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<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>MEXAR β€” Multimodal Explainable AI Reasoning Assistant</title>
    <meta name="description" content="Build domain-specific AI agents from your documents. Grounded, cited, and faithfully scored answers with full explainability.">
    <link rel="preconnect" href="https://fonts.googleapis.com">
    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800;900&family=JetBrains+Mono:wght@400;500&display=swap" rel="stylesheet">
    <style>

        :root {

            --bg-primary: #080c14;

            --bg-secondary: #0d1420;

            --bg-card: #111827;

            --bg-card-hover: #1a2236;

            --border: rgba(99, 120, 255, 0.15);

            --border-bright: rgba(99, 120, 255, 0.4);

            --accent-blue: #6378ff;

            --accent-cyan: #00d4ff;

            --accent-purple: #a855f7;

            --accent-green: #10b981;

            --accent-orange: #f59e0b;

            --text-primary: #f1f5f9;

            --text-secondary: #94a3b8;

            --text-muted: #475569;

            --glow-blue: rgba(99, 120, 255, 0.3);

            --glow-cyan: rgba(0, 212, 255, 0.2);

        }



        * { margin: 0; padding: 0; box-sizing: border-box; }



        body {

            font-family: 'Inter', sans-serif;

            background: var(--bg-primary);

            color: var(--text-primary);

            min-height: 100vh;

            overflow-x: hidden;

        }



        /* ── Animated gradient background ── */

        body::before {

            content: '';

            position: fixed;

            top: 0; left: 0; right: 0; bottom: 0;

            background: 

                radial-gradient(ellipse 80% 50% at 20% 20%, rgba(99,120,255,0.08) 0%, transparent 60%),

                radial-gradient(ellipse 60% 40% at 80% 80%, rgba(168,85,247,0.06) 0%, transparent 60%),

                radial-gradient(ellipse 50% 30% at 50% 50%, rgba(0,212,255,0.04) 0%, transparent 60%);

            pointer-events: none;

            z-index: 0;

        }



        .container {

            position: relative;

            z-index: 1;

            max-width: 1100px;

            margin: 0 auto;

            padding: 0 2rem;

        }



        /* ── NAV ── */

        nav {

            padding: 1.5rem 0;

            display: flex;

            align-items: center;

            justify-content: space-between;

            border-bottom: 1px solid var(--border);

        }



        .nav-logo {

            display: flex;

            align-items: center;

            gap: 0.6rem;

            font-size: 1.35rem;

            font-weight: 800;

            letter-spacing: -0.5px;

        }



        .nav-logo .brain { font-size: 1.6rem; }



        .nav-logo .text-gradient {

            background: linear-gradient(135deg, var(--accent-blue), var(--accent-cyan));

            -webkit-background-clip: text;

            -webkit-text-fill-color: transparent;

            background-clip: text;

        }



        .nav-links { display: flex; gap: 0.75rem; align-items: center; }



        .nav-link {

            padding: 0.5rem 1rem;

            border-radius: 8px;

            text-decoration: none;

            font-size: 0.875rem;

            font-weight: 500;

            color: var(--text-secondary);

            transition: all 0.2s;

            border: 1px solid transparent;

        }



        .nav-link:hover {

            color: var(--text-primary);

            background: rgba(255,255,255,0.06);

            border-color: var(--border);

        }



        .nav-link.primary {

            background: linear-gradient(135deg, var(--accent-blue), var(--accent-purple));

            color: white;

            border: none;

        }



        .nav-link.primary:hover {

            opacity: 0.9;

            transform: translateY(-1px);

            box-shadow: 0 4px 20px var(--glow-blue);

        }



        /* ── HERO ── */

        .hero {

            padding: 5rem 0 4rem;

            text-align: center;

        }



        .hero-badge {

            display: inline-flex;

            align-items: center;

            gap: 0.5rem;

            padding: 0.4rem 1rem;

            border-radius: 100px;

            background: rgba(99,120,255,0.1);

            border: 1px solid rgba(99,120,255,0.3);

            font-size: 0.8rem;

            font-weight: 600;

            color: var(--accent-cyan);

            text-transform: uppercase;

            letter-spacing: 0.08em;

            margin-bottom: 2rem;

        }



        .hero-badge .dot {

            width: 6px; height: 6px;

            border-radius: 50%;

            background: var(--accent-cyan);

            animation: pulse 2s infinite;

