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docs(03-02): complete hardware tier detection plan

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

2026-01-27 18:35:41 -05:00

3.6 KiB

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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

03-resource-management

resource-management

yaml

hardware-detection

tier-classification

model-selection

phase	provides
03-01	enhanced ResourceMonitor with pynvml GPU support

Hardware tier detection and classification system

Configurable tier definitions via YAML

Model recommendation engine based on hardware capabilities

Performance characteristics mapping for each tier

03-03

03-04

model-interface

conversation-engine

added

patterns

yaml

pathlib

hardware-tiering

configuration-driven-hardware-detection

tier-based-model-selection

created

modified

src/resource/__init__.py

src/resource/tiers.py

src/config/resource_tiers.yaml

Three-tier system: low_end, mid_range, high_end provides clear hardware classification

YAML-driven configuration enables threshold adjustments without code changes

Integration with existing ResourceMonitor leverages enhanced GPU detection

Pattern: Configuration-driven hardware classification using YAML thresholds

Pattern: Tier-based model selection with fallback mechanisms

Pattern: Performance characteristic mapping per hardware tier

4min

2026-01-27

Phase 3: Hardware Tier Detection Summary

Hardware tier classification system with configurable YAML definitions and intelligent model mapping

Performance

Duration: 4 min
Started: 2026-01-27T23:29:04Z
Completed: 2026-01-27T23:32:51Z
Tasks: 3
Files modified: 3

Accomplishments

Created resource management module with proper exports and documentation
Implemented configurable hardware tier definitions with comprehensive thresholds
Built HardwareTierDetector class with intelligent classification logic
Established model recommendation system based on detected capabilities
Integrated with existing ResourceMonitor for real-time hardware monitoring

Task Commits

Each task was committed atomically:

Task 1: Create resource module structure - 5d93e97 (feat)
Task 2: Create configurable hardware tier definitions - 0b4c270 (feat)
Task 3: Implement HardwareTierDetector class - 8857ced (feat)

Plan metadata: (to be committed after summary)

Files Created/Modified

src/resource/__init__.py - Resource management module initialization with exports
src/config/resource_tiers.yaml - Comprehensive tier definitions with thresholds and performance characteristics
src/resource/tiers.py - HardwareTierDetector class implementing tier classification logic

Decisions Made

Three-tier classification system provides clear boundaries: low_end (1B-3B), mid_range (3B-7B), high_end (7B-70B)
YAML configuration enables runtime adjustment of thresholds without code changes
Integration with existing ResourceMonitor leverages enhanced GPU detection from Plan 01
Conservative fallback to low_end tier ensures stability on uncertain systems

Deviations from Plan

None - plan executed exactly as written.

Issues Encountered

None - all components implemented and verified successfully.

User Setup Required

None - no external service configuration required.

Next Phase Readiness

Hardware tier detection system complete and ready for integration with:

Proactive scaling system (Plan 03-03)
Resource personality communication (Plan 03-04)
Model interface selection system
Conversation engine optimization

Phase: 03-resource-management Completed: 2026-01-27

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