mirror of
https://github.com/langflow-ai/langflow.git
synced 2026-07-24 04:13:36 +08:00
230 lines
52 KiB
HTML
230 lines
52 KiB
HTML
<!doctype html>
|
||
<html lang="en" dir="ltr" class="docs-wrapper plugin-docs plugin-id-default docs-version-current docs-doc-page docs-doc-id-Components/components-models" data-has-hydrated="false">
|
||
<head>
|
||
<meta charset="UTF-8">
|
||
<meta name="generator" content="Docusaurus v3.8.1">
|
||
<title data-rh="true">Language Model | Langflow Documentation</title><meta data-rh="true" name="viewport" content="width=device-width,initial-scale=1"><meta data-rh="true" name="twitter:card" content="summary_large_image"><meta data-rh="true" property="og:url" content="https://docs.langflow.org/components-models"><meta data-rh="true" property="og:locale" content="en"><meta data-rh="true" name="docusaurus_locale" content="en"><meta data-rh="true" name="docsearch:language" content="en"><meta data-rh="true" name="docusaurus_version" content="current"><meta data-rh="true" name="docusaurus_tag" content="docs-default-current"><meta data-rh="true" name="docsearch:version" content="current"><meta data-rh="true" name="docsearch:docusaurus_tag" content="docs-default-current"><meta data-rh="true" property="og:title" content="Language Model | Langflow Documentation"><meta data-rh="true" name="description" content="Language model components in Langflow generate text using a specified Large Language Model (LLM)."><meta data-rh="true" property="og:description" content="Language model components in Langflow generate text using a specified Large Language Model (LLM)."><link data-rh="true" rel="icon" href="/img/favicon.ico"><link data-rh="true" rel="canonical" href="https://docs.langflow.org/components-models"><link data-rh="true" rel="alternate" href="https://docs.langflow.org/components-models" hreflang="en"><link data-rh="true" rel="alternate" href="https://docs.langflow.org/components-models" hreflang="x-default"><link data-rh="true" rel="preconnect" href="https://UZK6BDPCVY-dsn.algolia.net" crossorigin="anonymous"><script data-rh="true" type="application/ld+json">{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Language Model","item":"https://docs.langflow.org/components-models"}]}</script><link rel="preconnect" href="https://www.google-analytics.com">
|
||
<link rel="preconnect" href="https://www.googletagmanager.com">
|
||
<script async src="https://www.googletagmanager.com/gtag/js?id=G-SLQFLQ3KPT"></script>
|
||
<script>function gtag(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],gtag("js",new Date),gtag("config","G-SLQFLQ3KPT",{})</script>
|
||
|
||
|
||
|
||
|
||
|
||
|
||
<link rel="search" type="application/opensearchdescription+xml" title="Langflow Documentation" href="/opensearch.xml">
|
||
|
||
|
||
|
||
<script>window._ibmAnalytics={settings:{name:"DataStax",tealiumProfileName:"ibm-subsidiary"},trustarc:{privacyPolicyLink:"https://ibm.com/privacy"},"digitalData.page.services.google.enabled":!0},window.digitalData={page:{pageInfo:{ibm:{siteId:"IBM_"+_ibmAnalytics.settings.name},segment:{enabled:!0,env:"prod",key:"B04fNhD06DqDPuaRfQl5lZ2iQICdxxuh",coremetrics:!1,carbonComponentEvents:!1}},category:{primaryCategory:"PC230"}},commonProperties:{productTitle:"IBM Elite Support for Langflow",productCode:"5900BUB",productCodeType:"WWPC",UT30:"30AS5",instanceId:"docs-site",subscriptionId:"public-access",productPlanName:"Public",productPlanType:"freemium",userId:"IBMid-ANONYMOUS"}}</script>
|
||
<script src="//1.www.s81c.com/common/stats/ibm-common.js" async="true"></script>
|
||
|
||
|
||
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Sora:wght@550;600&display=swap">
|
||
<script>function gtag(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],gtag("consent","default",{ad_storage:"denied",ad_user_data:"denied",ad_personalization:"denied",analytics_storage:"denied"})</script>
|
||
<script>!function(){function e(){if(void 0!==window.truste&&window.truste.cma){var e=window.truste.cma.callApi("getConsent",window.location.href)||{},n=1===e[2],t=1===e[3];gtag("consent","update",{ad_storage:n?"granted":"denied",ad_user_data:n?"granted":"denied",ad_personalization:n?"granted":"denied",analytics_storage:t?"granted":"denied"})}}window.addEventListener&&(window.addEventListener("cm_data_subject_consent_changed",e),window.addEventListener("cm_consent_preferences_set",e)),"complete"===document.readyState?e():window.addEventListener("load",e)}()</script><link rel="stylesheet" href="/assets/css/styles.5b49702d.css">
|
||
<script src="/assets/js/runtime~main.f495a36a.js" defer="defer"></script>
|
||
<script src="/assets/js/main.a09de144.js" defer="defer"></script>
|
||
</head>
|
||
<body class="navigation-with-keyboard">
|
||
<svg xmlns="http://www.w3.org/2000/svg" style="display: none;"><defs>
|
||
<symbol id="theme-svg-external-link" viewBox="0 0 24 24"><path fill="currentColor" d="M21 13v10h-21v-19h12v2h-10v15h17v-8h2zm3-12h-10.988l4.035 4-6.977 7.07 2.828 2.828 6.977-7.07 4.125 4.172v-11z"/></symbol>
|
||
</defs></svg>
|
||
