chore: ignore interactive diagram sources
Keep diagram source files local while publishing the static PDF.\n\nCo-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
@gabriel.pereira
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.gitignore
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@@ -3,3 +3,4 @@ case_study.css
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case_study_one_page.html
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case_study_one_page.html
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case_study_one_page.md
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case_study_one_page.md
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architecture_dag.md
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architecture_dag.md
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architecture_diagram.html
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@@ -1,59 +0,0 @@
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# Quotation Semantic Layer - Data Flow DAG
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# SAP Source -> Snowflake -> dbt Transforms -> Semantic Views -> Cortex -> Chatbot Output
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graph LR
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SAP["🗄️ SAP ERP System<br/>(Sales & Discount Data)"]
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EXT["📥 Snowflake<br/>External Stage"]
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RAW["raw.quotations<br/>raw.discount_conditions"]
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STG["STAGING Layer<br/>stg_quotes<br/>stg_discount_conditions<br/>stg_product_master"]
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TRF["TRANSFORM Layer<br/>trf_quotation<br/>trf_chatbot_quotation"]
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DIM["Reference Dimensions<br/>dim_customer_discount_policy<br/>dim_product_portfolio<br/>fct_agreement_discounts"]
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SEMA["SEMANTIC LAYER<br/>sv_quotation<br/>sv_chatbot_quotation"]
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CORTEX["Cortex Analytics<br/>Guardrails & Information Protection<br/>Access Control<br/>Freshness Contract"]
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UI["Snowflake UI<br/>(BI Dashboard)"]
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CHAT["🤖 Internal Workspace<br/>(Chatbot)"]
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SAP -->|Daily Batch 05:00 UTC| EXT
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EXT -->|Load| RAW
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RAW -->|Column mapping<br/>Type casting| STG
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STG -->|Join dimensions<br/>Calculate discounts<br/>Apply governance flags| TRF
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DIM -->|Enrich with policies| TRF
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TRF -->|Expose semantic<br/>business logic<br/>Hide implementation| SEMA
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SEMA -->|Apply guardrails<br/>Protect sensitive information<br/>Enforce freshness| CORTEX
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CORTEX -->|Query & Visualize| UI
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CORTEX -->|LLM consumption<br/>Prompt engineering layer| CHAT
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CHAT -->|<1 min<br/>Quote Answers| USER["👤 Sales & Ops<br/>Team"]
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UI -->|Dashboard<br/>Reporting| OPS["📊 Operations<br/>Team"]
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SEMA -.->|Data Contract<br/>Lineage| AUDIT["🔒 Audit & Compliance<br/>- Access logs<br/>- Policy changes<br/>- Exception escalations"]
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style SAP fill:#d4a574
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style CORTEX fill:#ff9999
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style SEMA fill:#99ccff
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style CHAT fill:#99ff99
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style USER fill:#ffcc99
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style AUDIT fill:#cc99ff
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classDef layer_raw fill:#e1e4e8
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classDef layer_stg fill:#d0d7de
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classDef layer_trf fill:#adb8c1
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classDef layer_sema fill:#6e7681
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class RAW layer_raw
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class STG layer_stg
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class TRF layer_trf
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class SEMA layer_sema
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@@ -1,331 +0,0 @@
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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<title>Talk-to-Data: Architecture Animated Diagram</title>
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<script src="https://cdn.jsdelivr.net/npm/mermaid@10/dist/mermaid.min.js"></script>
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<style>
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body {
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
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margin: 0;
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padding: 20px;
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background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
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min-height: 100vh;
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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background: white;
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border-radius: 8px;
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box-shadow: 0 4px 6px rgba(0,0,0,0.1);
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padding: 30px;
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}
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h1 {
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color: #2c3e50;
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text-align: center;
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margin-bottom: 10px;
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font-size: 28px;
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}
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.subtitle {
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text-align: center;
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color: #7f8c8d;
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margin-bottom: 30px;
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font-size: 14px;
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}
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.diagram-wrapper {
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margin: 30px 0;
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padding: 28px;
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background: #f8f9fa;
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border-radius: 6px;
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border-left: 4px solid #3498db;
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overflow-x: auto;
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}
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.mermaid {
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display: flex;
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justify-content: center;
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min-width: 760px;
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}
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.mermaid svg {
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width: 100%;
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max-width: 920px;
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height: auto;
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overflow: hidden;
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}
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.mermaid .nodeLabel,
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.mermaid .edgeLabel {
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font-size: 16px !important;
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}
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.mermaid .edgeLabel {
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background: transparent !important;
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padding: 2px 4px;
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}
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.mermaid .edgeLabel:has(span:empty) {
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display: none;
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}
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.legend {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
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gap: 15px;
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margin-top: 30px;
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padding-top: 20px;
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border-top: 1px solid #ecf0f1;
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}
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.legend-item {
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display: flex;
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align-items: center;
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font-size: 13px;
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}
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.legend-color {
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width: 20px;
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height: 20px;
