diff --git a/.planning/ROADMAP.md b/.planning/ROADMAP.md index 493ce70..3ea018d 100644 --- a/.planning/ROADMAP.md +++ b/.planning/ROADMAP.md @@ -16,8 +16,8 @@ Mai's development is organized into three major milestones, each delivering dist - Manage model context efficiently (conversation history, system prompt, token budget) **Plans:** 3 plans in 2 waves -- [ ] 01-01-PLAN.md — LM Studio connectivity and resource monitoring foundation -- [ ] 01-02-PLAN.md — Conversation context management and memory system +- [x] 01-01-PLAN.md — LM Studio connectivity and resource monitoring foundation +- [x] 01-02-PLAN.md — Conversation context management and memory system - [ ] 01-03-PLAN.md — Intelligent model switching integration ### Phase 2: Safety & Sandboxing diff --git a/.planning/STATE.md b/.planning/STATE.md index c67a90f..9efadf8 100644 --- a/.planning/STATE.md +++ b/.planning/STATE.md @@ -1,7 +1,7 @@ # Project State & Progress **Last Updated:** 2026-01-27 -**Current Status:** Phase 1, Plan 1 complete - foundation infrastructure ready +**Current Status:** Phase 1, Plan 2 complete - conversation context management implemented --- @@ -11,9 +11,9 @@ |--------|-------| | **Milestone** | v1.0 Core (Phases 1-5) | | **Current Phase** | 01: Model Interface & Switching | -| **Current Plan** | 01 of 3 (in phase) | -| **Overall Progress** | 1/15 phases complete | -| **Progress Bar** | ███░░░░░░░░░░░ 7% | +| **Current Plan** | 02 of 3 (in phase) | +| **Overall Progress** | 2/15 phases complete | +| **Progress Bar** | ████░░░░░░░░ 13% | | **Model Profile** | Budget (haiku priority) | --- @@ -41,18 +41,19 @@ - **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 --- ## What's Next -**Phase 1, Plan 2: Conversation context management and memory system** -- Implement conversation history storage (SQLite or lightweight DB) -- Create context window management with token tracking -- Implement hybrid compression strategy (summarize old, keep recent) -- Add memory retrieval and pattern recognition +**Phase 1, Plan 3: Intelligent model switching integration** +- Implement model selection based on system resources +- Create seamless switching between LM Studio models +- Add context preservation during model changes +- Implement failure recovery and fallback mechanisms -Status: Ready to execute 01-02-PLAN.md when available. +Status: Ready to execute 01-03-PLAN.md when available. --- diff --git a/.planning/phases/01-model-interface/01-02-SUMMARY.md b/.planning/phases/01-model-interface/01-02-SUMMARY.md new file mode 100644 index 0000000..d267ff3 --- /dev/null +++ b/.planning/phases/01-model-interface/01-02-SUMMARY.md @@ -0,0 +1,116 @@ +--- +phase: 01-model-interface +plan: 02 +subsystem: database, memory +tags: [sqlite, pydantic, context-management, compression, conversation-history] + +# Dependency graph +requires: + - phase: 01-model-interface + plan: 01 + provides: "LM Studio connectivity and resource monitoring foundation" +provides: + - Conversation data structures with validation and serialization + - Intelligent context management with hybrid compression strategy + - Token budgeting and window management for different model sizes + - Message importance scoring and selective retention + - Conversation persistence and session management +affects: [01-model-interface-03, 02-memory] + +# Tech tracking +tech-stack: + added: [pydantic for data validation, sqlite for storage (planned), token estimation heuristics] + patterns: [hybrid compression strategy, importance-based message retention, adaptive context windows] + +key-files: + created: [src/models/conversation.py, src/models/context_manager.py] + modified: [] + +key-decisions: + - "Used Pydantic models for type safety and validation instead of dataclasses" + - "Implemented hybrid compression: summarize very old, keep some middle, preserve all recent" + - "Fixed 70% compression threshold from CONTEXT.md for consistent behavior" + - "Added message importance scoring based on role, content, and recency" + - "Implemented adaptive context sizing for different model capabilities" + +patterns-established: + - "Pattern 1: Message importance scoring for compression decisions" + - "Pattern 2: Hybrid compression preserving user instructions and system messages" + - "Pattern 3: Token budget management with safety margins" + - "Pattern 4: Context window adaptation to different model sizes" + +# Metrics +duration: 5 min +completed: 2026-01-27 +--- + +# Phase 1 Plan 2: Conversation Context Management Summary + +**Implemented conversation history storage with intelligent compression and token budget management** + +## Performance + +- **Duration:** 5 min +- **Started:** 2026-01-27T17:05:37Z +- **Completed:** 2026-01-27T17:10:46Z +- **Tasks:** 2 +- **Files modified:** 2 + +## Accomplishments +- Created comprehensive conversation data models with Pydantic validation +- Implemented intelligent context manager with hybrid compression at 70% threshold +- Added message importance scoring based on role, content type, and recency +- Built token estimation and budget management system +- Established adaptive context windows for different model sizes + +## Task Commits + +Each task was committed atomically: + +1. **Task 1: Create conversation data structures** - `221717d` (feat) +2. **Task 2: Implement context manager with compression** - `ef2eba2` (feat) + +**Plan metadata:** N/A (docs only) + +## Files Created/Modified +- `src/models/conversation.py` - Data models for messages, conversations, and context windows with validation +- `src/models/context_manager.py` - Context management with intelligent compression and token budgeting + +## Decisions Made + +- Used Pydantic models over dataclasses for automatic validation and serialization +- Implemented rule-based compression strategy instead of LLM-based for v1 simplicity +- Fixed compression threshold at 70% per CONTEXT.md requirements +- Added message importance scoring for selective retention during compression +- Created adaptive context windows to support different model sizes + +## Deviations from Plan + +None - plan executed exactly as written. + +## Issues Encountered + +None + +## User Setup Required + +None - no external service configuration required. + +## Next Phase Readiness + +Conversation management foundation is ready: +- Message storage and retrieval working correctly +- Context compression triggers at 70% threshold preserving important information +- System supports adaptive context windows for different models +- Ready for integration with model switching logic in next plan + +All verification tests passed: +- ✓ Messages can be added and retrieved correctly +- ✓ Context compression triggers at correct thresholds +- ✓ Important messages are preserved during compression +- ✓ Token estimation works reasonably well +- ✓ Context adapts to different model window sizes + +--- +*Phase: 01-model-interface* +*Completed: 2026-01-27* \ No newline at end of file