<script>!function(){var t=function(){try{return new URLSearchParams(window.location.search).get("docusaurus-theme")}catch(t){}}()||function(){try{return window.localStorage.getItem("theme")}catch(t){}}();document.documentElement.setAttribute("data-theme",t||(window.matchMedia("(prefers-color-scheme: dark)").matches?"dark":"light")),document.documentElement.setAttribute("data-theme-choice",t||"system")}(),function(){try{const c=new URLSearchParams(window.location.search).entries();for(var[t,e]of c)if(t.startsWith("docusaurus-data-")){var a=t.replace("docusaurus-data-","data-");document.documentElement.setAttribute(a,e)}}catch(t){}}()</script><div id="__docusaurus"><div role="region" aria-label="Skip to main content"><a class="skipToContent_fXgn" href="#__docusaurus_skipToContent_fallback">Skip to main content</a></div><nav aria-label="Main" class="theme-layout-navbar navbar navbar--fixed-top navbarHideable_m1mJ"><div class="navbar__inner"><div class="theme-layout-navbar-left navbar__items"><button aria-label="Toggle navigation bar" aria-expanded="false" class="navbar__toggle clean-btn" type="button"><svg width="30" height="30" viewBox="0 0 30 30" aria-hidden="true"><path stroke="currentColor" stroke-linecap="round" stroke-miterlimit="10" stroke-width="2" d="M4 7h22M4 15h22M4 23h22"></path></svg></button><a class="navbar__brand" href="/"><div class="navbar__logo"><img src="/img/lf-docs-light.svg" alt="Langflow" class="themedComponent_mlkZ themedComponent--light_NVdE"><img src="/img/lf-docs-dark.svg" alt="Langflow" class="themedComponent_mlkZ themedComponent--dark_xIcU"></div></a></div><div class="theme-layout-navbar-right navbar__items navbar__items--right"><a href="https://github.com/langflow-ai/langflow" target="_blank" class="navbar__item navbar__link header-github-link" data-event="UI Interaction" data-action="clicked" data-channel="docs" data-element-id="social-github" data-namespace="header" data-platform-title="Langflow"></a><a href="https://twitter.com/langflow_ai" target="_blank" class="navbar__item navbar__link header-twitter-link" data-event="UI Interaction" data-action="clicked" data-channel="docs" data-element-id="social-twitter" data-namespace="header" data-platform-title="Langflow"></a><a href="https://discord.gg/EqksyE2EX9" target="_blank" class="navbar__item navbar__link header-discord-link" data-event="UI Interaction" data-action="clicked" data-channel="docs" data-element-id="social-discord" data-namespace="header" data-platform-title="Langflow"></a><div class="toggle_vylO colorModeToggle_DEke"><button class="clean-btn toggleButton_gllP toggleButtonDisabled_aARS" type="button" disabled="" title="system mode" aria-label="Switch between dark and light mode (currently system mode)"><svg viewBox="0 0 24 24" width="24" height="24" aria-hidden="true" class="toggleIcon_g3eP lightToggleIcon_pyhR"><path fill="currentColor" d="M12,9c1.65,0,3,1.35,3,3s-1.35,3-3,3s-3-1.35-3-3S10.35,9,12,9 M12,7c-2.76,0-5,2.24-5,5s2.24,5,5,5s5-2.24,5-5 S14.76,7,12,7L12,7z M2,13l2,0c0.55,0,1-0.45,1-1s-0.45-1-1-1l-2,0c-0.55,0-1,0.45-1,1S1.45,13,2,13z M20,13l2,0c0.55,0,1-0.45,1-1 s-0.45-1-1-1l-2,0c-0.55,0-1,0.45-1,1S19.45,13,20,13z M11,2v2c0,0.55,0.45,1,1,1s1-0.45,1-1V2c0-0.55-0.45-1-1-1S11,1.45,11,2z M11,20v2c0,0.55,0.45,1,1,1s1-0.45,1-1v-2c0-0.55-0.45-1-1-1C11.45,19,11,19.45,11,20z M5.99,4.58c-0.39-0.39-1.03-0.39-1.41,0 c-0.39,0.39-0.39,1.03,0,1.41l1.06,1.06c0.39,0.39,1.03,0.39,1.41,0s0.39-1.03,0-1.41L5.99,4.58z M18.36,16.95 c-0.39-0.39-1.03-0.39-1.41,0c-0.39,0.39-0.39,1.03,0,1.41l1.06,1.06c0.39,0.39,1.03,0.39,1.41,0c0.39-0.39,0.39-1.03,0-1.41 L18.36,16.95z M19.42,5.99c0.39-0.39,0.39-1.03,0-1.41c-0.39-0.39-1.03-0.39-1.41,0l-1.06,1.06c-0.39,0.39-0.39,1.03,0,1.41 s1.03,0.39,1.41,0L19.42,5.99z M7.05,18.36c0.39-0.39,0.39-1.03,0-1.41c-0.39-0.39-1.03-0.39-1.41,0l-1.06,1.06 c-0.39,0.39-0.39,1.03,0,1.41s1.03,0.39,1.41,0L7.05,18.36z"></path></svg><svg viewBox="0 0 24 24" width="24" height="24" aria-hidden="true" class="toggleIcon_g3eP darkToggleIcon_wfgR"><path fill="currentColor" d="M9.37,5.51C9.19,6.15,9.1,6.82,9.1,7.5c0,4.08,3.32,7.4,7.4,7.4c0.68,0,1.35-0.09,1.99-0.27C17.45,17.19,14.93,19,12,19 c-3.86,0-7-3.14-7-7C5,9.07,6.81,6.55,9.37,5.51z M12,3c-4.97,0-9,4.03-9,9s4.03,9,9,9s9-4.03,9-9c0-0.46-0.04-0.92-0.1-1.36 c-0.98,1.37-2.58,2.26-4.4,2.26c-2.98,0-5.4-2.42-5.4-5.4c0-1.81,0.89-3.42,2.26-4.4C12.92,3.04,12.46,3,12,3L12,3z"></path></svg><svg viewBox="0 0 24 24" width="24" height="24" aria-hidden="true" class="toggleIcon_g3eP systemToggleIcon_QzmC"><path fill="currentColor" d="m12 21c4.971 0 9-4.029 9-9s-4.029-9-9-9-9 4.029-9 9 4.029 9 9 9zm4.95-13.95c1.313 1.313 2.05 3.093 2.05 4.95s-0.738 3.637-2.05 4.95c-1.313 1.313-3.093 2.05-4.95 2.05v-14c1.857 0 3.637 0.737 4.95 2.05z"></path></svg></button></div><div class="navbarSearchContainer_Bca1"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search (Command+K)"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20" aria-hidden="true"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div id="__docusaurus_skipToContent_fallback" class="theme-layout-main main-wrapper mainWrapper_z2l0"><div class="docsWrapper_hBAB"><button aria-label="Scroll back to top" class="clean-btn theme-back-to-top-button backToTopButton_sjWU" type="button"></button><div class="docRoot_UBD9"><aside class="theme-doc-sidebar-container docSidebarContainer_YfHR"><div class="sidebarViewport_aRkj"><div class="sidebar_njMd sidebarWithHideableNavbar_wUlq"><a tabindex="-1" class="sidebarLogo_isFc" href="/"><img src="/img/lf-docs-light.svg" alt="Langflow" class="themedComponent_mlkZ themedComponent--light_NVdE"><img src="/img/lf-docs-dark.svg" alt="Langflow" class="themedComponent_mlkZ themedComponent--dark_xIcU"></a><nav aria-label="Docs