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Fase 1: Populate BPM in sample_metadata.db (283/511 samples from filenames) Fase 2: DB-aware sample selection (_pick_best_db) with BPM±5 and key matching Fase 3: Auto-warp samples to project tempo via warp_clip_to_bpm Fase 4: Connect pattern_library engines (BassPatterns, ChordProgressions, MelodyGenerator) Fase 5: Harmonic coherence — detect key from drumloop and transpose MIDI Fase 6: SentimientoLatino2025 + reggaeton3 integrated — 616 samples, 19 clean categories New files: - engines/bpm_key_parser.py — robust BPM+key parser for filenames - engines/populate_bpm_from_filenames.py — DB population script - engines/recategorize_samples.py — category normalization (19 categories) Modified: - score_renderer.py — DB selection, auto-warp, engine patterns, key detection, 18 categories - ai_loop.py — SYSTEM_PROMPT with full category list
51 lines
2.0 KiB
Markdown
51 lines
2.0 KiB
Markdown
# CLAUDE.md - AbletonMCP_AI v3.2
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> **Canonical project context** for AI agents.
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> Read this BEFORE doing any work.
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## CRITICAL RULES
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1. **NEVER touch `libreria/` or `librerias/`** - User's sample library.
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2. **NEVER delete project files** - Overwrite only.
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3. **NEVER create debug .md files in project root** - All in `AbletonMCP_AI/docs/`.
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4. **ALWAYS compile after changes**: `python -m py_compile "<file_path>"`
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5. **ALWAYS restart Ableton** after changes to `__init__.py`.
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6. **STRICT SESSION VIEW ONLY** - Arrangement View is discarded for production.
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## Architecture
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```
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AbletonMCP_AI/
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├── __init__.py # Remote Script (All-in-one API)
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├── docs/ # Sprints & SYSTEM_SCORE_RENDER.md
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└── mcp_server/
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├── server.py # MCP Server (130+ tools)
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├── score_engine.py # [NEW] Pure Python song data model
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├── score_renderer.py # [NEW] Session View renderer
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├── ai_loop.py # [NEW] Autonomous production loop
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└── scores/ # [NEW] JSON song storage
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```
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## Primary Workflow (Score → Render)
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The preferred way to produce music is the **Compose-then-Render** pipeline:
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1. **Compose**: Use `compose_from_template` or incremental `new_score` + `compose_*` tools.
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2. **Review**: Use `get_score` to see the JSON structure.
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3. **Save**: Use `save_score` to persist the canzone in `mcp_server/scores/`.
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4. **Render**: Use `render_score` to inject the JSON into Ableton's Session View.
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5. **Batch**: Use `render_all_scores` to produce multiple songs at once.
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## How It Works
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1. **Ableton** starts TCP server (9877).
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2. **MCP tools** build a `SongScore` object in memory.
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3. **Renderer** translates JSON sections to **Scenes** and definitions to **Clip Slots**.
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4. **Patterns** (Dembow, Bass, etc.) are resolved server-side into MIDI notes.
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## Workflow
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- **Kimi** codes fast, implements features.
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- **Qwen** verifies, compiles, debugs, creates next sprint.
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- Refer to `docs/SYSTEM_SCORE_RENDER.md` for full technical details.
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