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Tasks completed: 3/3 - Resource module structure with proper exports - Configurable hardware tier definitions in YAML - HardwareTierDetector class with classification logic SUMMARY: .planning/phases/03-resource-management/03-02-SUMMARY.md
107 lines
3.6 KiB
Markdown
107 lines
3.6 KiB
Markdown
---
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phase: 03-resource-management
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plan: 02
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subsystem: resource-management
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tags: [yaml, hardware-detection, tier-classification, model-selection]
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# Dependency graph
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requires:
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- phase: 03-01
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provides: enhanced ResourceMonitor with pynvml GPU support
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provides:
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- Hardware tier detection and classification system
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- Configurable tier definitions via YAML
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- Model recommendation engine based on hardware capabilities
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- Performance characteristics mapping for each tier
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affects: [03-03, 03-04, model-interface, conversation-engine]
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# Tech tracking
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tech-stack:
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added: [yaml, pathlib, hardware-tiering]
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patterns: [configuration-driven-hardware-detection, tier-based-model-selection]
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key-files:
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created: [src/resource/__init__.py, src/resource/tiers.py, src/config/resource_tiers.yaml]
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modified: []
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key-decisions:
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- "Three-tier system: low_end, mid_range, high_end provides clear hardware classification"
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- "YAML-driven configuration enables threshold adjustments without code changes"
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- "Integration with existing ResourceMonitor leverages enhanced GPU detection"
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patterns-established:
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- "Pattern: Configuration-driven hardware classification using YAML thresholds"
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- "Pattern: Tier-based model selection with fallback mechanisms"
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- "Pattern: Performance characteristic mapping per hardware tier"
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# Metrics
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duration: 4min
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completed: 2026-01-27
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---
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# Phase 3: Hardware Tier Detection Summary
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**Hardware tier classification system with configurable YAML definitions and intelligent model mapping**
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## Performance
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- **Duration:** 4 min
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- **Started:** 2026-01-27T23:29:04Z
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- **Completed:** 2026-01-27T23:32:51Z
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- **Tasks:** 3
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- **Files modified:** 3
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## Accomplishments
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- Created resource management module with proper exports and documentation
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- Implemented configurable hardware tier definitions with comprehensive thresholds
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- Built HardwareTierDetector class with intelligent classification logic
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- Established model recommendation system based on detected capabilities
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- Integrated with existing ResourceMonitor for real-time hardware monitoring
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## Task Commits
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Each task was committed atomically:
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1. **Task 1: Create resource module structure** - `5d93e97` (feat)
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2. **Task 2: Create configurable hardware tier definitions** - `0b4c270` (feat)
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3. **Task 3: Implement HardwareTierDetector class** - `8857ced` (feat)
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**Plan metadata:** (to be committed after summary)
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## Files Created/Modified
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- `src/resource/__init__.py` - Resource management module initialization with exports
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- `src/config/resource_tiers.yaml` - Comprehensive tier definitions with thresholds and performance characteristics
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- `src/resource/tiers.py` - HardwareTierDetector class implementing tier classification logic
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## Decisions Made
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- Three-tier classification system provides clear boundaries: low_end (1B-3B), mid_range (3B-7B), high_end (7B-70B)
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- YAML configuration enables runtime adjustment of thresholds without code changes
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- Integration with existing ResourceMonitor leverages enhanced GPU detection from Plan 01
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- Conservative fallback to low_end tier ensures stability on uncertain systems
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## Deviations from Plan
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None - plan executed exactly as written.
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## Issues Encountered
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None - all components implemented and verified successfully.
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## User Setup Required
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None - no external service configuration required.
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## Next Phase Readiness
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Hardware tier detection system complete and ready for integration with:
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- Proactive scaling system (Plan 03-03)
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- Resource personality communication (Plan 03-04)
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- Model interface selection system
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- Conversation engine optimization
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---
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*Phase: 03-resource-management*
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*Completed: 2026-01-27* |