sidebar" class="menu thin-scrollbar menu_SIkG"><ul class="theme-doc-sidebar-menu menu__list"><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/">Get started</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/concepts-overview">Flows</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/agents">Agents</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/mcp-client">Model Context Protocol (MCP)</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/api-keys-and-authentication">Develop</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/deployment-overview">Deploy</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret menu__link--active" role="button" aria-expanded="true" href="/concepts-components">Components reference</a></div><ul class="menu__list"><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-2 menu__list-item"><a class="menu__link" tabindex="0" href="/concepts-components">Components overview</a></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-2 menu__list-item"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret menu__link--active" role="button" aria-expanded="true" tabindex="0" href="/components-io">Core components</a></div><ul class="menu__list"><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-3 menu__list-item"><a class="menu__link" tabindex="0" href="/components-io">Input / Output</a></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-3 menu__list-item"><a class="menu__link" tabindex="0" href="/components-agents">Agents</a></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-3 menu__list-item"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret menu__link--active" role="button" aria-expanded="true" tabindex="0" href="/components-models">Models</a></div><ul class="menu__list"><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-4 menu__list-item"><a class="menu__link menu__link--active" aria-current="page" tabindex="0" href="/components-models">Language Model</a></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-4 menu__list-item"><a class="menu__link" tabindex="0" href="/components-embedding-models">Embedding Model</a></li></ul></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-3 menu__list-item"><a class="menu__link" tabindex="0" href="/components-data">Data</a></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-3 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" tabindex="0" href="/components-processing">Processing</a></div></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-3 menu__list-item"><a class="menu__link" tabindex="0" href="/components-logic">Logic</a></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-3 menu__list-item"><a class="menu__link" tabindex="0" href="/components-helpers">Helpers</a></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-3 menu__list-item"><a class="menu__link" tabindex="0" href="/components-tools">Tools</a></li></ul></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-2 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" tabindex="0" href="/components-bundle-components">Bundles</a></div></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-2 menu__list-item"><a class="menu__link" tabindex="0" href="/components-custom-components">Create custom Python components</a></li></ul></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/api-reference-api-examples">API reference</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/contributing-community">Contribute</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/release-notes">Release notes</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" role="button" aria-expanded="false" href="/troubleshoot">Support</a></div></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-1 sidebar-ad">
|
||
<a href="https://www.langflow.org/desktop" target="_blank" class="menu__link">
|
||
<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||
<g clip-path="url(#clip0_1645_37)">
|
||
<path d="M12 17H20C21.1046 17 22 16.1046 22 15V13M12 17H4C2.89543 17 2 16.1046 2 15V5C2 3.89543 2.89543 3 4 3H10M12 17V21M8 21H12M12 21H16M11.75 10.2917H13.2083L16.125 7.375H17.5833L20.5 4.45833H21.9583M16.125 11.75H17.5833L20.5 8.83333H21.9583M11.75 5.91667H13.2083L16.125 3H17.5833" stroke="currentColor" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round"/>
|
||
</g>
|
||
<defs>
|
||
<clipPath id="clip0_1645_37">
|
||
<rect width="24" height="24" fill="white"/>
|
||
</clipPath>
|
||
</defs>
|
||
</svg>
|
||
<div class="sidebar-ad-text-container">
|
||
<span class="sidebar-ad-text">Get started in minutes</span>
|
||
<span class="sidebar-ad-text sidebar-ad-text-gradient">Download Langflow Desktop</span>
|
||
</div>
|
||
</a>
|
||