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border-radius: 3px;
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margin-right: 10px;
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flex-shrink: 0;
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}
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.section {
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margin-top: 40px;
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padding: 20px;
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background: #ecf0f1;
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border-radius: 6px;
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}
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.section h2 {
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color: #2c3e50;
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margin-top: 0;
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font-size: 18px;
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border-bottom: 2px solid #3498db;
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padding-bottom: 10px;
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}
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.section p {
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color: #555;
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line-height: 1.6;
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margin: 10px 0;
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}
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.flow-step {
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display: flex;
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align-items: center;
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margin: 15px 0;
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padding: 10px;
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background: white;
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border-radius: 4px;
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}
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.flow-step span {
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display: inline-block;
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width: 110px;
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min-width: 110px;
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flex-shrink: 0;
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font-weight: bold;
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color: #3498db;
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}
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.flow-step p {
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flex: 1;
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min-width: 0;
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}
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code {
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background: #f4f4f4;
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padding: 2px 6px;
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border-radius: 3px;
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font-size: 12px;
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}
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@keyframes flow {
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0% { opacity: 0.3; }
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50% { opacity: 1; }
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100% { opacity: 0.3; }
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}
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.animate-flow {
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animation: flow 2s ease-in-out infinite;
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}
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@media print {
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@page {
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size: A4 portrait;
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margin: 12mm;
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}
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body {
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padding: 0;
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background: white;
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}
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.container {
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max-width: none;
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padding: 0;
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box-shadow: none;
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}
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h1 {
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font-size: 22px;
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margin: 0 0 4px;
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}
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.subtitle {
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margin: 0 0 12px;
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font-size: 11px;
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}
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.diagram-wrapper {
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margin: 0;
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padding: 8px;
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border-left-width: 3px;
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break-inside: avoid;
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}
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.mermaid {
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min-width: 0;
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}
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.mermaid svg {
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||||||
width: auto;
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max-width: 100%;
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max-height: 185mm;
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}
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.legend {
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grid-template-columns: repeat(4, 1fr);
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gap: 6px;
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margin-top: 10px;
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padding-top: 8px;
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font-size: 9px;
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break-inside: avoid;
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}
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.legend-item {
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font-size: 9px;
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}
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.legend-color {
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width: 12px;
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height: 12px;
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margin-right: 5px;
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}
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.section {
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display: none;
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}
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}
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</style>
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</head>
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<body>
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<div class="container">
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<h1>Talk-to-Data: Semantic Analytics Architecture</h1>
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<p class="subtitle">SAP → Snowflake → dbt → Cortex → Chatbot | <1 minute quote answers</p>
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<div class="diagram-wrapper">
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<div class="mermaid">
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graph TD
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SAP["SAP ERP<br/>Quotes and discounts<br/>Daily batch"]
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RAW["Snowflake raw data"]
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STG["dbt staging<br/>Clean and standardize"]
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TRF["dbt transforms<br/>Business rules and flags"]
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SEMA["Semantic views<br/>Business terms and lineage"]
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CORTEX["Cortex Analytics<br/>Guardrails and audit"]
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UI["Snowflake UI<br/>Dashboards"]
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CHAT["Internal workspace<br/>Chatbot"]
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USER["Sales and operations<br/>30+ users<br/><1 min estimated answer"]
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AUDIT["Audit trail<br/>Access and exceptions"]
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SAP --> RAW
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RAW --> STG
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STG --> TRF
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TRF --> SEMA
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SEMA --> CORTEX
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CORTEX --> UI
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CORTEX --> CHAT
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UI --> USER
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CHAT --> USER
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SEMA -.-> AUDIT
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style SAP fill:#d4a574,stroke:#333,stroke-width:2px,color:#fff
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style CORTEX fill:#ff9999,stroke:#c0392b,stroke-width:2px,color:#fff
