170 lines
6.2 KiB
Markdown
170 lines
6.2 KiB
Markdown
# Checkpoint 1: Repository Inventory Report
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## Current State Analysis - Trax Project
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### 1. Project Structure
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The Trax project is currently a **minimal skeleton** with uv package management properly configured.
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#### What Exists ✅
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- **uv Configuration**: Proper `pyproject.toml` with uv tooling
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- **Documentation**: Basic `CLAUDE.md` (97 lines) and `AGENTS.md` (163 lines) - both well under 600 LOC limit
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- **Config System**: Centralized configuration inheriting from root `.env`
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- **Testing Setup**: pytest with coverage configured
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- **Code Quality**: Black, Ruff, MyPy configured with strict settings
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- **Python 3.11+**: Modern Python with type checking
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- **Virtual Environment**: `.venv` directory configured
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#### What's Missing ❌
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- No actual media processing code yet
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- No transcript services implemented
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- No caching layer
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- No database/models
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- No API endpoints
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- No export functionality
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- No batch processing system
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### 2. Key Components to Migrate from YouTube Summarizer
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Based on analysis and priorities, here are the critical components to bring over:
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#### 🔥 Priority 1: Caching Architecture
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**90% cost reduction achieved in YouTube Summarizer**
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- **Multi-layer caching system**:
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- EmbeddingCacheService (24h TTL, LZ4 compression)
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- MultiAgentCacheService (7d TTL, $0.015/analysis saved)
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- RAGQueryCacheService (6h TTL, 2+ second savings)
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- PromptComplexityCacheService (30d TTL, 95% accuracy)
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- **UnifiedCacheOrchestrator** for cross-cache optimization
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- **SQLite-based** with connection pooling
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- **Smart cache warming** and resource allocation
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#### 🎯 Priority 2: Transcription Service
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**20-70x faster transcription achieved**
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- **FasterWhisperTranscriptService** with M3 optimizations
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- distil-large-v3 model (best speed/accuracy tradeoff)
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- Smart chunking for large files (10-minute segments)
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- Audio preprocessing (16kHz mono conversion)
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- VAD (Voice Activity Detection) optimization
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- **Enhanced transcript storage** with compression (68.6% space savings)
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- **YouTube integration** with fallback strategies
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- **Batch processing** support
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#### 📦 Priority 3: Export & Formatting
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**Critical for data persistence**
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- **Multi-format export** (SRT, VTT, TXT, JSON, PDF)
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- **Template-driven formatting** with Jinja2
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- **Batch export system** for multiple files
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- **Professional formatting** with metadata
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- **Safe filename generation** with collision avoidance
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#### ⚡ Priority 4: Performance Optimizations
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**Essential patterns that worked**
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- **Database Registry Pattern** (prevents SQLAlchemy conflicts)
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- **Async pipeline patterns** throughout
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- **Connection pooling** for database and external services
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- **Smart compression** (68.6% space savings for transcripts)
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- **Protocol-based design** for component swapping
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### 3. Technical Debt & Failed Patterns to Avoid
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#### ❌ Patterns That Failed
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- **React Frontend Complexity**: Eventually decommissioned in favor of headless API
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- **Simultaneous Frontend/Backend Development**: Caused integration issues
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- **Over-engineering**: Features without clear value added complexity
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- **Documentation Bloat**: Grew beyond 600 LOC limits causing context issues
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- **Mock-heavy Testing**: Unrealistic test scenarios
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- **Streaming Transcription**: Unreliable, download-first approach won
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#### ✅ Patterns That Worked
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- **Backend-first development**: Get data layer right before UI
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- **Database modification checklist**: Prevented breaking changes
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- **Test runner system**: 229 tests with 0.2s discovery time
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- **Registry pattern for SQLAlchemy**: Solved relationship conflicts
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- **Multi-layer caching**: Massive cost and performance benefits
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- **Real test files**: Caught actual edge cases
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- **Protocol-based services**: Easy refactoring and swapping
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### 4. Migration Risk Assessment
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#### Low Risk Components ✅
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- **Config system**: Already compatible with uv and inheritance model
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- **Caching services**: Self-contained, easy to port
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- **Export functionality**: Modular design, simple migration
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- **Testing patterns**: Can adopt test runner system directly
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#### Medium Risk Components ⚠️
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- **Transcription service**: Needs audio dependencies (FFmpeg, etc.)
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- **Database patterns**: Requires Alembic setup and careful migration
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- **Batch processing**: Needs queue design from scratch
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#### High Risk Components ❌
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- None identified - starting fresh avoids legacy issues
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### 5. Configuration Analysis
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Current `src/config.py` provides:
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- Centralized configuration with root `.env` inheritance
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- API key management for multiple AI services
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- Path management for project directories
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- Validation methods for required keys
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- Service availability detection
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**Ready for Extension** with:
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- Database configuration
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- Media processing settings
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- Transcription parameters
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- Caching configuration
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- Export paths
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### 6. Development Environment Status
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| Component | Status | Action Needed |
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|-----------|--------|--------------|
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| Python 3.11+ | ✅ Ready | None |
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| uv package manager | ✅ Configured | Install dependencies |
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| PostgreSQL | ❌ Not setup | Install and configure |
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| FFmpeg | ❌ Not verified | Install for audio processing |
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| Test infrastructure | ⚠️ Basic | Add real test files |
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| CI/CD | ❌ None | Setup GitHub Actions |
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### 7. Immediate Requirements
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To begin development, we need:
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1. **Dependencies Installation**:
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- Core: `sqlalchemy`, `alembic`, `psycopg2-binary`
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- Transcription: `faster-whisper`, `yt-dlp`, `ffmpeg-python`
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- AI: `openai` (for DeepSeek), `aiohttp`
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- Testing: Real audio/video test files
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2. **Directory Structure**:
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- `src/services/` for business logic
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- `src/models/` for database models
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- `src/agents/rules/` for consistency rules
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- `tests/fixtures/` for real test files
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3. **Database Setup**:
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- PostgreSQL installation
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- Initial schema design
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- Alembic configuration
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### Summary
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**Current State**: Trax is a clean skeleton with proper uv configuration, ready for development.
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**Migration Path**: Clear path exists for migrating priority components from YouTube Summarizer.
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**No Blocking Issues**: No significant technical debt or conflicts identified.
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**Ready to Proceed**: With systematic development following the established patterns.
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---
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*Generated: 2024*
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*Status: COMPLETE*
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*Next: Historical Context Report* |