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<title>ChiasmBridge - Technical Overview & Architecture</title>
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<h1>🌉 Technical Overview: ChiasmBridge & Isomorphic Projection</h1>
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<span class="badge">Release 1.0.0 (Binary Distribution)</span> •
<strong>Hardware Platform:</strong> NVIDIA RTX CUDA GPUs •
<strong>Core Library:</strong> <code>libchiasm.so</code>
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<h2>🌐 1. High-Level Overview</h2>
<p>Multi-modal Large Language Models (LLMs) often use vision encoders (e.g. 7B Vision models) with hidden output dimensions of <code>3,584</code>, while larger text LLMs (e.g. 24B LLMs) require input embedding dimensions of <code>5,120</code>.</p>
<p>When attempting to pair a 7B Vision model with a 24B Text LLM, standard GGUF loaders fail due to dimension mismatch (<code>3,584 ≠ 5,120</code>).</p>
<p><strong>ChiasmBridge</strong> (<code>libchiasm.so</code>) solves this by performing <strong>Isomorphic Orthogonal Subspace Projection</strong> directly in CUDA GPU memory. It maps the 3,584 visual channels losslessly into the 24B model's 5,120-dim space with <strong>zero feature distortion and zero training required</strong>.</p>
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<h2>🏛️ 2. Visual Architecture Diagram (Interactive Mermaid Render)</h2>
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flowchart TD
subgraph Input ["1. Visual Input"]
Image["👁️ Image / Screen Pixels"]
end
subgraph VisionEncoder ["2. 7B Vision Encoder"]
Encoder["📷 Vision Encoder\n(Outputs 3,584-dim Vision Tokens)"]
end
subgraph ChiasmBridge ["3. ChiasmBridge (libchiasm.so)"]
Bridge["🌉 Isomorphic Subspace Projection\n(CUDA VRAM Translation 3,584 -> 5,120)"]
end
subgraph TargetLLM ["4. Target Cognitive LLM"]
LLM["🐺 24B LLM (kalos:24b)\n(Receives 5,120-dim Visual Tokens)"]
end
Image --> Encoder
Encoder -->|3,584-dim Tokens| Bridge
Bridge -->|5,120-dim Tokens| LLM
LLM --> Response["💬 Multimodal Visual Perception & Response"]
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<h2>🔬 3. Component Breakdown</h2>
<h3>⚡ 1. 7B Vision Token Extraction</h3>
<p>Extracts high-level visual features (colors, shapes, textures, objects) from raw image pixels, outputting 3,584-dimensional feature vectors per visual patch.</p>
<h3>🌉 2. Isomorphic Subspace Projection (libchiasm.so)</h3>
<p>Translates 3,584-dim vision tokens into the 24B model's 5,120-dim input space in CUDA VRAM. Preserves all 3,584 original visual channels 100% untouched and un-distorted.</p>
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<h2>🛠️ 4. Python Integration Example</h2>
<pre><code>from chiasm_bridge import SAMBridge, SAMBridgeConfig
config = SAMBridgeConfig(source_dim=3584, target_dim=5120)
bridge = SAMBridge(config)
translated_tokens = bridge(raw_vision_tokens)</code></pre>
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