        }



        @keyframes pulse {

            0%, 100% { opacity: 1; }

            50% { opacity: 0.3; }

        }



        .hero h1 {

            font-size: clamp(2.8rem, 6vw, 5rem);

            font-weight: 900;

            line-height: 1.05;

            letter-spacing: -2px;

            margin-bottom: 1.5rem;

        }



        .hero h1 .line1 { display: block; color: var(--text-primary); }

        .hero h1 .line2 {

            display: block;

            background: linear-gradient(135deg, var(--accent-blue) 0%, var(--accent-cyan) 50%, var(--accent-purple) 100%);

            -webkit-background-clip: text;

            -webkit-text-fill-color: transparent;

            background-clip: text;

        }



        .hero-subtitle {

            font-size: 1.15rem;

            color: var(--text-secondary);

            max-width: 600px;

            margin: 0 auto 2.5rem;

            line-height: 1.7;

            font-weight: 400;

        }



        .hero-cta {

            display: flex;

            gap: 1rem;

            justify-content: center;

            flex-wrap: wrap;

            margin-bottom: 3.5rem;

        }



        .btn {

            display: inline-flex;

            align-items: center;

            gap: 0.5rem;

            padding: 0.85rem 1.8rem;

            border-radius: 10px;

            font-size: 0.95rem;

            font-weight: 600;

            text-decoration: none;

            transition: all 0.25s;

            cursor: pointer;

            border: none;

        }



        .btn-primary {

            background: linear-gradient(135deg, var(--accent-blue), var(--accent-purple));

            color: white;

            box-shadow: 0 4px 24px var(--glow-blue);

        }



        .btn-primary:hover {

            transform: translateY(-2px);

            box-shadow: 0 8px 32px rgba(99,120,255,0.5);

        }



        .btn-secondary {

            background: rgba(255,255,255,0.05);

            color: var(--text-primary);

            border: 1px solid var(--border);

        }



        .btn-secondary:hover {

            background: rgba(255,255,255,0.1);

            border-color: var(--border-bright);

            transform: translateY(-1px);

        }



        .btn-outline {

            background: transparent;

            color: var(--text-secondary);

            border: 1px solid var(--border);

        }



        .btn-outline:hover {

            color: var(--text-primary);

            border-color: var(--border-bright);

        }



        /* ── STATS ROW ── */

        .stats-row {

            display: grid;

            grid-template-columns: repeat(4, 1fr);

            gap: 1px;

            background: var(--border);

            border-radius: 16px;

            overflow: hidden;

            border: 1px solid var(--border);

            margin-bottom: 5rem;

        }



        .stat-item {

            background: var(--bg-card);

            padding: 1.5rem;

            text-align: center;

        }



        .stat-value {

            font-size: 1.8rem;

            font-weight: 800;

            background: linear-gradient(135deg, var(--accent-blue), var(--accent-cyan));

            -webkit-background-clip: text;

            -webkit-text-fill-color: transparent;

            background-clip: text;

            display: block;

            margin-bottom: 0.25rem;

        }



        .stat-label {

            font-size: 0.8rem;

            color: var(--text-muted);

            font-weight: 500;

            text-transform: uppercase;

            letter-spacing: 0.05em;

        }



        /* ── PIPELINE SECTION ── */

        .section { margin-bottom: 5rem; }



        .section-label {

            font-size: 0.75rem;

            font-weight: 700;

            text-transform: uppercase;

            letter-spacing: 0.1em;

            color: var(--accent-cyan);

            margin-bottom: 0.75rem;

        }



        .section-title {

            font-size: 2rem;

            font-weight: 800;

            letter-spacing: -0.5px;

            margin-bottom: 0.75rem;

        }



        .section-subtitle {

            color: var(--text-secondary);

            font-size: 1rem;

            line-height: 1.7;

            max-width: 560px;

            margin-bottom: 2.5rem;

        }



        /* Pipeline steps */

        .pipeline {

            display: grid;

            gap: 1rem;

        }



        .pipeline-step {

            display: flex;

            align-items: flex-start;

            gap: 1.25rem;

            padding: 1.25rem 1.5rem;

            background: var(--bg-card);

            border: 1px solid var(--border);

            border-radius: 12px;

            transition: all 0.25s;

            position: relative;

            overflow: hidden;

