---
phase: 01-model-interface
plan: 03
subsystem: models, orchestration, cli
tags: [intelligent-switching, model-manager, resource-monitoring, context-preservation, argparse]

# Dependency graph
requires:
  - phase: 01-model-interface
    plan: 01
    provides: "LM Studio connectivity and resource monitoring foundation"
  - phase: 01-model-interface
    plan: 02
    provides: "Conversation context management and memory system"
provides:
  - 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
affects: [02-safety, 03-resource-management, 05-conversation-engine]

# Tech tracking
tech-stack:
  added: [argparse for CLI, asyncio for async operations, yaml for configuration]
  patterns: [Model selection algorithms, silent switching, fallback chains, orchestration pattern]

key-files:
  created: [src/models/model_manager.py, src/mai.py, src/__main__.py]
  modified: []

key-decisions:
  - "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"

patterns-established:
  - "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"

# Metrics
duration: 16 min
completed: 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*