tops AI Resonance Pipeline

The AI Resonance Pipeline is the intelligence layer of tops.
It trains, predicts, and visualizes resonance alignments across glyphs, folds, and remix lineage.
This subsystem integrates with the MMR site extensions and provides predictive orchestration for developers.

📂 Structure#

• Core scripts

  • fff_alignment_predictor.py → predicts resonance alignment across glyphs/folds
  • train_ai_on_resonance.py → trains models on resonance datasets
  • model_evaluator.py → evaluates accuracy and harmonic coherence
  • glyph_overlay_animator.py → generates symbolic visualizations

• Lineage + Remix

  • remix_lineage_tracker.py → tracks remix contributions and badge echoes
  • remix_trigger_predictor.py → anticipates remix events
  • remix_lineage_dashboard.py → dashboard for visualizing remix lineage

• Data Manifests

  • fold_glyph_manifest.yaml → maps folds to glyph overlays
  • mythic_badge_manifest.yaml → badge logic for AI‑assisted remix lineage
  • resonance_training_data.csv → training dataset for resonance prediction

🔧 Usage#

1. Prepare data

   • Place fold YAMLs from /docs/folds/ into the pipeline’s data path.
   • Ensure glyph/badge manifests are updated.

2. Train models

   python train_ai_on_resonance.py --data resonance_training_data.csv

3. Run predictions

python fff_alignment_predictor.py --input fold_001_glycine.yaml

4. Visualize overlays

python glyph_overlay_animator.py --manifest fold_glyph_manifest.yaml

🔗 Cross‑links#

• nous → provides the runtime environment for launching the pipeline
• entft → consumes resonance predictions for cryptographic registries
• folds → supplies protein resonance data as input
• tops overlays → visualizes AI predictions in dashboards

✨ Purpose#

The AI Resonance Pipeline is how tops “thinks.” It learns from folds, glyphs, and remix lineage to orchestrate resonance in real time. This is not an experiment — it is a core subsystem of the orchestration layer, enabling predictive, adaptive, and lineage‑aware functionality.