py	Add MINIMAX elif branch in get_llm() factory
backend/example.env	Add MiniMax M2.7 / M2.7-highspeed config examples
frontend/src/utils/Constants.ts	Add MiniMax models to default LLM list
README.md	Add MiniMax to supported LLMs list
backend/tests/test_minimax_provider.py	21 unit tests for routing, config, params
backend/tests/test_minimax_integration.py	3 integration tests (API connectivity)

Configuration

# backend/.env
LLM_MODEL_CONFIG_minimax_m2.7="MiniMax-M2.7,your_minimax_api_key"
LLM_MODEL_CONFIG_minimax_m2.7_highspeed="MiniMax-M2.7-highspeed,your_minimax_api_key"

Test plan

• 21 unit tests pass (model routing, env config, source code validation)
• 3 integration tests pass (M2.7 chat, M2.7-highspeed chat, structured output support)
• Manual verification: add MiniMax config to .env, select model in frontend, run graph extraction