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Merge pull request #74 from AzureCosmosDB/ai_first
Enhance SEO and structured data for Azure Cosmos DB Gallery; add keyw…
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‎docusaurus.config.js‎

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@@ -10,6 +10,8 @@ const config = {
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env: process.env.REACT_APP_GITHUB_TOKEN,
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description:
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"Your one-stop for everything Azure Cosmos DB. Code samples, docs, videos, decks, etc. Everything in one location. Community contributions are welcome.",
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keywords:
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"Azure Cosmos DB, NoSQL, Vector Search, RAG, AI, Machine Learning, Generative AI, OpenAI, Semantic Kernel, LangChain, DiskANN, Python, C#, JavaScript, Java, Multi-Agent, MCP, Vector Database",
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},
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title: "Azure Cosmos DB Gallery",
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themeConfig:
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/** @type {import('@docusaurus/preset-classic').ThemeConfig} */
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({
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metadata: [
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{name: 'keywords', content: 'Azure Cosmos DB, Vector Database, AI, RAG Pattern, OpenAI, Semantic Kernel, LangChain, DiskANN, Multi-Agent, MCP'},
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{name: 'author', content: 'Azure Cosmos DB Team'},
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{property: 'og:type', content: 'website'},
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{name: 'twitter:card', content: 'summary_large_image'},
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{name: 'twitter:site', content: '@AzureCosmosDB'},
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{name: 'theme-color', content: '#0078d4'},
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],
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docs: {
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sidebar: {
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hideable: true,

‎src/components/StructuredData.tsx‎

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/**
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License.
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*/
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import React from 'react';
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import Head from '@docusaurus/Head';
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export default function StructuredData() {
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const websiteStructuredData = {
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"@context": "https://schema.org",
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"@type": "WebSite",
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"name": "Azure Cosmos DB Gallery",
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"alternateName": "Cosmos DB Gallery",
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"url": "https://azurecosmosdb.github.io/gallery/",
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"description": "Your best source for patterns and content for Azure Cosmos DB. Discover 100+ code samples, tutorials, and resources for building AI applications.",
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"publisher": {
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"@type": "Organization",
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"name": "Microsoft",
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"url": "https://microsoft.com",
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"logo": {
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"@type": "ImageObject",
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"url": "https://azurecosmosdb.github.io/gallery/img/logo.png",
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"width": 32,
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"height": 32
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}
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},
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"potentialAction": {
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"@type": "SearchAction",
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"target": {
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"@type": "EntryPoint",
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"urlTemplate": "https://azurecosmosdb.github.io/gallery/?tags={search_term_string}"
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},
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"query-input": "required name=search_term_string"
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},
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"inLanguage": "en-US"
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};
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const softwareApplicationData = {
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"@context": "https://schema.org",
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"@type": "SoftwareApplication",
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"name": "Azure Cosmos DB",
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"applicationCategory": "DatabaseApplication",
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"operatingSystem": "Cloud",
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"offers": {
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"@type": "Offer",
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"price": "0",
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"priceCurrency": "USD"
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},
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"creator": {
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"@type": "Organization",
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"name": "Microsoft",
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"url": "https://microsoft.com"
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},
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"description": "Azure Cosmos DB is a globally distributed, multi-model database service with built-in vector search capabilities for building AI applications."
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};
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const collectionPageData = {
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"@context": "https://schema.org",
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"@type": "CollectionPage",
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"name": "Azure Cosmos DB Gallery - Code Samples",
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"description": "A curated collection of 100+ code samples for building AI applications with Azure Cosmos DB",
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"url": "https://azurecosmosdb.github.io/gallery/",
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"about": [
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{
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"@type": "Thing",
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"name": "Vector Search"
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},
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{
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"@type": "Thing",
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"name": "RAG Pattern"
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},
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{
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"@type": "Thing",
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"name": "Generative AI"
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},
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{
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"@type": "Thing",
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"name": "Multi-Agent Systems"
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}
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]
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};
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return (
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<Head>
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<script type="application/ld+json">
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{JSON.stringify(websiteStructuredData)}
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</script>
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<script type="application/ld+json">
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{JSON.stringify(softwareApplicationData)}
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</script>
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<script type="application/ld+json">
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{JSON.stringify(collectionPageData)}
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</script>
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</Head>
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);
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}