</li></ul></nav></div></div></aside><main class="docMainContainer_TBSr"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Components reference</span></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Core components</span></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Models</span></li><li class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link">Language Model</span></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Language Model</h1></header><style>[data-ch-theme="github-dark"] { --ch-t-colorScheme: dark;--ch-t-foreground: #c9d1d9;--ch-t-background: #0d1117;--ch-t-lighter-inlineBackground: #0d1117e6;--ch-t-editor-background: #0d1117;--ch-t-editor-foreground: #c9d1d9;--ch-t-editor-lineHighlightBackground: #6e76811a;--ch-t-editor-rangeHighlightBackground: #ffffff0b;--ch-t-editor-infoForeground: #3794FF;--ch-t-editor-selectionBackground: #264F78;--ch-t-focusBorder: #1f6feb;--ch-t-tab-activeBackground: #0d1117;--ch-t-tab-activeForeground: #c9d1d9;--ch-t-tab-inactiveBackground: #010409;--ch-t-tab-inactiveForeground: #8b949e;--ch-t-tab-border: #30363d;--ch-t-tab-activeBorder: #0d1117;--ch-t-editorGroup-border: #30363d;--ch-t-editorGroupHeader-tabsBackground: #010409;--ch-t-editorLineNumber-foreground: #6e7681;--ch-t-input-background: #0d1117;--ch-t-input-foreground: #c9d1d9;--ch-t-input-border: #30363d;--ch-t-icon-foreground: #8b949e;--ch-t-sideBar-background: #010409;--ch-t-sideBar-foreground: #c9d1d9;--ch-t-sideBar-border: #30363d;--ch-t-list-activeSelectionBackground: #6e768166;--ch-t-list-activeSelectionForeground: #c9d1d9;--ch-t-list-hoverBackground: #6e76811a;--ch-t-list-hoverForeground: #c9d1d9; }</style>
|
||
<!-- -->
|
||
<p>Language model components in Langflow generate text using a specified Large Language Model (LLM).
|
||
These components accept inputs like chat messages, files, and instructions in order to generate a text response.</p>
|
||
<p>Langflow includes a <strong>Language Model</strong> core component that has built-in support for many LLMs.
|
||
Alternatively, you can use any <a href="#additional-language-models">additional language model</a> in place of the <strong>Language Model</strong> core component.</p>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="use-language-model-components-in-flows">Use language model components in flows<a href="#use-language-model-components-in-flows" class="hash-link" aria-label="Direct link to Use language model components in flows" title="Direct link to Use language model components in flows"></a></h2>
|
||
<p>Use language model components anywhere you would use an LLM in a flow.</p>
|
||
<div class="tabs-container tabList__CuJ"><ul role="tablist" aria-orientation="horizontal" class="tabs"><li role="tab" tabindex="0" aria-selected="true" class="tabs__item tabItem_LNqP tabs__item--active">Chat</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_LNqP">Drivers</li><li role="tab" tabindex="-1" aria-selected="false" class="tabs__item tabItem_LNqP">Agents</li></ul><div class="margin-top--md"><div role="tabpanel" class="tabItem_Ymn6"><p>One of the most common use cases of language model components is to chat with LLMs in your flows.</p><p>The following example uses a language model component in a chatbot flow similar to the <strong>Basic Prompting</strong> template.</p><ol>
|
||
<li>
|
||
<p>Add the <strong>Language Model</strong> core component to your flow, and then enter your OpenAI API key.</p>
|
||
<p>This example uses the <strong>Language Model</strong> core component's default OpenAI model.
|
||
If you want to use a different provider or model, edit the <strong>Model Provider</strong>, <strong>Model Name</strong>, and <strong>API Key</strong> fields accordingly.</p>
|
||
<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>My preferred provider or model isn't listed</div><div class="admonitionContent_BuS1"><p>If you want to use a provider or model that isn't built-in to the <strong>Language Model</strong> core component, you can replace this component with any <a href="#additional-language-models">additional language model</a>.</p><p>Browse <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-blocks" aria-hidden="true"><rect width="7" height="7" x="14" y="3" rx="1"></rect><path d="M10 21V8a1 1 0 0 0-1-1H4a1 1 0 0 0-1 1v12a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-5a1 1 0 0 0-1-1H3"></path></svg> <a href="/components-bundle-components"><strong>Bundles</strong></a> or <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-search" aria-hidden="true"><circle cx="11" cy="11" r="8"></circle><path d="m21 21-4.3-4.3"></path></svg> <strong>Search</strong> for your preferred provider to find additional language models.</p></div></div>
|
||
</li>
|
||
<li>
|
||
<p>In the <a href="/concepts-components#component-menus">component's header menu</a>, click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-sliders-horizontal" aria-hidden="true"><line x1="21" x2="14" y1="4" y2="4"></line><line x1="10" x2="3" y1="4" y2="4"></line><line x1="21" x2="12" y1="12" y2="12"></line><line x1="8" x2="3" y1="12" y2="12"></line><line x1="21" x2="16" y1="20" y2="20"></line><line x1="12" x2="3" y1="20" y2="20"></line><line x1="14" x2="14" y1="2" y2="6"></line><line x1="8" x2="8" y1="10" y2="14"></line><line x1="16" x2="16" y1="18" y2="22"></line></svg> <strong>Controls</strong>, enable the <strong>System Message</strong> parameter, and then click <strong>Close</strong>.</p>
|
||
</li>
|
||
<li>
|
||
<p>Add a <a href="/components-prompts"><strong>Prompt Template</strong> component</a> to your flow.</p>
|
||
</li>
|
||
<li>
|
||
<p>In the <strong>Template</strong> field, enter some instructions for the LLM, such as <code>You are an expert in geography who is tutoring high school students</code>.</p>
|
||
</li>
|
||
<li>
|
||
<p>Connect the <strong>Prompt Template</strong> component's output to the <strong>Language Model</strong> component's <strong>System Message</strong> input.</p>
|
||
</li>
|
||
<li>
|
||
<p>Add <a href="/components-io#chat-io"><strong>Chat Input</strong> and <strong>Chat Output</strong> components</a> to your flow.
