Resonance Loop Protocol
Relevant source files
The following files were used as context for generating this wiki page:
The Resonance Loop Protocol manages cognitive synthesis and acoustic alignment within the GestaltView system. It operates primarily through the generative engine to calculate resonance between user context and artificial intelligence responses. This protocol ensures that generated artifacts and voice outputs maintain a consistent "frequency" with the user's established Personal Language Key (PLK).
This system spans two primary domains: the high-level cognitive synthesis in the api/gen-engine and the low-level acoustic modulation in the billy_voice subsystem. By evaluating intent against core embodiment schemas, the protocol validates that every output resonates with the user's identity before it passes through system Execution Gates.
Sources: diagram_inventory.json:51, diagram_inventory.json:69, diagram_inventory.json:103
Generative Engine Integration
The Resonance Loop Protocol exposes a dedicated endpoint within the api/gen-engine route surface. The Resonance Handler processes calculations that bridge the gap between raw generative output and the user's personal context.
API Architecture
The protocol follows a structured routing path from client requests to the generative core. When a client initiates a resonance-dependent task, the request travels through the following components:
- Endpoint:
/resonanceserves as the entry point for resonance calculations. - Orchestration: The request is routed to the
Resonance Handler. - Engine Logic: The logic is executed within
gestaltview_generative_engine.py. - Persistence: Finalized resonance states are synchronized via the
Engine Persistence Bridgeto Supabase storage.
Sources: diagram_inventory.json:69, build_story_artifact.py:108
The diagram shows the request flow from the client to the persistence layer through the Resonance Handler.
Sources: diagram_inventory.json:69
Voice Synthesis Resonance
Acoustic resonance is managed by the billy_voice and Voice Studio subsystems. This implementation ensures that the digital intelligence's voice synthesis sounds authentically aligned with the user's register rather than generic prose.
Acoustic Modulation
The protocol utilizes specific methods to adjust the synthesis stream:
synthesizeSpeechStream(): Generates the raw audio output.adjustResonanceFrequency(): Modifies the output to match the resonance parameters defined in the user's PLK profile.
Sources: diagram_inventory.json:51
The sequence diagram illustrates how ToneGuard diagnostics trigger frequency adjustments during speech synthesis.
Sources: diagram_inventory.json:51
Technical Specifications
The Resonance Loop Protocol is defined within the specs/ directory as part of the Gen-Engine Specs. These documents outline the technical requirements for the resonance pipeline, ensuring it integrates correctly with fusion and prediction modules.
| Component | Responsibility | Relevant Entity |
|---|---|---|
| Resonance Pipeline | Calculates cognitive alignment | Gen-Engine Specs |
| Resonance Handler | Manages API requests for resonance | api/gen-engine/resonance.ts |
| Frequency Adjuster | Modifies acoustic resonance | billy_voice/ |
| Execution Gate | Validates resonance invariants | EngineCore.ts |
Sources: diagram_inventory.json:66, diagram_inventory.json:69, diagram_inventory.json:103
Resonance Invariants
Before an artifact is finalized, the protocol checks for specific invariants:
- Presence: Verifies the output is consistent with the "Keeper of Threads" archetype.
- Acoustic Integrity: Ensures
adjustResonanceFrequency()has been applied to voice streams. - Isolation: Validates that resonance calculations do not leak across different user profiles.
Sources: diagram_inventory.json:49, diagram_inventory.json:51, diagram_inventory.json:66
Conclusion
The Resonance Loop Protocol functions as a critical bridge between natural language intent and technical execution. It ensures that both cognitive synthesis and voice synthesis remain grounded in the user's individual context, preventing the system from producing generic or dissonant outputs. By integrating directly with the gestaltview_generative_engine.py and the billy_voice library, it maintains system-wide coherence.