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<title>Quantum Code Weaver Engine - Architecture Dashboard</title>
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<h1 class="text-5xl md:text-7xl font-bold mb-4 bg-clip-text text-transparent bg-gradient-to-r from-cyan-400 to-purple-500">
Quantum Code Weaver Engine
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A distributed, graph-based coding engine transforming software development from conversation to state-space search.
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<!-- Architecture Overview -->
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<h2 class="text-3xl font-bold">System Architecture</h2>
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State-Driven Execution
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<architecture-diagram></architecture-diagram>
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<h2 class="text-3xl font-bold mb-8 text-center">System Status</h2>
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<h2 class="text-3xl font-bold mb-8 text-center">Performance Metrics</h2>
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<h2 class="text-3xl font-bold mb-8">Architecture Components</h2>
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<!-- Brain Card -->
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<i data-feather="cpu"></i>
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<h3 class="text-xl font-bold">The Brain</h3>
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<p class="text-gray-300 mb-4">Local LLM Orchestrator responsible for verification, scoring, and routing.</p>
<ul class="text-sm text-gray-400 space-y-2">
<li class="flex items-center"><i data-feather="check" class="w-4 h-4 mr-2 text-cyan-400"></i> Zero heavy generation</li>
<li class="flex items-center"><i data-feather="check" class="w-4 h-4 mr-2 text-cyan-400"></i> JSON-in, JSON-out only</li>
<li class="flex items-center"><i data-feather="check" class="w-4 h-4 mr-2 text-cyan-400"></i> Hot state processing</li>
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<i data-feather="activity"></i>
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<h3 class="text-xl font-bold">The Muscle</h3>
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<p class="text-gray-300 mb-4">Cloud LLM Workers for high-volume, parallel code generation.</p>
<ul class="text-sm text-gray-400 space-y-2">
<li class="flex items-center"><i data-feather="cpu" class="w-4 h-4 mr-2 text-purple-400"></i> Stateless functions</li>
<li class="flex items-center"><i data-feather="zap" class="w-4 h-4 mr-2 text-purple-400"></i> Parallel execution</li>
<li class="flex items-center"><i data-feather="code" class="w-4 h-4 mr-2 text-purple-400"></i> AST-compliant output</li>
</ul>
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<i data-feather="radio"></i>
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<h3 class="text-xl font-bold">Nervous System</h3>
</div>
<p class="text-gray-300 mb-4">Redis-based Pub/Sub queue implementing the Hot Event Loop.</p>
<ul class="text-sm text-gray-400 space-y-2">
<li class="flex items-center"><i data-feather="fast-forward" class="w-4 h-4 mr-2 text-red-400"></i> Async decoupling</li>
<li class="flex items-center"><i data-feather="layers" class="w-4 h-4 mr-2 text-red-400"></i> Task & result queues</li>
<li class="flex items-center"><i data-feather="refresh-cw" class="w-4 h-4 mr-2 text-red-400"></i> Real-time processing</li>
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<i data-feather="database"></i>
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<h3 class="text-xl font-bold">Long-Term Memory</h3>
</div>
<p class="text-gray-300 mb-4">Neo4j graph database storing the Verification Graph.</p>
<ul class="text-sm text-gray-400 space-y-2">
<li class="flex items-center"><i data-feather="git-merge" class="w-4 h-4 mr-2 text-green-400"></i> Nodes = Verified states</li>
<li class="flex items-center"><i data-feather="link" class="w-4 h-4 mr-2 text-green-400"></i> Edges = Derivation paths</li>
<li class="flex items-center"><i data-feather="filter" class="w-4 h-4 mr-2 text-green-400"></i> No failed attempts stored</li>
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<h2 class="text-2xl font-bold mb-6">Orchestrator Scaffolding</h2>
<div class="bg-gray-900 rounded-lg p-4 overflow-x-auto">
<pre class="text-gray-300 text-sm font-mono">
<span class="text-cyan-400">class</span> <span class="text-yellow-400">Orchestrator</span>:
<span class="text-cyan-400">def</span> __init__(<span class="text-green-400">self</span>, redis_host: str = <span class="text-red-400">"localhost"</span>, redis_port: int = <span class="text-purple-400">6379</span>):
<span class="text-green-400">self</span>.redis_client = redis.Redis(host=redis_host, port=redis_port)
<span class="text-green-400">self</span>.neo4j_driver = GraphDatabase.driver(<span class="text-red-400">"bolt://localhost:7689"</span>)
<span class="text-green-400">self</span>.threshold_score = <span class="text-purple-400">0.8</span>
<span class="text-gray-500"># Async initialization complete</span>
<span class="text-cyan-400">async def</span> <span class="text-yellow-400">poll_results</span>(<span class="text-green-400">self</span>) -> List[Dict[str, Any]]:
<span class="text-gray-500">"""Continuously poll Redis for worker results"""</span>
<span class="text-cyan-400">while</span> <span class="text-yellow-400">True</span>:
result = <span class="text-green-400">self</span>.redis_client.rpop(<span class="text-red-400">"queue:results"</span>)
<span class="text-cyan-400">if</span> result:
<span class="text-cyan-400">yield</span> json.loads(result)
<span class="text-cyan-400">await</span> asyncio.sleep(<span class="text-purple-400">0.01</span>)
<span class="text-cyan-400">def</span> <span class="text-yellow-400">evaluate_candidate</span>(<span class="text-green-400">self</span>, candidate: Dict[str, Any]) -> float:
<span class="text-gray-500">"""Score code candidate (stubbed with LLM integration)"""</span>
<span class="text-cyan-400">return</span> random.uniform(<span class="text-purple-400">0</span>, <span class="text-purple-400">1</span>) <span class="text-gray-500"># Placeholder for LLM scoring</span>
<span class="text-cyan-400">async def</span> <span class="text-yellow-400">update_graph</span>(<span class="text-green-400">self</span>, candidate: Dict[str, Any], score: float):
<span class="text-gray-500">"""Commit to Neo4j if score exceeds threshold"""</span>
<span class="text-cyan-400">if</span> score > <span class="text-green-400">self</span>.threshold_score:
<span class="text-cyan-400">with</span> <span class="text-green-400">self</span>.neo4j_driver.session() <span class="text-cyan-400">as</span> session:
session.run(...) <span class="text-gray-500"># Graph update logic</span></pre>
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