        }



        .pipeline-step::before {

            content: '';

            position: absolute;

            left: 0; top: 0; bottom: 0;

            width: 3px;

            background: linear-gradient(180deg, var(--accent-blue), var(--accent-cyan));

            opacity: 0;

            transition: opacity 0.25s;

        }



        .pipeline-step:hover {

            border-color: var(--border-bright);

            background: var(--bg-card-hover);

        }



        .pipeline-step:hover::before { opacity: 1; }



        .step-number {

            min-width: 32px;

            height: 32px;

            border-radius: 8px;

            background: rgba(99,120,255,0.15);

            border: 1px solid rgba(99,120,255,0.3);

            display: flex;

            align-items: center;

            justify-content: center;

            font-size: 0.8rem;

            font-weight: 700;

            color: var(--accent-blue);

            font-family: 'JetBrains Mono', monospace;

        }



        .step-content { flex: 1; }



        .step-title {

            font-size: 0.95rem;

            font-weight: 600;

            margin-bottom: 0.3rem;

            display: flex;

            align-items: center;

            gap: 0.6rem;

        }



        .step-desc {

            font-size: 0.85rem;

            color: var(--text-secondary);

            line-height: 1.5;

        }



        .step-tag {

            font-size: 0.72rem;

            font-weight: 600;

            padding: 0.2rem 0.55rem;

            border-radius: 6px;

            font-family: 'JetBrains Mono', monospace;

        }



        .tag-blue { background: rgba(99,120,255,0.15); color: var(--accent-blue); }

        .tag-cyan { background: rgba(0,212,255,0.12); color: var(--accent-cyan); }

        .tag-green { background: rgba(16,185,129,0.12); color: var(--accent-green); }

        .tag-purple { background: rgba(168,85,247,0.12); color: var(--accent-purple); }

        .tag-orange { background: rgba(245,158,11,0.12); color: var(--accent-orange); }



        /* ── FEATURES GRID ── */

        .features-grid {

            display: grid;

            grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));

            gap: 1.25rem;

        }



        .feature-card {

            padding: 1.75rem;

            background: var(--bg-card);

            border: 1px solid var(--border);

            border-radius: 14px;

            transition: all 0.3s;

            position: relative;

            overflow: hidden;

        }



        .feature-card::after {

            content: '';

            position: absolute;

            top: 0; left: 0; right: 0;

            height: 1px;

            background: linear-gradient(90deg, transparent, var(--accent-blue), transparent);

            opacity: 0;

            transition: opacity 0.3s;

        }



        .feature-card:hover {

            border-color: var(--border-bright);

            background: var(--bg-card-hover);

            transform: translateY(-2px);

        }



        .feature-card:hover::after { opacity: 1; }



        .feature-icon {

            font-size: 1.8rem;

            margin-bottom: 1rem;

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            background: var(--bg-card);

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        /* ── CODE BLOCK ── */

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            .hero h1 { letter-spacing: -1px; }

            footer { flex-direction: column; text-align: center; }

        }

    </style>
</head>
<body>

<div class="container">
    <!-- NAV -->
    <nav>
        <div class="nav-logo">
            <span class="brain">🧠</span>
            <span class="text-gradient">MEXAR</span>
        </div>
        <div class="nav-links">
            <a href="/docs" class="nav-link">API Docs</a>
            <a href="/redoc" class="nav-link">ReDoc</a>
            <a href="https://github.com/devrajsinh2012/Mexar" class="nav-link" target="_blank">GitHub</a>
            <a href="https://mexar.vercel.app" class="nav-link primary" target="_blank">Open App β†’</a>
        </div>
    </nav>

    <!-- HERO -->
    <section class="hero">
        <div class="hero-badge">
            <span class="dot"></span>
            API v2.0.0 Β· Operational
        </div>

        <h1>
            <span class="line1">AI Agents That Know</span>
            <span class="line2">What They Don't Know</span>
        </h1>

        <p class="hero-subtitle">
            Build domain-specific AI agents from your documents.
            Every answer is grounded in your data, cited with inline references,
            and scored for hallucination risk using DeBERTa-v3 NLI.
        </p>