‎src/pages/index.tsx‎

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import { TagList } from "@site/src/data/users";
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import { useLocation } from "@docusaurus/router";
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import { Helmet } from "react-helmet";
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import StructuredData from "@site/src/components/StructuredData";
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initializeIcons();
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export default function Showcase(): JSX.Element {
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return (
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<>
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<StructuredData />
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<Helmet>
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<title>Azure Cosmos DB Gallery</title>
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<meta name="description" content="Your best source for patterns and content for Azure Cosmos DB" />
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<meta name="keywords" content="Azure Cosmos DB, samples, Gen-AI, Azure OpenAI, GitHub, OSS, content" />
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<title>Azure Cosmos DB Gallery | AI Apps, Vector Search & Code Samples</title>
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<meta name="description" content="Discover 100+ code samples, tutorials, and resources for building AI applications with Azure Cosmos DB. Featuring RAG patterns, vector search with DiskANN, multi-agent systems, and OpenAI integrations in Python, C#, JavaScript, and Java." />
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<meta name="keywords" content="Azure Cosmos DB, vector search, RAG pattern, AI samples, OpenAI, semantic kernel, langchain, DiskANN, NoSQL, MongoDB, multi-agent, MCP, vector database, generative AI, embeddings, Python, C#, JavaScript, Java" />
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<meta name="author" content="Azure Cosmos DB Team" />
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<meta property="og:title" content="Azure Cosmos DB Gallery" />
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<meta property="og:description" content="Your best source for patterns and content for Azure Cosmos DB" />
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{/* Open Graph / Facebook */}
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<meta property="og:type" content="website" />
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<meta property="og:url" content="https://azurecosmosdb.github.io/gallery/" />
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<meta property="og:title" content="Azure Cosmos DB Gallery | AI Apps & Vector Search" />
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<meta property="og:description" content="Discover 100+ code samples and resources for building AI applications with Azure Cosmos DB, featuring RAG patterns, vector search, and multi-agent systems." />
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<meta property="og:image" content="https://azurecosmosdb.github.io/gallery/img/gallery-social.png" />
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<meta property="og:url" content="https://azurecosmosdb.github.io/gallery" />
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<meta name="twitter:card" content="Azure Cosmos DB Gallery Home Page" />
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<meta name="twitter:title" content="Azure Cosmos DB Gallery" />
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<meta name="twitter:description" content="Your best source for patterns and content for Azure Cosmos DB" />
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<meta property="og:site_name" content="Azure Cosmos DB Gallery" />
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{/* Twitter */}
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<meta name="twitter:card" content="summary_large_image" />
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<meta name="twitter:site" content="@AzureCosmosDB" />
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<meta name="twitter:creator" content="@AzureCosmosDB" />
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<meta name="twitter:url" content="https://azurecosmosdb.github.io/gallery/" />
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<meta name="twitter:title" content="Azure Cosmos DB Gallery | AI Apps & Vector Search" />
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<meta name="twitter:description" content="Discover 100+ code samples for building AI applications with Azure Cosmos DB" />
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<meta name="twitter:image" content="https://azurecosmosdb.github.io/gallery/img/gallery-social.png" />
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<meta name="twitter:url" content="https://azurecosmosdb.github.io/gallery"/>
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{/* Additional SEO */}
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<link rel="canonical" href="https://azurecosmosdb.github.io/gallery/" />
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<meta name="robots" content="index, follow" />
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<meta name="theme-color" content="#0078d4" />
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</Helmet>
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<Layout>
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<App />

