198 lines
9.5 KiB
TypeScript
198 lines
9.5 KiB
TypeScript
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import React from 'react';
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import { TerminalBlock } from '../components/TerminalBlock';
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import { Check, ArrowRight } from 'lucide-react';
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import { Link } from 'react-router-dom';
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export const Services: React.FC = () => {
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return (
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<div className="bg-paper min-h-screen pt-24 pb-24">
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<div className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
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<header className="max-w-3xl mb-24">
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<h1 className="font-serif text-4xl md:text-5xl text-ink leading-tight mb-8">
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Services
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</h1>
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<p className="font-serif text-xl text-subtle leading-relaxed border-l-4 border-ink pl-6">
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We operate at the intersection of software engineering and machine learning research. Our engagements are typically project-based or retainer-style for high-growth technical teams who need to ship, not just explore.
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</p>
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</header>
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<div className="space-y-32">
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{/* Service Block 1: MVP */}
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<section className="grid grid-cols-1 lg:grid-cols-2 gap-16 items-center border-t border-gray-200 pt-16">
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<div>
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<div className="flex items-center gap-4 mb-4">
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<span className="font-sans font-bold text-xs uppercase tracking-widest text-accent">01 — Prototyping</span>
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<div className="h-px bg-gray-200 flex-grow"></div>
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</div>
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<h3 className="font-serif text-3xl text-ink mb-6">Accelerated MVP</h3>
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<p className="font-serif text-lg text-subtle leading-relaxed mb-8">
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We help founders and technical leads validate AI hypotheses quickly. Instead of spending months hiring a full ML team, we deliver a production-ready prototype in 4-6 weeks.
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</p>
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<ul className="space-y-4 font-sans text-sm text-gray-600 mb-8">
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{[
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"Full stack implementation (React + Python/Node)",
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"Model selection (Gemini, Claude, OpenAI) & prompt engineering",
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"Basic evaluation pipeline setup",
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"Deployment to your cloud (AWS/GCP)"
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].map((item, i) => (
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<li key={i} className="flex items-start">
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<Check className="w-5 h-5 text-green-600 mr-3 shrink-0" />
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<span>{item}</span>
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</li>
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))}
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</ul>
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</div>
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<div className="relative">
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<div className="absolute -inset-4 bg-gray-100 rounded-lg transform rotate-2 z-0"></div>
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<TerminalBlock
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title="api/routes.py"
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lines={[
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"@app.post('/generate')",
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"async def generate_insight(ctx: Context):",
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" # Production-ready guardrails",
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" if not guardrails.check(ctx.prompt):",
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" raise SecurityException('Injection detected')",
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"",
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" # Structured output with retries",
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" response = await llm.generate(",
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" model='gemini-2.5-flash',",
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" prompt=build_prompt(ctx),",
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" schema=InsightSchema",
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" )",
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" return response"
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]}
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className="relative z-10 shadow-2xl"
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/>
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</div>
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</section>
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{/* Service Block 2: Audit */}
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<section className="grid grid-cols-1 lg:grid-cols-2 gap-16 items-center border-t border-gray-200 pt-16">
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<div className="lg:order-2">
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<div className="flex items-center gap-4 mb-4">
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<span className="font-sans font-bold text-xs uppercase tracking-widest text-accent">02 — Architecture</span>
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<div className="h-px bg-gray-200 flex-grow"></div>
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</div>
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<h3 className="font-serif text-3xl text-ink mb-6">RAG & System Audit</h3>
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<p className="font-serif text-lg text-subtle leading-relaxed mb-8">
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Your retrieval system is likely the bottleneck. We perform a rigorous audit of your embedding strategies, chunking logic, and reranking stages to improve context relevance and reduce hallucinations.