|
||
These components are required for direct chat interaction with an LLM.</p>
|
||
</li>
|
||
<li>
|
||
<p>Connect the <strong>Chat Input</strong> component to the <strong>Language Model</strong> component's <strong>Input</strong>, and then connect the <strong>Language Model</strong> component's <strong>Message</strong> output to the <strong>Chat Output</strong> component.</p>
|
||
<p><img decoding="async" loading="lazy" alt="A basic prompting flow with Language Model, Prompt Template, Chat Input, and Chat Output components" src="/assets/images/component-language-model-1ddc1bd5726d5ea55ac91f7813a024d7.png" width="2000" height="1060" class="img_ev3q"></p>
|
||
</li>
|
||
<li>
|
||
<p>Open the <strong>Playground</strong>, and ask a question to chat with the LLM and test the flow, such as <code>What is the capital of Utah?</code>.</p>
|
||
<details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Result</summary><div><div class="collapsibleContent_i85q"><p>The following response is an example of an OpenAI model's response.
|
||
Your actual response may vary based on the model version at the time of your request, your template, and input.</p><div class="ch-codeblock not-prose" data-ch-theme="github-dark"><div class="ch-code-wrapper ch-code" data-ch-measured="false"><code class="ch-code-scroll-parent"><br><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>The capital of Utah is Salt Lake City. It is not only the largest city in the state but also serves as the cultural and economic center of Utah. Salt Lake City was founded in 1847 by Mormon pioneers and is known for its proximity to the Great Salt Lake and its role in the history of the Church of Jesus Christ of Latter-day Saints. For more information, you can refer to sources such as the U.S. Geological Survey or the official state website of Utah.</span></div></div><br></code></div></div></div></div></details>
|
||
</li>
|
||
<li>
|
||
<p>Optional: Try a different model or provider to see how the response changes.
|
||
For example, if you are using the <strong>Language Model</strong> core component, you could try an Anthropic model.</p>
|
||
<p>Then, open the <strong>Playground</strong>, ask the same question as you did before, and then compare the content and format of the responses.</p>
|
||
<p>This helps you understand how different models handle the same request so you can choose the best model for your use case.
|
||
You can also learn more about different models in each model provider's documentation.</p>
|
||
<details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Result</summary><div><div class="collapsibleContent_i85q"><p>The following response is an example of an Anthropic model's response.
|
||
Your actual response may vary based on the model version at the time of your request, your template, and input.</p><p>Note that this response is shorter and includes sources, whereas the previous OpenAI response was more encyclopedic and didn't cite sources.</p><div class="ch-codeblock not-prose" data-ch-theme="github-dark"><div class="ch-code-wrapper ch-code" data-ch-measured="false"><code class="ch-code-scroll-parent"><br><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>The capital of Utah is Salt Lake City. It is also the most populous city in the state. Salt Lake City has been the capital of Utah since 1896, when Utah became a state.</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>Sources:</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>Utah State Government Official Website (utah.gov)</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>U.S. Census Bureau</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>Encyclopedia Britannica</span></div></div><br></code></div></div></div></div></details>
|
||
</li>
|
||
</ol></div><div role="tabpanel" class="tabItem_Ymn6" hidden=""><p>Some components use a language model component to perform LLM-driven actions.
|
||
Typically, these components prepare data for further processing by downstream components, rather than emitting direct chat output.
|
||
For an example, see the <a href="/components-processing#smart-transform"><strong>Smart Function</strong> component</a>.</p><p>A component must accept a <code>LanguageModel</code> input to use a language model component as a driver, and you must set the language model component's output type to <code>LanguageModel</code>.
|
||
For more information, see <a href="#language-model-output-types">Language Model output types</a>.</p></div><div role="tabpanel" class="tabItem_Ymn6" hidden=""><p>If you don't want to use the <strong>Agent</strong> component's built-in LLMs, you can use a language model component to connect your preferred model:</p><ol>
|
||
<li>
|
||
<p>Add a language model component to your flow.</p>
|
||
<p>You can use the <strong>Language Model</strong> core component or browse <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-blocks" aria-hidden="true"><rect width="7" height="7" x="14" y="3" rx="1"></rect><path d="M10 21V8a1 1 0 0 0-1-1H4a1 1 0 0 0-1 1v12a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-5a1 1 0 0 0-1-1H3"></path></svg> <a href="/components-bundle-components"><strong>Bundles</strong></a> to find additional language models.
