Build Your Own Dreams: Browser-based custom narrative generation

## Overview

Enable users to create personalized dream narratives that run entirely in the browser, with no server dependencies.

## User Stories

1. **As a user**, I want to describe my ideal dream scenario in a text box, so I can experience a personalized guided dream.
2. **As a user**, I want my custom dreams saved locally, so I can reuse them without regenerating.
3. **As a user**, I want the generation to work offline after initial load, so I can create dreams anywhere.

## Technical Architecture

### Client-Side Stack (All in-browser)
- **LLM**: SmolLM or similar lightweight model via WebLLM/Transformers.js
- **TTS**: Web Speech API or Piper TTS (WASM)
- **Music**: Existing procedural synthesis (already client-side capable)
- **Storage**: IndexedDB for saving generated dreams

### Generation Pipeline

```
User Input → LLM (narrative sections) → Add [PAUSE] markers → TTS → Mix with music → Save to IndexedDB
```

## Implementation Phases

### Phase 1: MVP - Text-to-Narrative
- [ ] Integrate SmolLM via WebLLM for narrative generation
- [ ] Create prompt templates for dream narrative style
- [ ] UI: Simple text input + "Generate" button
- [ ] Generate narrative in sections (intro, scenes, transitions, outro)
- [ ] Auto-insert [PAUSE] markers between sections
- [ ] Display generated narrative for review/editing

### Phase 2: Audio Generation
- [ ] Integrate browser TTS (Web Speech API as fallback, Piper WASM for quality)
- [ ] Port music generation to client-side (already uses numpy-like operations)
- [ ] Combine narration + music in browser (Web Audio API)
- [ ] Export as playable audio blob

### Phase 3: Persistence & Polish
- [ ] Save custom dreams to IndexedDB
- [ ] Show custom dreams in library alongside pre-made dreams
- [ ] Allow editing/regenerating sections
- [ ] Share custom dreams (export/import JSON)

## Key Technical Decisions

| Decision | Choice | Rationale |
|----------|--------|-----------|
| LLM Runtime | WebLLM | Best performance for in-browser LLMs |
| Model | SmolLM-360M or similar | Small enough for mobile, good enough for narratives |
| TTS | Piper WASM (primary), Web Speech API (fallback) | Quality vs. compatibility tradeoff |
| Storage | IndexedDB | Large audio file support, offline access |

## Complexity Estimate

- Phase 1: Medium (2-3 weeks) - LLM integration is the main challenge
- Phase 2: High (3-4 weeks) - Audio pipeline in browser is complex
- Phase 3: Low (1 week) - Standard CRUD operations

## References

- SmolLM demo: https://context-lab.com/llm-course/demos/chatbot-evolution/
- WebLLM: https://github.com/mlc-ai/web-llm
- Piper TTS: https://github.com/rhasspy/piper

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_Split from #115 - targeted dream content (pre-made narratives completed)_