# Project State & Progress

**Last Updated:** 2026-01-28
**Current Status:** Phase 4 complete with gap closure - all personality learning gaps fixed and verified

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## Current Position

| Aspect | Value |
|--------|-------|
| **Milestone** | v1.0 Core (Phases 1-5) |
| **Current Phase** | 04: Memory & Context Management |
| **Current Plan** | Complete (Phase 4 gap closure finished) |
| **Overall Progress** | 5/15 phases complete |
| **Progress Bar** | ███████░░░░ 30% |
| **Model Profile** | Budget (haiku priority) |

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## Key Decisions Made

### Architecture & Approach
- **Local-first design**: All inference, memory, and improvement happens locally — no cloud dependency
- **Second-agent review system**: Prevents broken self-modifications while allowing auto-improvement
- **Personality as code + learned layers**: Unshakeable core prevents misuse while allowing authentic growth
- **v1 scope**: Core systems only (model interface, safety, memory, conversation) before adding task automation

### Phase 1 Complete (Model Interface)
- **Model selection strategy**: Primary factor is available resources (CPU, RAM, GPU)
- **Context management**: Trigger compression at 70% of window, use hybrid approach (summarize old, keep recent)
- **Switching behavior**: Silent switching, no user notifications when changing models
- **Failure handling**: Auto-start LM Studio if needed, try next best model automatically
- **Discretion**: Claude determines capability tiers, compression algorithms, and degradation specifics
- **Implementation**: All three plans executed with comprehensive model switching, resource monitoring, and CLI interface

### Phase 3 Complete (Resource Management)
- **Proactive scaling strategy**: Scale at 80% resource usage for upgrades, 90% for immediate degradation
- **Hybrid monitoring**: Combined continuous background monitoring with pre-flight checks for comprehensive coverage
- **Graceful degradation**: Complete current tasks before switching models to maintain user experience
- **Stabilization periods**: 5-minute cooldowns prevent model switching thrashing during volatile conditions
- **Performance tracking**: Use actual response times and failure rates for data-driven scaling decisions
- **Implementation**: ProactiveScaler integrated into ModelManager with seamless scaling callbacks

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## Recent Work

- **2026-01-26**: Created comprehensive roadmap with 15 phases across v1.0, v1.1, v1.2
- **2026-01-27**: Gathered Phase 1 context and created detailed execution plan (01-01-PLAN.md)
- **2026-01-27**: Configured GSD workflow with MCP tools (Hugging Face, WebSearch)
- **2026-01-27**: **EXECUTED** Phase 1, Plan 1 - Created LM Studio connectivity and resource monitoring foundation
- **2026-01-27**: **EXECUTED** Phase 1, Plan 2 - Implemented conversation context management and memory system
- **2026-01-27**: **EXECUTED** Phase 1, Plan 3 - Integrated intelligent model switching and CLI interface
- **2026-01-27**: Phase 1 complete - all models interface and switching functionality implemented
- **2026-01-27**: Phase 2 has 4 plans ready for execution
- **2026-01-27**: **EXECUTED** Phase 2, Plan 01 - Created security assessment infrastructure with Bandit and Semgrep
- **2026-01-27**: **EXECUTED** Phase 2, Plan 02 - Implemented Docker sandbox execution environment with resource limits
- **2026-01-27**: **EXECUTED** Phase 2, Plan 03 - Created tamper-proof audit logging system with SHA-256 hash chains
- **2026-01-27**: **EXECUTED** Phase 2, Plan 04 - Implemented safety system integration and comprehensive testing
- **2026-01-27**: Phase 2 complete - sandbox execution environment with security assessment, audit logging, and resource management fully implemented
- **2026-01-27**: **EXECUTED** Phase 3, Plan 3 - Implemented proactive scaling system with hybrid monitoring and graceful degradation
- **2026-01-27**: **EXECUTED** Phase 3, Plan 4 - Implemented personality-driven resource communication with dere-tsun gremlin persona
- **2026-01-28**: **EXECUTED** Phase 4, Plan 7 - Enhanced SQLiteManager with metadata methods and integrated ContextAwareSearch with comprehensive topic analysis
- **2026-01-28**: **EXECUTED** Phase 4, Gap Closure Plan 1 - Fixed missing AdaptationRate import for PersonalityLearner initialization
- **2026-01-28**: **EXECUTED** Phase 4, Gap Closure Plan 2 - Implemented SQLiteManager methods (get_conversations_by_date_range, get_conversation_messages) for personality learning data pipeline

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## What's Next

Phase 4 complete: All memory and context management systems implemented with metadata integration.
Ready for Phase 5: CLI Interface and User Interaction.
Phase 4 accomplishments:
- SQLite database with full conversation and message storage ✓
- Vector embeddings with sqlite-vec integration ✓
- Semantic search with relevance scoring ✓
- Context-aware search with metadata-driven topic analysis ✓
- Timeline search with date-range filtering ✓
- Progressive compression with quality scoring ✓
- JSON archival system for long-term storage ✓
- Smart retention policies based on importance ✓
- Comprehensive metadata access for enhanced search ✓

Status: Phase 4 complete - 4/4 plans finished.

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## Blockers & Concerns

None — Phase 4 complete with all gaps closed. Memory and context management with progressive compression, JSON archival, smart retention, personality learning with pattern extraction and layer creation, and complete VectorStore implementation fully functional. All personality learning gaps fixed and verified.

**Phase 4 Final Status:** ✓ COMPLETE (16/16 must-haves verified, verification score 100%)

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## Configuration

**Model Profile**: budget (prioritize haiku for speed/cost)
**Workflow Toggles**:
- Research: enabled
- Plan checking: enabled
- Verification: enabled
- Auto-push: enabled

**MCP Integration**:
- Hugging Face Hub: enabled (model discovery, datasets, papers)
 - Web Research: enabled (current practices, architecture patterns)

## Session Continuity

Last session: 2026-01-28T18:29:27Z
Stopped at: Completed 04-06-PLAN.md
Resume file: None