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- Updated embedding_manager.py to include backend parameter in model configuration. - Modified model_manager.py to utilize cache_name for ONNX models. - Refactored hybrid_search.py to improve embedder initialization based on backend type. - Added backend column to vector_store.py for better model configuration management. - Implemented migration for existing database to include backend information. - Enhanced API settings implementation with comprehensive provider and endpoint management. - Introduced LiteLLM integration guide detailing configuration and usage. - Added examples for LiteLLM usage in TypeScript.
1.4 KiB
1.4 KiB
Code Quality Standards
Code Quality
- Follow project's existing patterns
- Match import style and naming conventions
- Single responsibility per function/class
- DRY (Don't Repeat Yourself)
- YAGNI (You Aren't Gonna Need It)
Testing
- Test all public functions
- Test edge cases and error conditions
- Mock external dependencies
- Target 80%+ coverage
Error Handling
- Proper try-catch blocks
- Clear error messages
- Graceful degradation
- Don't expose sensitive info
Core Principles
Incremental Progress:
- Small, testable changes
- Commit working code frequently
- Build on previous work (subtasks)
Evidence-Based:
- Study 3+ similar patterns before implementing
- Match project style exactly
- Verify with existing code
Pragmatic:
- Boring solutions over clever code
- Simple over complex
- Adapt to project reality
Context Continuity (Multi-Task):
- Leverage resume for consistency
- Maintain established patterns
- Test integration between subtasks
Execution Checklist
Before:
- Understand PURPOSE and TASK clearly
- Review CONTEXT files, find 3+ patterns
- Check RULES templates and constraints
During:
- Follow existing patterns exactly
- Write tests alongside code
- Run tests after every change
- Commit working code incrementally
After:
- All tests pass
- Coverage meets target
- Build succeeds
- All EXPECTED deliverables met