Add full MiniMax provider support across the entire stack:
Backend:
- Add MINIMAX to LiteLLMProvider enum in db.py
- Add MINIMAX mapping to all provider_map dicts in llm_service.py,
llm_router_service.py, and llm_config.py
- Add Alembic migration (rev 106) for PostgreSQL enum
- Add MiniMax M2.5 example in global_llm_config.example.yaml
Frontend:
- Add MiniMax to LLM_PROVIDERS enum with apiBase
- Add MiniMax-M2.5 and MiniMax-M2.5-highspeed to LLM_MODELS
- Add MINIMAX to Zod validation schema
- Add MiniMax SVG icon and wire up in provider-icons
Docs:
- Add MiniMax setup guide in chinese-llm-setup.md
MiniMax uses an OpenAI-compatible API (https://api.minimax.io/v1)
with models supporting up to 204K context window.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Increased maximum file upload limit from 10 to 50 to improve user experience.
- Implemented batch processing for document uploads to avoid proxy timeouts, splitting files into manageable chunks.
- Enhanced garbage collection in chat streaming functions to prevent memory leaks and improve performance.
- Added memory delta tracking in system snapshots for better monitoring of resource usage.
- Updated LLM router and service configurations to prevent unbounded internal accumulation and improve efficiency.
- Improved in-memory rate limiting by evicting timestamps outside the current window and cleaning up empty keys.
- Updated LLM router service to cache context profiles and avoid redundant computations.
- Introduced cache eviction logic for MCP tools and sandbox instances to manage memory usage effectively.
- Added garbage collection triggers in chat streaming functions to reclaim resources promptly.
-Introduce granular permissions for documents, chats, podcasts, and logs.
- Update routes to enforce permission checks for creating, reading, updating, and deleting resources. - Refactor user and search space interactions to align with RBAC model, removing ownership checks in favor of permission validation.
- Added new LLM providers including Google, Azure OpenAI, Bedrock, and others to the backend.
- Updated the model selection UI to dynamically display available models based on the selected provider.
- Enhanced the provider change handling to reset the model selection when the provider is changed.
- Improved the overall user experience by providing contextual information for model selection.
- Added `validate_llm_config` function to `llm_service.py` for validating LLM configurations via test API calls.
- Integrated validation in `create_llm_config` and `update_llm_config` routes in `llm_config_routes.py`, raising HTTP exceptions for invalid configurations.
- Enhanced error handling to provide detailed feedback on configuration issues.
- Add support for DeepSeek, Qwen (Alibaba), Kimi (Moonshot), and GLM (Zhipu)
- Implement auto-fill API Base URL when selecting Chinese LLM providers
- Add smart validation and warnings for missing API endpoints
- Fix session state management in task logging service
- Add comprehensive Chinese setup documentation
- Add database migration for new LLM provider enums
Closes#383
- RBAC soon??
- Updated various services and routes to handle search space-specific LLM preferences.
- Modified frontend components to pass search space ID for LLM configuration management.
- Removed onboarding page and settings page as part of the refactor.
- Updated import paths for LLM, connector, query, and streaming services to reflect their new location in the 'services' module.
- Removed obsolete utility service files that have been migrated.
2025-07-06 17:51:24 -07:00
Renamed from surfsense_backend/app/utils/llm_service.py (Browse further)