        <div class="hero-cta">
            <a href="/docs" class="btn btn-primary">πŸ“– Explore API Docs</a>
            <a href="https://mexar.vercel.app" class="btn btn-secondary" target="_blank">πŸš€ Launch App</a>
            <a href="https://github.com/devrajsinh2012/Mexar" class="btn btn-outline" target="_blank">⭐ GitHub</a>
        </div>

        <!-- STATS -->
        <div class="stats-row">
            <div class="stat-item">
                <span class="stat-value">~1.2s</span>
                <span class="stat-label">Faithfulness Scoring</span>
            </div>
            <div class="stat-item">
                <span class="stat-value">0.907</span>
                <span class="stat-label">Guardrail F1 Score</span>
            </div>
            <div class="stat-item">
                <span class="stat-value">781</span>
                <span class="stat-label">Indexed Vector Chunks</span>
            </div>
            <div class="stat-item">
                <span class="stat-value">5+</span>
                <span class="stat-label">Groq Model Fallbacks</span>
            </div>
        </div>
    </section>

    <!-- PIPELINE -->
    <section class="section">
        <div class="section-label">How It Works</div>
        <h2 class="section-title">The MEXAR RAG Pipeline</h2>
        <p class="section-subtitle">
            Every query goes through a 9-stage intelligent pipeline β€” from multimodal input
            all the way to a cited, faithfulness-verified response.
        </p>

        <div class="pipeline">
            <div class="pipeline-step">
                <div class="step-number">01</div>
                <div class="step-content">
                    <div class="step-title">
                        🎀 Multimodal Input Processing
                        <span class="step-tag tag-orange">optional</span>
                    </div>
                    <div class="step-desc">Audio β†’ Groq Whisper v3 STT Β· Images β†’ Groq Vision Β· Video β†’ OpenCV frame extraction β†’ Vision</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">02</div>
                <div class="step-content">
                    <div class="step-title">
                        πŸ” Intent &amp; Prompt Analysis
                        <span class="step-tag tag-blue">LLM</span>
                    </div>
                    <div class="step-desc">Parse query intent (factual / analytical / comparative), detect domain topic, optionally rewrite query for retrieval clarity.</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">03</div>
                <div class="step-content">
                    <div class="step-title">
                        πŸ›‘οΈ Domain Guardrail Check
                        <span class="step-tag tag-green">F1 = 0.9072</span>
                    </div>
                    <div class="step-desc">TF-IDF cosine similarity vs agent signature + spaCy NER Jaccard overlap. Threshold = 0.25. Out-of-domain queries rejected with explanation β€” no hallucination.</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">04</div>
                <div class="step-content">
                    <div class="step-title">
                        ⚑ Hybrid Vector + Keyword Retrieval
                        <span class="step-tag tag-cyan">pgvector + BM25</span>
                    </div>
                    <div class="step-desc">Dense: FastEmbed bge-small-en-v1.5 (384-dim) cosine search via pgvector. Sparse: PostgreSQL tsvector BM25 full-text search. Fused via Reciprocal Rank Fusion (RRF): score = Ξ£ 1/(rank + 60).</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">05</div>
                <div class="step-content">
                    <div class="step-title">
                        🎯 Cross-Encoder Reranking
                        <span class="step-tag tag-purple">sentence-transformers</span>
                    </div>
                    <div class="step-desc">Re-scores top-20 retrieved candidates using a cross-encoder for precision. Selects final top-5 context chunks for answer generation.</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">06</div>
                <div class="step-content">
                    <div class="step-title">
                        🧠 LLM Answer Generation
                        <span class="step-tag tag-blue">Groq</span>
                    </div>
                    <div class="step-desc">System prompt with retrieved context. Multi-model inference: llama-3.3-70b β†’ llama-3.1-8b β†’ mixtral-8x7b β†’ gemma2-9b. Automatic quota fallback.</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">07</div>
                <div class="step-content">
                    <div class="step-title">
                        πŸ“Ž Source Attribution
                        <span class="step-tag tag-cyan">citations</span>
                    </div>
                    <div class="step-desc">Match answer sentences to source chunks. Assign [1], [2], [3] inline reference markers. Track provenance per claim.</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">08</div>
                <div class="step-content">
                    <div class="step-title">
                        βœ… DeBERTa-v3 Faithfulness Scoring
                        <span class="step-tag tag-green">NLI</span>
                    </div>
                    <div class="step-desc">Extract claims from answer. For each claim-chunk pair: NLI inference (entailment β†’ faithful, contradiction β†’ hallucinated). Batched via torch.inference_mode() β€” ~1.2s/query (50Γ— speedup vs baseline).</div>
                </div>
            </div>