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style SEMA fill:#99ccff,stroke:#2980b9,stroke-width:2px,color:#fff
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style CHAT fill:#99ff99,stroke:#27ae60,stroke-width:2px,color:#000
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style USER fill:#ffcc99,stroke:#e67e22,stroke-width:2px,color:#000
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style AUDIT fill:#cc99ff,stroke:#8e44ad,stroke-width:2px,color:#fff
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style RAW fill:#e1e4e8,stroke:#666,stroke-width:1px
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style STG fill:#d0d7de,stroke:#666,stroke-width:1px
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style TRF fill:#adb8c1,stroke:#666,stroke-width:1px
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style RAW fill:#e1e4e8,stroke:#666,stroke-width:1px
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</div>
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</div>
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<div class="legend">
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<div class="legend-item">
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<div class="legend-color" style="background: #d4a574;"></div>
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<span><strong>SAP Source:</strong> Daily batch extract</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #e1e4e8;"></div>
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<span><strong>Raw:</strong> Unmodified data</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #d0d7de;"></div>
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<span><strong>Staging:</strong> Data preparation</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #adb8c1;"></div>
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<span><strong>Transform:</strong> Business logic</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #99ccff;"></div>
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<span><strong>Semantic:</strong> Data contract</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #ff9999;"></div>
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<span><strong>Cortex:</strong> AI guardrails</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #99ff99;"></div>
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<span><strong>Chatbot:</strong> User interface</span>
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</div>
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<div class="legend-item">
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<div class="legend-color" style="background: #cc99ff;"></div>
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<span><strong>Audit:</strong> Compliance trail</span>
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</div>
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</div>
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<div class="section">
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<h2>Data Flow Stages</h2>
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<div class="flow-step">
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<span>1. Source</span>
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<p>SAP ERP systems extract quotation, discount, and customer data daily at 05:00 UTC. Data includes quotation identifiers, line items, pricing, and discount conditions.</p>
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</div>
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<div class="flow-step">
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<span>2. Raw</span>
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<p>Snowflake External Stage ingests CSV/Parquet. Raw schema preserves source structure without modification. Data quality checks validate row counts, null patterns.</p>
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</div>
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<div class="flow-step">
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<span>3. Staging</span>
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<p><code>stg_*</code> models rename columns, cast data types, and handle nulls. Example: source quotation ID → <code>quote_id</code>, source amount → <code>net_value</code>. No business logic yet.</p>
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</div>
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<div class="flow-step">
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<span>4. Transform</span>
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<p><code>trf_quotation</code> joins customer policies, product portfolios, and agreement discounts. Calculates discount totals, applies governance flags (e.g., <code>discount_above_ceiling</code>). Two models: <code>trf_quotation</code> (BI) and <code>trf_chatbot_quotation</code> (LLM-optimized).</p>
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</div>
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<div class="flow-step">
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<span>5. Semantic</span>
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<p>Snowflake DDL semantic views expose curated dimensions and facts. Includes synonyms for natural language (e.g., "desconto cliente" → <code>discount_customer_pct</code>). Single source of truth for BI dashboards and LLM queries.</p>
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</div>
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<div class="flow-step">
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<span>6. Cortex</span>
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||||||
<p><a href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst" target="_blank" rel="noopener noreferrer">Cortex Analyst</a> applies guardrails: hides raw discount percentages, protects customer names, checks data freshness, enforces role-based access, and logs all access. LLM queries go through here.</p>
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</div>
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<div class="flow-step">
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<span>7. Consume</span>
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|
||||||
<p><strong>Snowflake UI:</strong> Dashboards for ops/sales teams (full data visibility). <strong>Internal Workspace:</strong> Chatbot interface (guardrail-filtered data). Both consume the same semantic layer; governance rules ensure consistency.</p>
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</div>
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</div>
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<div class="section">
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<h2>Why This Architecture?</h2>
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<p><strong>Governance-first:</strong> Guardrails (discount policies, protection of personal and customer information, and audit logs) are embedded in the data layer, not bolted on to the LLM prompt. The bot can't bypass policy; it's enforced by Cortex + dbt.</p>
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<p><strong>Semantic contract:</strong> The semantic layer (sv_quotation, sv_chatbot_quotation) defines the agreement between data engineers, BI teams, and LLM consumers. Column definitions, synonyms, and access rules are version-controlled.</p>
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<p><strong>Team efficiency:</strong> dbt lineage shows how every dimension flows from SAP → semantic layer. Data engineers and business analysts can trace a discount calculation back to SAP in seconds. Onboarding takes days, not weeks.</p>
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<p><strong>Prototyping speed:</strong> Snowflake + Cortex means we didn't build custom infrastructure. POC shipped in weeks. Cortex guardrails were ready on day 1; no custom policy engine to build.</p>
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</div>
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<div class="section">
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||||||
<h2>Expected Outcomes</h2>
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||||||
<p><strong>Latency:</strong> Quote research from 5-30 minutes (email + manual lookup) → <1 minute (chatbot query)</p>
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|
||||||
<p><strong>Scalability:</strong> 30+ salespeople can query the chatbot concurrently. Snowflake handles scale; dbt models are stateless (scale linearly).</p>
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|
||||||
<p><strong>Governance:</strong> All discount exceptions flagged and audited. Policy violations are visible and traceable.</p>
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|
||||||
<p><strong>Team capability:</strong> Once-daily batch + semantic layer pattern is reusable. Next use cases (contracts, pricing, serviceability) ship faster by leveraging the same playbook.</p>
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</div>
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<div class="section">
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|
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<h2>Learn More</h2>
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<p>
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|
||||||
See <code>README.md</code> for full narrative, decisions, and lessons learned.
|
|
||||||
Check <code>dbt/</code> for anonymized SQL models.
|
|
||||||
Review <code>cortex/cortex_governance_config.yaml</code> for guardrails and access control.
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</p>
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</div>
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</div>
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</body>
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</html>
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Reference in New Issue
Block a user