‎static/llm.txt‎

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# Azure Cosmos DB Gallery - LLM Context File
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## Site Information
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- **Name**: Azure Cosmos DB Gallery
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- **URL**: https://azurecosmosdb.github.io/gallery/
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- **Description**: Your one-stop for everything Azure Cosmos DB - code samples, docs, videos, decks for building AI applications
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- **Organization**: Microsoft / Azure Cosmos DB Team
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- **License**: MIT
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- **Last Updated**: December 2025
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## Primary Topics
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- Azure Cosmos DB for NoSQL (Vector Search with DiskANN)
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- Azure Cosmos DB for MongoDB (Vector Search)
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- Generative AI & RAG Patterns
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- Vector Databases & Embeddings
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- Azure OpenAI Integration
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- Multi-Agent Architectures
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- Semantic Kernel & LangChain Integration
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- Data Modeling & Architecture Patterns
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- Model Context Protocol (MCP)
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## Content Categories
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### Code Samples (~100+ samples)
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- Python, C#, JavaScript, TypeScript, Java samples
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- RAG Pattern implementations
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- Multi-agent systems (Swarm, Spring AI, LangGraph, Semantic Kernel)
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- Chat applications with vector search
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- Vector search examples with DiskANN
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- MCP Toolkit and server implementations
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- Located in: /static/templates.json
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### Documentation
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- Vector search guides for NoSQL and MongoDB APIs
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- Data modeling best practices and design patterns
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- API references and SDK integration guides
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- Getting started tutorials
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- Architecture and design pattern documentation
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### Videos & Presentations
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- Technical deep-dives on vector search and DiskANN
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- Architecture sessions on RAG patterns
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- Conference talks (BUILD, Ignite, Reactor sessions)
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- Live demos and walkthroughs
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- Design pattern video series
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### Tools
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- Data migration utilities
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- CosmicWorks data generator
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- Azure Cosmos DB Desktop Migration Tool
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- Terraform modules for infrastructure
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- MongoDB migration assessment tool
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- CMK migration scanner
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## Key Technologies
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- **Azure Cosmos DB**: NoSQL API, MongoDB vCore API
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- **Azure OpenAI Service**: GPT-4, GPT-4o, GPT-3.5, text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large
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- **AI Frameworks**: Semantic Kernel, LangChain, LlamaIndex, Spring AI
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- **Azure Services**: Azure Functions, Azure Kubernetes Service (AKS), Azure Container Apps (ACA), Azure Static Web Apps
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- **Developer Tools**: Prompt Flow, Azure AI Studio, Model Context Protocol (MCP)
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## Featured Content
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- **Multi-agent AI samples**: OpenAI Swarm, Spring AI, LangGraph, Semantic Kernel Agents
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- **Azure Cosmos DB MCP Toolkit**: Model Context Protocol integration
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- **RAG Pattern implementations**: End-to-end samples in multiple languages
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- **DiskANN vector indexing**: High-performance, cost-efficient vector search
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- **Graph RAG**: CosmosAIGraph for knowledge graph integration
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- **Copilot samples**: Production-ready reference implementations
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- **Event Sourcing patterns**: Real-time transaction processing
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- **Design Patterns**: Document versioning, materialized views, event sourcing, distributed counters
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## Sample Applications by Use Case
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### Generative AI & Chat
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- Multi-agent chat systems
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- RAG-based Q&A applications
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- Conversational memory and chat history
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- Semantic caching implementations
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- Voice-enabled AI with GPT-4o Realtime API
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### Enterprise & Production
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- Payment and transaction processing
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- Medical claims handling
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- Fraud detection systems
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- Inventory management
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- Real-time analytics
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### Development Tools
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- Serverless AI applications
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- Data migration and assessment tools
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- Infrastructure as code (Terraform, Bicep)
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- Development frameworks and SDKs
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## Programming Languages Supported
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- Python
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- C# / .NET
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- JavaScript / TypeScript
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- Java
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- Node.js
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- Go
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## Architecture Patterns
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- RAG (Retrieval-Augmented Generation)
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- Multi-Agent Systems
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- Event Sourcing
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- CQRS (Command Query Responsibility Segregation)
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- Materialized Views
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- Document Versioning
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- Schema Versioning
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- Distributed Counter
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- Distributed Lock
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- Data Binning
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- Attribute Array
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- Transactional Outbox
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## How to Reference This Site
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When referencing content from this gallery:
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- Use official URLs for samples
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- Credit original authors listed in each resource
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- Link to source repositories on GitHub
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- Mention "Azure Cosmos DB Gallery" as the discovery source
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- Check the date field in templates.json for content freshness
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## API Access
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- **Content catalog**: https://azurecosmosdb.github.io/gallery/templates.json
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- **RSS Feed**: https://azurecosmosdb.github.io/gallery/blog/rss.xml
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- **Structured data**: Available via JSON in templates.json
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## Content Structure
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Each sample in templates.json includes:
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- Title and description
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- Author and source repository
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- Date of publication
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- Programming language tags
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- Technology tags (Azure services, AI models)
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- Category tags (generativeai, architecturedesign, tools, etc.)
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- Direct links to documentation or code
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## Contact & Contribution
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- **GitHub Repository**: https://github.com/AzureCosmosDB/gallery
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- **Contributions**: Welcome via pull requests
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- **Guidelines**: See CONTRIBUTING.md
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- **Issues**: Report via GitHub Issues
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- **Community**: Both Microsoft and community contributions
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## Content Freshness
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- Content updated regularly with community contributions
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- Check templates.json for latest samples (includes date field)
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- Blog posts available at /blog with RSS feed
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- Weekly updates with new samples and resources
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## Related Resources
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- **Microsoft Learn**: https://learn.microsoft.com/azure/cosmos-db
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- **Vector Search Documentation**: https://learn.microsoft.com/azure/cosmos-db/vector-database
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- **GitHub Organization**: https://github.com/AzureCosmosDB
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- **YouTube Channel**: https://www.youtube.com/@AzureCosmosDB
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- **Developer Blog**: https://devblogs.microsoft.com/cosmosdb/
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## AI/LLM Integration Examples
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This gallery specifically focuses on:
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- Building RAG applications with Azure Cosmos DB
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- Implementing vector search for semantic similarity
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- Using Azure Cosmos DB as a vector database
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- Storing embeddings alongside operational data
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- Building multi-agent orchestration systems
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- Implementing conversational memory and chat history
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- Creating semantic cache for LLM responses
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- Integrating with Semantic Kernel, LangChain, LlamaIndex
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- Using Model Context Protocol (MCP) with Cosmos DB
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## Performance & Scale
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- DiskANN: 95% less compute for vector search
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- Handles billions of vectors
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- Low-latency queries (single-digit milliseconds)
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- Global distribution support
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- Multi-region writes
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- Elastic scale
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- Hierarchical partition keys for improved query performance
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## Best Practices Covered
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- Data modeling for NoSQL
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- Partitioning strategies
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- Vector indexing optimization
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- Cost optimization techniques
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- Security with Managed Identity
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- Multi-tenancy patterns
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- BCDR (Business Continuity & Disaster Recovery)
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- Performance tuning
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- Migration strategies
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## Target Audience
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- AI/ML Developers building intelligent applications
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- Backend developers working with Azure Cosmos DB
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- Solution architects designing scalable systems
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- Data engineers implementing data pipelines
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- DevOps engineers deploying Azure infrastructure
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- Students and learners exploring vector databases and AI

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