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MeloMed Behavioral AI Core (Private)
This repository contains MeloMed’s internal behavioral-AI components: journal understanding, emotional embeddings, lyrical resonance, and music-mood interpretation.
📌 Modules (Planned)
1. Implicit Emotion Classifier
Detects:
- emotional drift
- rumination score
- avoidance index
- fragmentation level
- urgency signals
Base models: RoBERTa / DistilBERT (HuggingFace)
2. Journal Embedding Tracker
Tracks emotional change across entries:
- volatility
- stability score
- regression points
- resilience increments
Based on sentence-transformers (mpnet / MiniLM).
3. Lyrical Resonance Engine
Computes similarity between user journal embeddings and song lyric embeddings. This drives MeloMed’s music-based journaling personalization.
4. Mood → Music Feature Extractor
Extracts emotional metadata from songs:
- energy
- valence
- timbre
- harmonic tension
Uses audio embedding models (CLAP / MusicGen encoders).
5. Behavioral Prompt Generator
Dynamic therapeutic prompts based on detected emotional patterns.
🧪 Planned Files / Structure
license: apache-2.0
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