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</p>
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<ul className="space-y-4 font-sans text-sm text-gray-600 mb-8">
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{[
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"Vector Database Indexing Strategy Review",
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"Embedding Latency & Cost Analysis",
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"Context Window Optimization",
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"Security & Prompt Injection Vulnerability Scan"
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].map((item, i) => (
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<li key={i} className="flex items-start">
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<Check className="w-5 h-5 text-green-600 mr-3 shrink-0" />
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<span>{item}</span>
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</li>
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))}
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</ul>
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</div>
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<div className="lg:order-1 relative">
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<div className="absolute -inset-4 bg-gray-100 rounded-lg transform -rotate-1 z-0"></div>
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<TerminalBlock
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title="audit_report.json"
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lines={[
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"{",
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" 'system_health': 'DEGRADED',",
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" 'metrics': {",
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" 'retrieval_precision_at_5': 0.42,",
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" 'average_latency_ms': 1250,",
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" 'hallucination_rate': '15%'",
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" },",
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" 'critical_findings': [",
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" 'Embedding dimension mismatch in legacy index',",
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" 'Missing semantic cache for frequent queries'",
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" ],",
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" 'recommendation': 'Migrate to hybrid search'",
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"}"
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]}
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className="relative z-10 shadow-2xl"
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/>
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</div>
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</section>
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{/* Service Block 3: Integration */}
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<section className="grid grid-cols-1 lg:grid-cols-2 gap-16 items-center border-t border-gray-200 pt-16">
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<div>
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<div className="flex items-center gap-4 mb-4">
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<span className="font-sans font-bold text-xs uppercase tracking-widest text-accent">03 — Fine-tuning</span>
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<div className="h-px bg-gray-200 flex-grow"></div>
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</div>
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<h3 className="font-serif text-3xl text-ink mb-6">Custom Model Integration</h3>
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<p className="font-serif text-lg text-subtle leading-relaxed mb-8">
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When prompt engineering hits a wall, we fine-tune open weights (Llama 3, Mistral, Gemma) on your proprietary data. We handle the data cleaning, training runs (LoRA/QLoRA), and deployment optimization.
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</p>
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<ul className="space-y-4 font-sans text-sm text-gray-600 mb-8">
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{[
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"Dataset curation and cleaning pipelines",
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"Parameter-Efficient Fine-Tuning (LoRA)",
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"Evaluation against base model benchmarks",
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"Private cloud deployment (AWS/GCP/Azure)"
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].map((item, i) => (
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<li key={i} className="flex items-start">
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<Check className="w-5 h-5 text-green-600 mr-3 shrink-0" />
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<span>{item}</span>
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</li>
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))}
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</ul>
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</div>
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<div className="relative">
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<div className="absolute -inset-4 bg-gray-100 rounded-lg transform rotate-1 z-0"></div>
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<TerminalBlock
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title="train_lora.sh"
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lines={[
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"$ torchrun --nproc_per_node=8 train.py \\",
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" --model_name 'mistralai/Mistral-7B' \\",
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" --data_path './proprietary_docs' \\",
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" --output_dir './finetuned_weights' \\",
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" --use_lora True \\",
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" --lora_r 16 \\",
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" --lora_alpha 32 \\",
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" --quantization '4bit'",
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"",
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"# Training started...",
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"# Epoch 1: loss=0.45",
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"# Epoch 2: loss=0.32"
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]}
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className="relative z-10 shadow-2xl"
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/>
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</div>
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</section>
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<section className="bg-ink text-white p-12 md:p-16 rounded-sm mt-12 text-center relative overflow-hidden">
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<div className="relative z-10">
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<h3 className="font-serif text-3xl mb-6">Ready to build?</h3>
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<p className="font-sans text-gray-300 mb-10 max-w-lg mx-auto text-lg">
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We take on a limited number of clients per quarter to ensure deep technical focus on every project.
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</p>
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<a href="mailto:hello@pradit.app" className="inline-flex items-center bg-white text-ink font-bold py-4 px-10 hover:bg-gray-100 transition-colors rounded-sm">
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Schedule Consultation <ArrowRight className="ml-2 w-5 h-5" />
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</a>
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</div>
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{/* Background decoration */}
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<div className="absolute top-0 left-0 w-full h-full opacity-10 pointer-events-none">
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<div className="grid grid-cols-12 h-full">
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{[...Array(12)].map((_, i) => (
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<div key={i} className="border-r border-white/20 h-full"></div>
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))}
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</div>
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</div>
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</section>
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</div>
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</div>
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</div>
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);
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}; |