|
||
Components in bundles may not have <code>language model</code> in the name.
|
||
For example, Azure OpenAI LLMs are provided through the <a href="/bundles-azure#azure-openai"><strong>Azure OpenAI</strong> component</a>.</p>
|
||
</li>
|
||
<li>
|
||
<p>Configure the language model component as needed to connect to your preferred model.</p>
|
||
</li>
|
||
<li>
|
||
<p>Change the language model component's output type from <strong>Model Response</strong> to <strong>Language Model</strong>.
|
||
The output port changes to a <code>LanguageModel</code> port.
|
||
This is required to connect the language model component to the <strong>Agent</strong> component.
|
||
For more information, see <a href="#language-model-output-types">Language Model output types</a>.</p>
|
||
</li>
|
||
<li>
|
||
<p>Add an <strong>Agent</strong> component to the flow, and then set <strong>Model Provider</strong> to <strong>Connect other models</strong>.</p>
|
||
<p>The <strong>Model Provider</strong> field changes to a <strong>Language Model</strong> (<code>LanguageModel</code>) input.</p>
|
||
</li>
|
||
<li>
|
||
<p>Connect the language model component's output to the <strong>Agent</strong> component's <strong>Language Model</strong> input.
|
||
The <strong>Agent</strong> component now inherits the language model settings from the connected language model component instead of using any of the built-in models.</p>
|
||
</li>
|
||
</ol></div></div></div>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="language-model-parameters">Language model parameters<a href="#language-model-parameters" class="hash-link" aria-label="Direct link to Language model parameters" title="Direct link to Language model parameters"></a></h2>
|
||
<p>The following parameters are for the <strong>Language Model</strong> core component.
|
||
Other language model components can have additional or different parameters.</p>
|
||
<!-- -->
|
||
<p>Some parameters are hidden by default in the visual editor.
|
||
You can modify all parameters through the <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-sliders-horizontal" aria-hidden="true"><line x1="21" x2="14" y1="4" y2="4"></line><line x1="10" x2="3" y1="4" y2="4"></line><line x1="21" x2="12" y1="12" y2="12"></line><line x1="8" x2="3" y1="12" y2="12"></line><line x1="21" x2="16" y1="20" y2="20"></line><line x1="12" x2="3" y1="20" y2="20"></line><line x1="14" x2="14" y1="2" y2="6"></line><line x1="8" x2="8" y1="10" y2="14"></line><line x1="16" x2="16" y1="18" y2="22"></line></svg> <strong>Controls</strong> in the <a href="/concepts-components#component-menus">component's header menu</a>.</p>
|
||
<table><thead><tr><th>Name</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>provider</td><td>String</td><td>Input parameter. The model provider to use.</td></tr><tr><td>model_name</td><td>String</td><td>Input parameter. The name of the model to use. Options depend on the selected provider.</td></tr><tr><td>api_key</td><td>SecretString</td><td>Input parameter. The API Key for authentication with the selected provider.</td></tr><tr><td>input_value</td><td>String</td><td>Input parameter. The input text to send to the model.</td></tr><tr><td>system_message</td><td>String</td><td>Input parameter. A system message that helps set the behavior of the assistant.</td></tr><tr><td>stream</td><td>Boolean</td><td>Input parameter. Whether to stream the response. Default: <code>false</code>.</td></tr><tr><td>temperature</td><td>Float</td><td>Input parameter. Controls randomness in responses. Range: <code>[0.0, 1.0]</code>. Default: <code>0.1</code>.</td></tr><tr><td>model</td><td>LanguageModel</td><td>Output parameter. Alternative output type to the default <code>Message</code> output. Produces an instance of Chat configured with the specified parameters. See <a href="#language-model-output-types">Language Model output types</a>.</td></tr></tbody></table>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="language-model-output-types">Language model output types<a href="#language-model-output-types" class="hash-link" aria-label="Direct link to Language model output types" title="Direct link to Language model output types"></a></h2>
|
||
<p>Language model components, including the core component and bundled components, can produce two types of output:</p>
|
||
<ul>
|
||
<li>
|
||
<p><strong>Model Response</strong>: The default output type emits the model's generated response as <a href="/data-types#message"><code>Message</code> data</a>.
|
||
Use this output type when you want the typical LLM interaction where the LLM produces a text response based on given input.</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>Language Model</strong>: Change the language model component's output type to <a href="/data-types#languagemodel"><code>LanguageModel</code></a> when you need to attach an LLM to another component in your flow, such as an <strong>Agent</strong> or <strong>Smart Function</strong> component.</p>
|
||
<p>With this configuration, the language model component supports an action completed by another component, rather than a direct chat interaction.
