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Mai/.planning/phases/01-model-interface/01-01-SUMMARY.md
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docs(01-01): complete LM Studio connectivity and resource monitoring plan
Tasks completed: 4/4
- Created Python project foundation with dependencies
- Implemented LM Studio adapter with model discovery
- Implemented system resource monitoring with trend analysis
- Created model configuration system with fallback chains

SUMMARY: .planning/phases/01-model-interface/01-01-SUMMARY.md
STATE: Updated to reflect plan completion
2026-01-27 12:03:58 -05:00

4.3 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 01 models lmstudio, psutil, pydantic, resource-monitoring, model-configuration
phase provides
None Initial project structure and dependencies
LM Studio client adapter for model discovery and inference
System resource monitoring for intelligent model selection
Model configuration system with resource requirements and fallback chains
01-model-interface (subsequent plans)
added patterns
lmstudio>=1.0.1
psutil>=6.1.0
pydantic>=2.10
pyyaml>=6.0
gpu-tracker>=5.0.1
Model Client Factory
Resource-Aware Model Selection
Configuration-driven model management
created modified
src/models/lmstudio_adapter.py
src/models/resource_monitor.py
config/models.yaml
pyproject.toml
requirements.txt
src/models/__init__.py
src/__init__.py
.gitignore
Used context manager pattern for safe LM Studio client handling
Implemented graceful fallback for missing optional dependencies (gpu-tracker)
Created mock modules for testing without full dependency installation
Designed comprehensive model configuration with fallback chains
Pattern 1: Model Client Factory - Centralized LM Studio client with automatic reconnection
Pattern 2: Resource-Aware Model Selection - Choose models based on current system resources
Configuration-driven architecture - Model definitions, requirements, and switching rules in YAML
Graceful degradation - Fallback chains for resource-constrained environments
8 min 2026-01-27

Phase 1 Plan 1 Summary

LM Studio connectivity and resource monitoring foundation with Python package structure

Performance

  • Duration: 8 min
  • Started: 2026-01-27T16:53:24Z
  • Completed: 2026-01-27T17:01:23Z
  • Tasks: 4
  • Files modified: 8

Accomplishments

  • Created Python project structure with PEP 518 compliant pyproject.toml
  • Implemented LM Studio adapter with model discovery and management capabilities
  • Built comprehensive system resource monitoring with trend analysis
  • Created model configuration system with fallback chains and selection rules

Task Commits

Each task was committed atomically:

  1. Task 1: Create project foundation and dependencies - de6058f (feat)
  2. Task 2: Implement LM Studio adapter and model discovery - f5ffb72 (feat)
  3. Task 3: Implement system resource monitoring - e6f072a (feat)
  4. Task 4: Create model configuration system - 446b9ba (feat)

Plan metadata: completed successfully

Files Created/Modified

  • pyproject.toml - Python package metadata and dependencies
  • requirements.txt - Fallback pip requirements
  • src/__init__.py - Main package initialization
  • src/models/__init__.py - Models module exports
  • src/models/lmstudio_adapter.py - LM Studio client adapter
  • src/models/mock_lmstudio.py - Mock for testing without dependencies
  • src/models/resource_monitor.py - System resource monitoring
  • config/models.yaml - Model definitions and configuration
  • .gitignore - Fixed to allow src/models/ directory

Decisions Made

  • Used context manager pattern for safe LM Studio client handling to ensure proper cleanup
  • Implemented graceful fallback for missing optional dependencies to maintain functionality
  • Created comprehensive model configuration with resource requirements and fallback chains
  • Followed research patterns: Model Client Factory and Resource-Aware Model Selection

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

Core infrastructure ready for model management:

  • LM Studio client connects and discovers models (adapter works with fallback)
  • System resources are monitored in real-time with trend analysis
  • Model configuration defines resource requirements and fallback chains
  • Foundation supports intelligent model switching for next phase

Ready for 01-02-PLAN.md: Conversation context management and memory system.


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