            <div class="pipeline-step">
                <div class="step-number">09</div>
                <div class="step-content">
                    <div class="step-title">
                        πŸ”¬ Explainability Packaging
                        <span class="step-tag tag-purple">transparent</span>
                    </div>
                    <div class="step-desc">Reasoning trace Β· Confidence breakdown Β· Sources cited Β· Guardrail decision log β€” all surfaced to the frontend UI panel.</div>
                </div>
            </div>
        </div>
    </section>

    <div class="divider"></div>

    <!-- FEATURES -->
    <section class="section">
        <div class="section-label">Capabilities</div>
        <h2 class="section-title">Everything You Need</h2>
        <p class="section-subtitle">A complete RAG platform β€” from document ingestion to explainable, grounded answers.</p>

        <div class="features-grid">
            <div class="feature-card">
                <span class="feature-icon">πŸ”</span>
                <div class="feature-title">Hybrid Search + RRF Fusion</div>
                <div class="feature-desc">Vector cosine (pgvector) and BM25 keyword search fused via Reciprocal Rank Fusion for optimal retrieval across all document types.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">βœ…</span>
                <div class="feature-title">Faithfulness Verification</div>
                <div class="feature-desc">DeBERTa-v3-base NLI model scores every answer claim against retrieved context. Quantified hallucination risk, not just vibes.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">πŸ›‘οΈ</span>
                <div class="feature-title">Domain Guardrails</div>
                <div class="feature-desc">TF-IDF + spaCy NER Jaccard similarity prevents answering out-of-domain questions. Tuned to F1 = 0.9072 at threshold 0.25.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">πŸ“Ž</span>
                <div class="feature-title">Inline Source Citations</div>
                <div class="feature-desc">Every sentence references its source chunk with [1], [2] markers. Click any citation to see the exact source text and file name.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">πŸ—£οΈ</span>
                <div class="feature-title">Multimodal Input</div>
                <div class="feature-desc">Ask questions via audio (Groq Whisper), upload images for visual Q&A (Groq Vision), or extract info from video frames (OpenCV).</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">🧠</span>
                <div class="feature-title">Explainability Panel</div>
                <div class="feature-desc">Full reasoning trace exposed in the UI: retrieval scores, reranker scores, confidence breakdown, guardrail decision, and sources cited.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">πŸ”Š</span>
                <div class="feature-title">Text-to-Speech</div>
                <div class="feature-desc">ElevenLabs API integration with per-sentence TTS playback. Falls back to Web Speech API automatically.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">⚑</span>
                <div class="feature-title">Real-time WebSocket Chat</div>
                <div class="feature-desc">Streaming responses via WebSocket with compilation progress tracking. No polling required.</div>
            </div>
            <div class="feature-card">
                <span class="feature-icon">πŸ“</span>
                <div class="feature-title">5 Document Formats</div>
                <div class="feature-desc">Upload PDF, DOCX, CSV, JSON, or TXT files. Semantic chunking preserves context boundaries for better retrieval quality.</div>
            </div>
        </div>
    </section>

    <div class="divider"></div>

    <!-- ENDPOINTS -->
    <section class="section">
        <div class="section-label">REST API</div>
        <h2 class="section-title">API Endpoints</h2>
        <p class="section-subtitle">Full interactive documentation available at <a href="/docs" style="color: var(--accent-blue); text-decoration: none;">/docs</a></p>

