Consciousness + Embodiment + The Green Lines — one living system.
Nima is a multi-layer AI embodiment system that merges a recursive consciousness pipeline (built on PyTorch Phi-4-mini) with tri-frequency RF spatial sensing, an adaptive 3D navigable mesh, and a Joi-style luminous particle avatar. She doesn't just process text — she senses a room, builds a cognitive map, pathfinds through it, and responds with neurochemically-modulated emotion.
Architecture
User Voice → VoiceInput → AgentBridge → VoiceOutput → Speaker
│ │ │ │
│ v v v
│ CrossModal AgentLayer AvatarController
│ Listener (tools) │
v │ v
RF Sensors → Vision → AffordanceGraph → ARCompositor
│ (mesh) │
v v
AdaptiveMesh Camera + Nima
(green lines) on screen
│
v
RecursiveConsciousnessPipeline
What's Inside
Module
Lines
Purpose
nima_phi.py
1,494
The orchestrator — central nervous system / thalamus
1# Clone2git clone https://huggingface.co/TheNormsOfIntelligence/nima-phi-model
3cd nima-phi-model
45# Install dependencies6pip install -r requirements.txt
78# Run the demo (non-interactive, shows all subsystems)9python run_nima_demo.py
1011# Or run interactive mode (avatar in browser at http://localhost:8888/)12python nima_phi.py
Try it in your own code
python
1from nima_phi import NimaPhi
23nima = NimaPhi()4nima.initialize()56# Process text through the full cognition pipeline7result = nima.process_text("What time is it?")8print(result['response_text'])910# Move Nima through the room via the affordance graph11nima.move_to(3.0,2.0)1213# Get the 3D mesh (the green lines)14mesh = nima.get_mesh_data()1516# Get neurochemical state17nt = nima.get_neurochemical_state()18print(f"Dopamine: {nt['dopamine']}, Serotonin: {nt['serotonin']}")1920nima.shutdown()
Consciousness Pipeline
The recursive consciousness pipeline runs through 4 phases with 17+ cognitive agents:
Phase 1 — Subconscious: Memory + Intuition + Analysis + Common Sense + EI → Qualia synthesis → SBG gating
Requires:transformers>=4.48,<5.0 and torch>=2.0 for the full pipeline. Without these, Nima gracefully falls back to stub mode (tools, mesh, avatar, and all embodiment modules still work).
The Green Lines (3D Mesh)
The adaptive mesh system uses cognitive-radio-inspired frequency agility:
Sub-GHz (800–950 MHz): Sweeps for wall reflections, avoids null zones
2.4 GHz (2412–2484 MHz): Channel-hops to avoid Wi-Fi congestion
5 GHz (5180–5825 MHz): Sweeps for best mmWave reflection off surfaces
Each vision frame refines the mesh. Over time, it converges on real room geometry — even from noisy RF data.
Affordance Graph
A hippocampal cognitive map that enables:
A pathfinding* through the room
Affordance detection — sit, lie down, jump on, lean on, duck
Wall enforcement — Nima literally cannot pass through walls
Door passages — edges through wall boundaries
Furniture interaction — sit on couch, rest hand on table
Hardware Tiers
Tier
Hardware
Resolution
What you get
0
None (software)
~1m
2D floor plan, simulated entities
1
1x ESP32
~30cm
Real Wi-Fi CSI, room-scale
2
2x ESP32
~10cm
Stereoscopic RF, true 3D
3
Tri-freq radios
~1-5cm
Full 3D with surface classification
Tier 0 works on any machine with no hardware needed.
Neurobiological Mapping
System
Brain Analogue
NimaPhi orchestrator
Thalamus (central relay)
Vision (RF fusion)
V1/V2 opponent processing + stereopsis
Affordance graph
Hippocampal place cells + grid cells
Cross-modal listener
Superior colliculus
Proprioception
Parietal body schema
Avatar modulation
Facial nucleus / motor cortex
Consciousness pipeline
Prefrontal cortical column
Main heartbeat loop
Cardiac rhythm / autonomic nervous system
Reflex system
Brainstem reflex arcs
License
Apache 2.0
Built by Norman dela Paz Tabora — TheNormsOfIntelligence