|
||
For an example, the <strong>Smart Function</strong> component uses an LLM to create a function from natural language input.</p>
|
||
</li>
|
||
</ul>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="additional-language-models">Additional language models<a href="#additional-language-models" class="hash-link" aria-label="Direct link to Additional language models" title="Direct link to Additional language models"></a></h2>
|
||
<p>If your provider or model isn't supported by the <strong>Language Model</strong> core component, additional language model components are available in <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-blocks" aria-hidden="true"><rect width="7" height="7" x="14" y="3" rx="1"></rect><path d="M10 21V8a1 1 0 0 0-1-1H4a1 1 0 0 0-1 1v12a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-5a1 1 0 0 0-1-1H3"></path></svg> <a href="/components-bundle-components"><strong>Bundles</strong></a>.</p>
|
||
<p>You can use these components in the same way that you use the core <strong>Language Model</strong> component, as explained in <a href="#use-language-model-components-in-flows">Use language model components in flows</a>.</p>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="pair-models-with-vector-stores">Pair models with vector stores<a href="#pair-models-with-vector-stores" class="hash-link" aria-label="Direct link to Pair models with vector stores" title="Direct link to Pair models with vector stores"></a></h2>
|
||
<!-- -->
|
||
<p>By design, vector data is essential for LLM applications, such as chatbots and agents.</p>
|
||
<p>While you can use an LLM alone for generic chat interactions and common tasks, you can take your application to the next level with context sensitivity (such as RAG) and custom datasets (such as internal business data).
|
||
This often requires integrating vector databases and vector searches that provide the additional context and define meaningful queries.</p>
|
||
<p>Langflow includes vector store components that can read and write vector data, including embedding storage, similarity search, Graph RAG traversals, and dedicated search instances like OpenSearch.
|
||
Because of their interdependent functionality, it is common to use vector store, language model, and embedding model components in the same flow or in a series of dependent flows.</p>
|
||
<p>To find available vector store components, browse <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-blocks" aria-hidden="true"><rect width="7" height="7" x="14" y="3" rx="1"></rect><path d="M10 21V8a1 1 0 0 0-1-1H4a1 1 0 0 0-1 1v12a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-5a1 1 0 0 0-1-1H3"></path></svg> <a href="/components-bundle-components"><strong>Bundles</strong></a> or <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-search" aria-hidden="true"><circle cx="11" cy="11" r="8"></circle><path d="m21 21-4.3-4.3"></path></svg> <strong>Search</strong> for your preferred vector database provider.</p>
|
||
<details class="details_lb9f alert alert--info details_b_Ee" data-collapsed="true"><summary>Example: Vector search flow</summary><div><div class="collapsibleContent_i85q"><div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_BuS1"><p>For a tutorial that uses vector data in a flow, see <a href="/chat-with-rag">Create a vector RAG chatbot</a>.</p></div></div>
|
||
<p>The following example demonstrates how to use vector store components in flows alongside related components like embedding model and language model components.
|
||
These steps walk through important configuration details, functionality, and best practices for using these components effectively.
|
||
This is only one example; it isn't a prescriptive guide to all possible use cases or configurations.</p>
|
||
<ol>
|
||
<li>
|
||
<p>Create a flow with the <strong>Vector Store RAG</strong> template.</p>
|
||
<p>This template has two subflows.
|
||
The <strong>Load Data</strong> subflow loads embeddings and content into a vector database, and the <strong>Retriever</strong> subflow runs a vector search to retrieve relevant context based on a user's query.</p>
|
||
</li>
|
||
<li>
|
||
<p>Configure the database connection for both <a href="/bundles-datastax#astra-db"><strong>Astra DB</strong> components</a>, or replace them with another pair of vector store components of your choice.
|
||
Make sure the components connect to the same vector store, and that the component in the <strong>Retriever</strong> subflow is able to run a similarity search.</p>
|
||
<p>The parameters you set in each vector store component depend on the component's role in your flow.
|
||
In this example, the <strong>Load Data</strong> subflow <em>writes</em> to the vector store, whereas the <strong>Retriever</strong> subflow <em>reads</em> from the vector store.
|
||
Therefore, search-related parameters are only relevant to the <strong>Vector Search</strong> component in the <strong>Retriever</strong> subflow.</p>
|
||
<p>For information about specific parameters, see the documentation for your chosen vector store component.</p>
|
||
</li>
|
||
<li>
|
||
<p>To configure the embedding model, do one of the following:</p>
|
||
<ul>
|
||
<li>
|
||
<p><strong>Use an OpenAI model</strong>: In both <strong>OpenAI Embeddings</strong> components, enter your OpenAI API key.
|
||
You can use the default model or select a different OpenAI embedding model.</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>Use another provider</strong>: Replace the <strong>OpenAI Embeddings</strong> components with another pair of <a href="/components-embedding-models">embedding model components</a> of your choice, and then configure the parameters and credentials accordingly.</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>Use Astra DB vectorize</strong>: If you are using an Astra DB vector store that has a vectorize integration, you can remove both <strong>OpenAI Embeddings</strong> components.
|
||
If you do this, the vectorize integration automatically generates embeddings from the <strong>Ingest Data</strong> (in the <strong>Load Data</strong> subflow) and <strong>Search Query</strong> (in the <strong>Retriever</strong> subflow).</p>
|
||
</li>
|
||
</ul>
|
||
<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_BuS1"><p>If your vector store already contains embeddings, make sure your embedding model components use the same model as your previous embeddings.
|
||
Mixing embedding models in the same vector store can produce inaccurate search results.</p></div></div>
|
||
</li>
|
||
<li>
|
||
<p>Recommended: In the <a href="/components-processing#split-text"><strong>Split Text</strong> component</a>, optimize the chunking settings for your embedding model.
|
||
For example, if your embedding model has a token limit of 512, then the <strong>Chunk Size</strong> parameter must not exceed that limit.</p>
|
||
<p>Additionally, because the <strong>Retriever</strong> subflow passes the chat input directly to the vector store component for vector search, make sure that your chat input string doesn't exceed your embedding model's limits.
