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348 lines
11 KiB
HTML
348 lines
11 KiB
HTML
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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Prompt Tuning⚙️</title>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bulma@0.9.4/css/bulma.min.css">
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<link href="https://unpkg.com/prismjs@1.20.0/themes/prism-okaidia.css" rel="stylesheet">
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<style>
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html {
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justify-content: center;
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padding: 0;
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margin: 0;
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header {
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background-color: lightgrey;
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padding: 10px;
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nav {
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padding: 1em;
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min-width: 200px;
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main {
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flex: 1;
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padding: 0 5em 0 5em;
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h1 {
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margin-top: 10px;
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/* Accessibility styling */
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a {
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color: #485fc7;
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text-decoration: underline;
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text-decoration: none;
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.token.comment, .token.prolog, .token.doctype, .token.cdata {
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color: #8093a5;
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color: #ff36ab;
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</style>
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<script>
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function onConsentChanged(categoryPreferences) {
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console.log("onConsentChanged", categoryPreferences);
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var siteConsent
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function initialize(){
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var currentYear = new Date().getFullYear()
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document.getElementById("copyright").innerHTML = `©️ ${currentYear} Microsoft`;
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window.WcpConsent && WcpConsent.init("en-US", "cookie-banner", function (err, _siteConsent) {
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siteConsent = _siteConsent; //siteConsent is used to get the current consent
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} else {
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console.log("Error initializing WcpConsent: "+ err);
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}, onConsentChanged, WcpConsent.themes.light);
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addEventListener("DOMContentLoaded", initialize)
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addEventListener("DOMContentLoaded", checkCookieManager)
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function checkCookieManager(){
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document.getElementById("cookiesManager").style.display = 'block';
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else{
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document.getElementById("divider").style.display = 'none';
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function manageConsent() {
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if(siteConsent.isConsentRequired){
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siteConsent.manageConsent();
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}
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</script>
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</head>
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<body>
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<header>
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<div id="cookie-banner"></div>
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<a href="/"><span class="logotitle">GraphRAG</span></a>
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</header>
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<div class="page-content">
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<!-- Sidebar -->
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<aside class="menu">
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<ul class="menu-list">
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<li>
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<a href="/">Welcome</a>
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</li>
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<!-- Get Started Links -->
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<li>
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<a href="/posts/get_started/">Get Started</a>
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<a href="/posts/developing/">Developing</a>
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</li>
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<!-- Indexing Links -->
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<li>
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<a href="/posts/index/overview/">Indexing</a>
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<ul><li>
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<a href="/posts/index/0-architecture/">Architecture</a>
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</li><li>
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<a href="/posts/index/1-default_dataflow/">Dataflow</a>
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</li><li>
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<a href="/posts/index/2-cli/">CLI</a>
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</li><li>
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<a href="/posts/config/overview/">Configuration</a>
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<ul>
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<li>
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<a href="/posts/config/env_vars">Using Env Vars</a>
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</li>
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<li>
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<a href="/posts/config/json_yaml">Using JSON or YAML</a>
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</li>
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<li>
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<a href="/posts/config/custom">Fully Custom</a>
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</li>
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<li>
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<a href="/posts/config/template">Template</a>
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</li>
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</ul>
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</li>
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<li>
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<a href="/posts/prompt_tuning/overview/">Prompt Tuning</a>
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<ul>
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<li>
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<a href="/posts/prompt_tuning/auto_prompt_tuning/">Automatic Templating</a>
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</li>
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<li>
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<a href="/posts/prompt_tuning/manual_prompt_tuning/" class="is-active" aria-current="page">Manual Prompt Tuning</a>
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</li>
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</ul>
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</li>
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</ul>
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</li>
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<!-- Query Links -->
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<li>
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<a href="/posts/query/overview/">Query</a>
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<ul><li>
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<a href="/posts/query/1-local_search/">Local Search</a>
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</li><li>
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<a href="/posts/query/2-question_generation/">Question Generation</a>
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</li><li>
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<a href="/posts/query/0-global_search/">Global Search</a>
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</li><li>
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<a href="/posts/query/3-cli/">CLI</a>
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</li><li>
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<a href="/posts/query/notebooks/overview/">Notebooks</a>
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<ul>
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<li>
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<a href="/posts/query/notebooks/global_search_nb">Global Search</a>
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</li>
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<li>
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<a href="/posts/query/notebooks/local_search_nb">Local Search</a>
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</li>
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</ul>
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</li>
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</ul>
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</li>
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</ul>
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</aside>
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<!-- Main Content -->
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<main>
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<h1>Prompt Tuning⚙️</h1>
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<p>The GraphRAG indexer, by default, will run with a handful of prompts that are designed to work well in the broad context of knowledge discovery.