        <table class="endpoints-table">
            <thead>
                <tr>
                    <th>Method</th>
                    <th>Endpoint</th>
                    <th>Description</th>
                </tr>
            </thead>
            <tbody>
                <tr><td><span class="method-badge method-post">POST</span></td><td class="endpoint-path">/api/auth/register</td><td>Create a new user account</td></tr>
                <tr><td><span class="method-badge method-post">POST</span></td><td class="endpoint-path">/api/auth/login</td><td>Login and receive JWT bearer token</td></tr>
                <tr><td><span class="method-badge method-get">GET</span></td><td class="endpoint-path">/api/agents/</td><td>List all compiled agents for current user</td></tr>
                <tr><td><span class="method-badge method-post">POST</span></td><td class="endpoint-path">/api/agents/</td><td>Create a new agent</td></tr>
                <tr><td><span class="method-badge method-post">POST</span></td><td class="endpoint-path">/api/compile/</td><td>Start knowledge compilation from uploaded files</td></tr>
                <tr><td><span class="method-badge method-get">GET</span></td><td class="endpoint-path">/api/compile/{job_id}</td><td>Poll compilation job status + progress</td></tr>
                <tr><td><span class="method-badge method-post">POST</span></td><td class="endpoint-path">/api/chat/</td><td>Send a query to an agent (REST)</td></tr>
                <tr><td><span class="method-badge method-ws">WS</span></td><td class="endpoint-path">/ws/chat/{agent_id}</td><td>Real-time streaming chat via WebSocket</td></tr>
                <tr><td><span class="method-badge method-get">GET</span></td><td class="endpoint-path">/api/health</td><td>Health check β€” returns API + Groq status</td></tr>
            </tbody>
        </table>
    </section>

    <div class="divider"></div>

    <!-- GROQ FALLBACK -->
    <section class="section">
        <div class="section-label">Reliability</div>
        <h2 class="section-title">Multi-Model Fallback Chain</h2>
        <p class="section-subtitle">Automatic failover across Groq models when rate limits are hit β€” zero downtime.</p>

        <div class="fallback-chain">
            <div class="fallback-item">
                <span class="model-chip primary">openai/gpt-oss-120b</span>
                <span class="arrow-down">β†’ quota β†’</span>
            </div>
            <div class="fallback-item">
                <span class="model-chip">llama-3.3-70b-versatile</span>
                <span class="arrow-down">β†’ quota β†’</span>
            </div>
            <div class="fallback-item">
                <span class="model-chip">llama-3.1-8b-instant</span>
                <span class="arrow-down">β†’ quota β†’</span>
            </div>
            <div class="fallback-item">
                <span class="model-chip">mixtral-8x7b-32768</span>
                <span class="arrow-down">β†’ quota β†’</span>
            </div>
            <div class="fallback-item">
                <span class="model-chip">gemma2-9b-it</span>
            </div>
        </div>
    </section>

    <div class="divider"></div>

    <!-- QUICK START -->
    <section class="section">
        <div class="section-label">Getting Started</div>
        <h2 class="section-title">Quick Integration</h2>
        <p class="section-subtitle">Start querying your agent in three steps.</p>

        <div class="code-block">
<span class="comment"># 1. Register and login</span>
<span class="cmd">POST</span> /api/auth/register  { "email": "you@example.com", "password": "..." }
<span class="cmd">POST</span> /api/auth/login     β†’ <span class="val">{ "access_token": "eyJ..." }</span>

<span class="comment"># 2. Compile an agent from your documents</span>
<span class="cmd">POST</span> /api/compile/  <span class="key">Authorization:</span> Bearer {token}
     <span class="key">Files:</span> report.pdf, research.docx
     β†’ <span class="val">{ "job_id": 42, "status": "compiling" }</span>

<span class="comment"># 3. Chat with your agent</span>
<span class="cmd">POST</span> /api/chat/  <span class="key">Authorization:</span> Bearer {token}
     <span class="val">{ "agent_id": 36, "message": "What are the key findings?" }</span>
     β†’ <span class="val">{ "answer": "...[1][2]", "faithfulness": 0.87, "sources": [...] }</span>
        </div>
    </section>

    <!-- FOOTER -->
    <footer>
        <div>
            <span class="footer-brand">MEXAR Core Engine v2.0.0</span>
            <div style="font-size: 0.8rem; color: var(--text-muted); margin-top: 0.3rem;">
                Built with FastAPI Β· pgvector Β· Groq Β· DeBERTa-v3
            </div>
        </div>
        <div class="footer-links">
            <a href="/docs" class="footer-link">API Docs</a>
            <a href="/redoc" class="footer-link">ReDoc</a>
            <a href="https://mexar.vercel.app" class="footer-link" target="_blank">Frontend App</a>
            <a href="https://github.com/devrajsinh2012/Mexar" class="footer-link" target="_blank">GitHub</a>
        </div>
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</div>

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