kofdai/vera-gemma4-12b-telepathic-swarm

🧠 Verantyx: Telepathic Swarm Architecture (Gemma 4 12B)

Verantyx is a revolutionary multi-agent AI architecture that completely discards traditional "prompt-to-text" token passing between agents. Instead, it uses Telepathic Swarm Intelligence — agents communicate pure, abstract mathematical concepts (high-dimensional latent vectors) directly to each other's hidden layers.

This repository contains the core Hybrid Inverse Topology Decoder and the models required to run the Verantyx Swarm locally.

🌟 The Architecture

Verantyx splits the traditional LLM pipeline into three distinct phases:

1. The Commander (JCross Core)

• —Model: commander_12b_rank1024.jgen (7.8GB)
• —Role: Takes human natural language and encodes it into an Intent Vector. It does not generate text. It generates pure thought and broadcasts it.

2. The Swarm (Workers / JCross Core)

• —Model: gemma_12b_generative.jgen (3.9GB)
• —Role: Workers receive the Intent Vector. Instead of generating text, they run a Puzzle Inference Engine (a * torch.roll(b, shifts=1, dims=-1)). They debate geometrically in latent space, combining their topologies until they reach a mathematically stable "Consensus Vector" (aligned_vector). No words are spoken during this debate.

3. The Telepathic Coder (Hybrid Logit Blending Decoder)

• —Model: gemma_12b_generative.jgen + Native Hugging Face GemmaForCausalLM
• —Role: Translates the Swarm's final Consensus Vector into flawless, executable code.

🔧 How the Hybrid Decoder Works (The Magic)

Previously, trying to decode abstract concepts back into text resulted in "Word Salad" or "Repetition Collapse" (e.g., repeating the word Stack infinitely). We solved this by creating the Hybrid Inverse Topology Decoder:

1. 1.Manifold Alignment: We use a calibrated transformation matrix (manifold_alignment.pt) to perfectly align the JCross vector space with Gemma's native vocabulary space.
2. 2.Intent Logits: The aligned vector is projected into a 32,000-dimensional probability distribution (what the Swarm wants to say).
3. 3.Logit Blending: We start Hugging Face's native model.generate(). At every single step of generation, a custom LogitsProcessor gently adds the Swarm's Intent Logits to Gemma's own predictions.
4. 4.Exponential Decay: The influence of the Swarm starts at a strength of 0.3 and decays by 0.95 per token. This forces Gemma to start writing based on the Swarm's intent, but rely on its own flawless syntax engine to finish the thought.

🚀 How to Run

1. 1.Clone this repository.
2. 2.Ensure you have the transformers and torch libraries installed.
3. 3.Use the provided Python scripts in cli/scripts/ to launch a Master node (Commander) and Worker nodes (Swarm).

# Example: Start a worker node
python3 cli/scripts/telepathic_coder.py --cluster-mode worker

# Example: Send a command from the master node
python3 cli/scripts/verantyx_shell.py --cluster-mode master

📂 Repository Contents

• —commander_12b_rank1024.jgen: The Master intent encoder.
• —gemma_12b_generative.jgen: The Swarm debate core.
• —telepathic_coder_lossless.jgen: The Telepathic Coder model containing Telepathy Receptors for stabilization.
• —manifold_alignment.pt: The spatial translation matrix.
• —cli/scripts/: Complete Python codebase for running the CLI, Swarm, and Hybrid Decoder.