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However, it is quite common to want to tune the prompts to better suit your specific use case.
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We provide a means for you to do this by allowing you to specify a custom prompt file, which will each use a series of token-replacements internally.</p>
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<p>Each of these prompts may be overridden by writing a custom prompt file in plaintext. We use token-replacements in the form of <code>{token_name}</code>, and the descriptions for the available tokens can be found below.</p>
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<h2>Entity/Relationship Extraction</h2>
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<p><a href="http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/graph/prompts.py">Prompt Source</a></p>
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<h3>Tokens (values provided by extractor)</h3>
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<ul>
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<li><strong>{input_text}</strong> - The input text to be processed.</li>
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<li><strong>{entity_types}</strong> - A list of entity types</li>
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<li><strong>{tuple_delimiter}</strong> - A delimiter for separating values within a tuple. A single tuple is used to represent an individual entity or relationship.</li>
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<li><strong>{record_delimiter}</strong> - A delimiter for separating tuple instances.</li>
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<li><strong>{completion_delimiter}</strong> - An indicator for when generation is complete.</li>
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</ul>
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<h2>Summarize Entity/Relationship Descriptions</h2>
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<p><a href="http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/summarize/prompts.py">Prompt Source</a></p>
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<h3>Tokens (values provided by extractor)</h3>
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<ul>
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<li><strong>{entity_name}</strong> - The name of the entity or the source/target pair of the relationship.</li>
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<li><strong>{description_list}</strong> - A list of descriptions for the entity or relationship.</li>
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</ul>
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<h2>Claim Extraction</h2>
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<p><a href="http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/claims/prompts.py">Prompt Source</a></p>
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<h3>Tokens (values provided by extractor)</h3>
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<ul>
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<li><strong>{input_text}</strong> - The input text to be processed.</li>
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<li><strong>{tuple_delimiter}</strong> - A delimiter for separating values within a tuple. A single tuple is used to represent an individual entity or relationship.</li>
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<li><strong>{record_delimiter}</strong> - A delimiter for separating tuple instances.</li>
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<li><strong>{completion_delimiter}</strong> - An indicator for when generation is complete.</li>
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</ul>
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<p>Note: there is additional paramater for the <code>Claim Description</code> that is used in claim extraction.
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The default value is</p>
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<p><code>"Any claims or facts that could be relevant to information discovery."</code></p>
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<p>See the <a href="/posts/config/overview/">configuration documentation</a> for details on how to change this.</p>
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<h2>Generate Community Reports</h2>
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<p><a href="http://github.com/microsoft/graphrag/blob/main/graphrag/index/graph/extractors/community_reports/prompts.py">Prompt Source</a></p>
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<h3>Tokens (values provided by extractor)</h3>
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<ul>
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<li><strong>{input_text}</strong> - The input text to generate the report with. This will contain tables of entities and relationships.</li>
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</ul>
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</main>
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</div>
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<footer>
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<a href="https://go.microsoft.com/fwlink/?LinkId=521839">Privacy</a>
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<a href="https://go.microsoft.com/fwlink/?LinkId=2259814">Consumer Health Privacy</a>
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<span id="cookiesManager" onClick="manageConsent();">Cookies</span>
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<span id="divider">|</span>
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<a href="https://go.microsoft.com/fwlink/?LinkID=206977">Terms of Use</a>
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<a href="https://www.microsoft.com/trademarks">Trademarks</a>
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<a href="https://www.microsoft.com" id="copyright"></a>
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<a href="https://github.com/microsoft/graphrag">GitHub</a>
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</footer>
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</body>
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</html> |