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Mai/.planning/phases/01-model-interface/01-03-SUMMARY.md
Mai Development b1a3b5e970
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docs(01-03): complete intelligent model switching integration
Tasks completed: 3/3
- ModelManager with intelligent selection and switching
- Core Mai orchestration class
- CLI interface for testing and monitoring

SUMMARY: .planning/phases/01-model-interface/01-03-SUMMARY.md

Phase 1 complete - model interface foundation ready for Phase 2: Safety & Sandboxing
2026-01-27 12:38:43 -05:00

5.4 KiB

phase, plan, subsystem, tags, requires, provides, affects, tech-stack, key-files, key-decisions, patterns-established, duration, completed
phase plan subsystem tags requires provides affects tech-stack key-files key-decisions patterns-established duration completed
01-model-interface 03 models, orchestration, cli
intelligent-switching
model-manager
resource-monitoring
context-preservation
argparse
phase plan provides
01-model-interface 01 LM Studio connectivity and resource monitoring foundation
phase plan provides
01-model-interface 02 Conversation context management and memory system
Intelligent model selection and switching logic based on resources and context
Core Mai orchestration class coordinating all subsystems
CLI entry point for testing model switching and monitoring
Integrated system with seamless conversation processing
02-safety
03-resource-management
05-conversation-engine
added patterns
argparse for CLI
asyncio for async operations
yaml for configuration
Model selection algorithms
silent switching
fallback chains
orchestration pattern
created modified
src/models/model_manager.py
src/mai.py
src/__main__.py
Used async/await patterns for model switching to prevent blocking
Implemented silent switching per CONTEXT.md - no user notifications
Created comprehensive fallback chains for model failures
Designed ModelManager as central coordinator for all model operations
Built CLI with argparse following standard Python patterns
Added resource-aware model selection with scoring system
Implemented graceful degradation when no models fit constraints
Pattern 1: Intelligent Model Selection - Score-based selection considering resources, capabilities, and recent failures
Pattern 2: Silent Model Switching - Seamless transitions without user notification
Pattern 3: Fallback Chains - Automatic switching to smaller models on failure
Pattern 4: Orchestration Pattern - Mai class delegates to specialized subsystems
Pattern 5: CLI Command Pattern - Subparser-based command structure with help
16 min 2026-01-27

Phase 1 Plan 3: Intelligent Model Switching Integration Summary

Integrated all components into intelligent model switching system with silent transitions and CLI interface

Performance

  • Duration: 16 min
  • Started: 2026-01-27T17:18:35Z
  • Completed: 2026-01-27T17:34:30Z
  • Tasks: 3
  • Files modified: 3

Accomplishments

  • Created comprehensive ModelManager class with intelligent resource-based model selection
  • Implemented silent model switching with fallback chains and failure recovery
  • Built core Mai orchestration class coordinating all subsystems
  • Created full-featured CLI interface with chat, status, models, and switch commands
  • Integrated context preservation during model switches
  • Added automatic retry and graceful degradation capabilities

Task Commits

Each task was committed atomically:

  1. Task 1: Implement ModelManager with intelligent switching - 0b7b527 (feat)
  2. Task 2: Create core Mai orchestration class - 24ae542 (feat)
  3. Task 3: Create CLI entry point for testing - 5297df8 (feat)

Plan metadata: 89b0c8d (docs: complete plan)

Files Created/Modified

  • src/models/model_manager.py - Intelligent model selection and switching system with resource awareness, fallback chains, and silent transitions
  • src/mai.py - Core orchestration class coordinating ModelManager, ContextManager, and subsystems with async support
  • src/__main__.py - CLI entry point with argparse providing chat, status, models listing, and model switching commands

Decisions Made

  • Used async/await patterns for model switching to prevent blocking operations
  • Implemented silent switching per CONTEXT.md requirements - no user notifications for model changes
  • Created comprehensive fallback chains from large to medium to small models
  • Designed ModelManager as central coordinator for all model operations and state
  • Built CLI with standard argparse patterns including subcommands and help
  • Added resource-aware model selection with scoring system considering capabilities and recent failures
  • Implemented graceful degradation when system resources cannot accommodate any model

Deviations from Plan

None - plan executed exactly as written.

Issues Encountered

None - all verification tests passed successfully.

User Setup Required

None - no external service configuration required.

Next Phase Readiness

Model interface foundation is complete and ready:

  • ModelManager can intelligently select models based on system resources and conversation context
  • Silent model switching works seamlessly with proper context preservation
  • Fallback chains provide graceful degradation when primary models fail
  • Mai orchestration class coordinates all subsystems effectively
  • CLI interface provides comprehensive testing and monitoring capabilities
  • System handles errors gracefully with automatic retry and resource cleanup

All verification tests passed:

  • ✓ ModelManager can select appropriate models based on resources
  • ✓ Conversation processing works with automatic model switching
  • ✓ CLI interface allows testing chat and system monitoring
  • ✓ Context is preserved during model switches
  • ✓ System gracefully handles model loading failures
  • ✓ Resource monitoring triggers appropriate model changes

Foundation ready for integration with safety and memory systems in Phase 2.


Phase: 01-model-interface Completed: 2026-01-27