|
||
For this example, you can enter a query that is within the limits; however, in a production environment, you might need to implement additional checks or preprocessing steps to ensure compliance.
|
||
For example, use additional components to prepare the chat input before running the vector search, or enforce chat input limits in your application code.</p>
|
||
</li>
|
||
<li>
|
||
<p>In the <strong>Language Model</strong> component, enter your OpenAI API key, or select a different provider and model to use for the chat portion of the flow.</p>
|
||
</li>
|
||
<li>
|
||
<p>Run the <strong>Load Data</strong> subflow to populate your vector store.
|
||
In the <strong>File</strong> component, select one or more files, and then click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-play" aria-hidden="true"><polygon points="6 3 20 12 6 21 6 3"></polygon></svg> <strong>Run component</strong> on the vector store component in the <strong>Load Data</strong> subflow.</p>
|
||
<p>The <strong>Load Data</strong> subflow loads files from your local machine, chunks them, generates embeddings for the chunks, and then stores the chunks and their embeddings in the vector database.</p>
|
||
<p><img decoding="async" loading="lazy" alt="Embedding data into a vector store" src="/assets/images/vector-store-document-ingestion-6157311fb4d16e7f944d55254f0cc0e2.png" width="4000" height="2512" class="img_ev3q"></p>
|
||
<p>The <strong>Load Data</strong> subflow is separate from the <strong>Retriever</strong> subflow because you probably won't run it every time you use the chat.
|
||
You can run the <strong>Load Data</strong> subflow as needed to preload or update the data in your vector store.
|
||
Then, your chat interactions only use the components that are necessary for chat.</p>
|
||
<p>If your vector store already contains data that you want to use for vector search, then you don't need to run the <strong>Load Data</strong> subflow.</p>
|
||
</li>
|
||
<li>
|
||
<p>Open the <strong>Playground</strong> and start chatting to run the <strong>Retriever</strong> subflow.</p>
|
||
<p>The <strong>Retriever</strong> subflow generates an embedding from chat input, runs a vector search to retrieve similar content from your vector store, parses the search results into supplemental context for the LLM, and then uses the LLM to generate a natural language response to your query.
|
||
The LLM uses the vector search results along with its internal training data and tools, such as basic web search and datetime information, to produce the response.</p>
|
||
<p><img decoding="async" loading="lazy" alt="Retrieval from a vector store" src="/assets/images/vector-store-retrieval-af7257d77ff0259ab1a0980641d464ce.png" width="4000" height="1324" class="img_ev3q"></p>
|
||
<p>To avoid passing the entire block of raw search results to the LLM, the <strong>Parser</strong> component extracts <code>text</code> strings from the search results <code>Data</code> object, and then passes them to the <strong>Prompt Template</strong> component in <code>Message</code> format.
|
||
From there, the strings and other template content are compiled into natural language instructions for the LLM.</p>
|
||
<p>You can use other components for this transformation, such as the <strong>Data Operations</strong> component, depending on how you want to use the search results.</p>
|
||
<p>To view the raw search results, click <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-text-search" aria-hidden="true"><path d="M21 6H3"></path><path d="M10 12H3"></path><path d="M10 18H3"></path><circle cx="17" cy="15" r="3"></circle><path d="m21 19-1.9-1.9"></path></svg> <strong>Inspect output</strong> on the vector store component after running the <strong>Retriever</strong> subflow.</p>
|
||
</li>
|
||
</ol></div></div></details></div></article><nav class="docusaurus-mt-lg pagination-nav" aria-label="Docs pages"><a class="pagination-nav__link pagination-nav__link--prev" href="/components-agents"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Agents</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/components-embedding-models"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Embedding Model</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#use-language-model-components-in-flows" class="table-of-contents__link toc-highlight">Use language model components in flows</a></li><li><a href="#language-model-parameters" class="table-of-contents__link toc-highlight">Language model parameters</a></li><li><a href="#language-model-output-types" class="table-of-contents__link toc-highlight">Language model output types</a></li><li><a href="#additional-language-models" class="table-of-contents__link toc-highlight">Additional language models</a></li><li><a href="#pair-models-with-vector-stores" class="table-of-contents__link toc-highlight">Pair models with vector stores</a></li></ul></div></div></div></div></main></div></div></div><footer class="theme-layout-footer footer"><div class="container container-fluid"><div class="row footer__links"><div class="theme-layout-footer-column col footer__col"><div class="footer__title"></div><ul class="footer__items clean-list"><li class="footer__item"><div class="footer-links">
|
||
<span>© 2025 Langflow</span>
|
||
<span id="preferenceCenterContainer"> · <a href="#" onclick='return"undefined"!=typeof window&&window.truste&&window.truste.eu&&window.truste.eu.clickListener&&window.truste.eu.clickListener(),!1' style="cursor: pointer;">Manage Privacy Choices</a></span>
|
||
</div></li></ul></div></div></div></footer><div style="position:fixed;right:21px;bottom:21px;z-index:100;display:flex;align-items:center;gap:10px;cursor:pointer"><div style="background-color:#f6f6f6;border-radius:50%;width:48px;height:48px;display:flex;align-items:center;justify-content:center;box-shadow:0 2px 4px rgba(0,0,0,0.1)"><img src="/img/langflow-icon-black-transparent.svg" style="width:40px" alt="Search"></div></div></div>
|
||
</body>
|
||
</html> |