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octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary Link--external" target="_blank" data-analytics-event="{"location":"navbar","action":"blog","context":"product","tag":"link","label":"blog_link_product_navbar"}" href="https://github.blog"> Blog <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> </ul> </div> </div> </div> </li> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Solutions <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 8.939l3.72-3.719a.749.749 0 0 1 1.06 0Z"></path> </svg> </button> <div class="HeaderMenu-dropdown dropdown-menu rounded m-0 p-0 pt-2 pt-lg-4 position-relative position-lg-absolute left-0 left-lg-n3 d-lg-flex flex-wrap dropdown-menu-wide"> <div class="HeaderMenu-column px-lg-4 border-lg-right mb-4 mb-lg-0 pr-lg-7"> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0 pb-lg-3 mb-3 mb-lg-0"> <span class="d-block h4 color-fg-default my-1" id="solutions-by-company-size-heading">By company size</span> <ul class="list-style-none f5" aria-labelledby="solutions-by-company-size-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"enterprises","context":"solutions","tag":"link","label":"enterprises_link_solutions_navbar"}" href="https://github.com/enterprise"> Enterprises </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"small_and_medium_teams","context":"solutions","tag":"link","label":"small_and_medium_teams_link_solutions_navbar"}" href="https://github.com/team"> Small and medium teams </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"startups","context":"solutions","tag":"link","label":"startups_link_solutions_navbar"}" href="https://github.com/enterprise/startups"> Startups </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"nonprofits","context":"solutions","tag":"link","label":"nonprofits_link_solutions_navbar"}" href="/solutions/industry/nonprofits"> Nonprofits </a></li> </ul> </div> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="solutions-by-use-case-heading">By use case</span> <ul class="list-style-none f5" aria-labelledby="solutions-by-use-case-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"devsecops","context":"solutions","tag":"link","label":"devsecops_link_solutions_navbar"}" href="/solutions/use-case/devsecops"> DevSecOps </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"devops","context":"solutions","tag":"link","label":"devops_link_solutions_navbar"}" href="/solutions/use-case/devops"> DevOps </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"ci_cd","context":"solutions","tag":"link","label":"ci_cd_link_solutions_navbar"}" href="/solutions/use-case/ci-cd"> CI/CD </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"view_all_use_cases","context":"solutions","tag":"link","label":"view_all_use_cases_link_solutions_navbar"}" href="/solutions/use-case"> View all use cases </a></li> </ul> </div> </div> <div class="HeaderMenu-column px-lg-4"> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="solutions-by-industry-heading">By industry</span> <ul class="list-style-none f5" aria-labelledby="solutions-by-industry-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"healthcare","context":"solutions","tag":"link","label":"healthcare_link_solutions_navbar"}" href="/solutions/industry/healthcare"> Healthcare </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"financial_services","context":"solutions","tag":"link","label":"financial_services_link_solutions_navbar"}" href="/solutions/industry/financial-services"> Financial services </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"manufacturing","context":"solutions","tag":"link","label":"manufacturing_link_solutions_navbar"}" href="/solutions/industry/manufacturing"> Manufacturing </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"government","context":"solutions","tag":"link","label":"government_link_solutions_navbar"}" href="/solutions/industry/government"> Government </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"view_all_industries","context":"solutions","tag":"link","label":"view_all_industries_link_solutions_navbar"}" href="/solutions/industry"> View all industries </a></li> </ul> </div> </div> <div class="HeaderMenu-trailing-link rounded-bottom-2 flex-shrink-0 mt-lg-4 px-lg-4 py-4 py-lg-3 f5 text-semibold"> <a href="/solutions"> View all solutions <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-right HeaderMenu-trailing-link-icon"> <path d="M6.22 3.22a.75.75 0 0 1 1.06 0l4.25 4.25a.75.75 0 0 1 0 1.06l-4.25 4.25a.751.751 0 0 1-1.042-.018.751.751 0 0 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d-lg-flex flex-wrap dropdown-menu-wide"> <div class="HeaderMenu-column px-lg-4 border-lg-right mb-4 mb-lg-0 pr-lg-7"> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="resources-topics-heading">Topics</span> <ul class="list-style-none f5" aria-labelledby="resources-topics-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"ai","context":"resources","tag":"link","label":"ai_link_resources_navbar"}" href="/resources/articles/ai"> AI </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"devops","context":"resources","tag":"link","label":"devops_link_resources_navbar"}" href="/resources/articles/devops"> DevOps </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"security","context":"resources","tag":"link","label":"security_link_resources_navbar"}" href="/resources/articles/security"> Security </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"software_development","context":"resources","tag":"link","label":"software_development_link_resources_navbar"}" href="/resources/articles/software-development"> Software Development </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"view_all","context":"resources","tag":"link","label":"view_all_link_resources_navbar"}" href="/resources/articles"> View all </a></li> </ul> </div> </div> <div class="HeaderMenu-column px-lg-4"> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0 border-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="resources-explore-heading">Explore</span> <ul class="list-style-none f5" aria-labelledby="resources-explore-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary Link--external" target="_blank" data-analytics-event="{"location":"navbar","action":"learning_pathways","context":"resources","tag":"link","label":"learning_pathways_link_resources_navbar"}" href="https://resources.github.com/learn/pathways"> Learning Pathways <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary Link--external" target="_blank" data-analytics-event="{"location":"navbar","action":"events_amp_webinars","context":"resources","tag":"link","label":"events_amp_webinars_link_resources_navbar"}" href="https://resources.github.com"> Events & Webinars <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"ebooks_amp_whitepapers","context":"resources","tag":"link","label":"ebooks_amp_whitepapers_link_resources_navbar"}" href="https://github.com/resources/whitepapers"> Ebooks & Whitepapers </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"customer_stories","context":"resources","tag":"link","label":"customer_stories_link_resources_navbar"}" href="https://github.com/customer-stories"> Customer Stories </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary Link--external" target="_blank" data-analytics-event="{"location":"navbar","action":"partners","context":"resources","tag":"link","label":"partners_link_resources_navbar"}" href="https://partner.github.com"> Partners <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"executive_insights","context":"resources","tag":"link","label":"executive_insights_link_resources_navbar"}" href="https://github.com/solutions/executive-insights"> Executive Insights </a></li> </ul> </div> </div> </div> </li> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Open Source <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 8.939l3.72-3.719a.749.749 0 0 1 1.06 0Z"></path> </svg> </button> <div class="HeaderMenu-dropdown dropdown-menu rounded m-0 p-0 pt-2 pt-lg-4 position-relative position-lg-absolute left-0 left-lg-n3 pb-2 pb-lg-4 px-lg-4"> <div class="HeaderMenu-column"> <div class="border-bottom pb-3 pb-lg-0 pb-lg-3 mb-3 mb-lg-0 mb-lg-3"> <ul class="list-style-none f5" > <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description" data-analytics-event="{"location":"navbar","action":"github_sponsors","context":"open_source","tag":"link","label":"github_sponsors_link_open_source_navbar"}" href="/sponsors"> <div> <div class="color-fg-default h4">GitHub Sponsors</div> Fund open source developers </div> </a></li> </ul> </div> <div class="border-bottom pb-3 pb-lg-0 pb-lg-3 mb-3 mb-lg-0 mb-lg-3"> <ul class="list-style-none f5" > <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description" data-analytics-event="{"location":"navbar","action":"the_readme_project","context":"open_source","tag":"link","label":"the_readme_project_link_open_source_navbar"}" href="https://github.com/readme"> <div> <div class="color-fg-default h4">The ReadME Project</div> GitHub community articles </div> </a></li> </ul> </div> <div class="border-bottom pb-3 pb-lg-0 border-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="open-source-repositories-heading">Repositories</span> <ul class="list-style-none f5" aria-labelledby="open-source-repositories-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"topics","context":"open_source","tag":"link","label":"topics_link_open_source_navbar"}" href="https://github.com/topics"> Topics </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" 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viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 8.939l3.72-3.719a.749.749 0 0 1 1.06 0Z"></path> </svg> </button> <div class="HeaderMenu-dropdown dropdown-menu rounded m-0 p-0 pt-2 pt-lg-4 position-relative position-lg-absolute left-0 left-lg-n3 pb-2 pb-lg-4 px-lg-4"> <div class="HeaderMenu-column"> <div class="border-bottom pb-3 pb-lg-0 pb-lg-3 mb-3 mb-lg-0 mb-lg-3"> <ul class="list-style-none f5" > <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description" data-analytics-event="{"location":"navbar","action":"enterprise_platform","context":"enterprise","tag":"link","label":"enterprise_platform_link_enterprise_navbar"}" href="/enterprise"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" 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100%;\"\u003e\u003c/a\u003e\n\u003c/p\u003e\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eMarqo\u003c/h2\u003e\u003ca id=\"user-content-marqo\" class=\"anchor\" aria-label=\"Permalink: Marqo\" href=\"#marqo\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eMarqo is more than a vector database, it's an end-to-end vector search engine for both text and images. Vector generation, storage and retrieval are handled out of the box through a single API. No need to bring your own embeddings.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eWhy Marqo?\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eVector similarity alone is not enough for vector search. Vector search requires more than a vector database - it also requires machine learning (ML) deployment and management, preprocessing and transformations of inputs as well as the ability to modify search behavior without retraining a model. Marqo contains all these pieces, enabling developers to build vector search into their application with minimal effort. A full list of features can be found \u003ca href=\"#-core-features\"\u003ebelow\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eWhy bundle embedding generation with vector search?\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eVector databases are specialized components for vector similarity and only service one component of a vector search system. They are “vectors in - vectors out”. They still require the production of vectors, management of the ML models, associated orchestration and processing of the inputs. Marqo makes this easy by being “documents in, documents out”. Preprocessing of text and images, embedding the content, storing meta-data and deployment of inference and storage is all taken care of by Marqo.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eQuick start\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eHere is a code snippet for a minimal example of vector search with Marqo (see \u003ca href=\"#getting-started\"\u003eGetting Started\u003c/a\u003e):\u003c/p\u003e\n\u003col dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eMarqo requires Docker. To install Docker go to the \u003ca href=\"https://docs.docker.com/get-docker/\" rel=\"nofollow\"\u003eDocker Official website\u003c/a\u003e. Ensure that docker has at least 8GB memory and 50GB storage. In Docker desktop, you can do this by clicking the settings icon, then resources, and selecting 8GB memory.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eUse docker to run Marqo:\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"\ndocker rm -f marqo\ndocker pull marqoai/marqo:latest\ndocker run --name marqo -it -p 8882:8882 marqoai/marqo:latest\n\"\u003e\u003cpre\u003edocker rm -f marqo\ndocker pull marqoai/marqo:latest\ndocker run --name marqo -it -p 8882:8882 marqoai/marqo:latest\n\u003c/pre\u003e\u003c/div\u003e\n\u003col start=\"3\" dir=\"auto\"\u003e\n\u003cli\u003eInstall the Marqo client:\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install marqo\"\u003e\u003cpre\u003epip install marqo\u003c/pre\u003e\u003c/div\u003e\n\u003col start=\"4\" dir=\"auto\"\u003e\n\u003cli\u003eStart indexing and searching! Let's look at a simple example below:\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"import marqo\n\nmq = marqo.Client(url='http://localhost:8882')\n\nmq.create_index(\u0026quot;my-first-index\u0026quot;, model=\u0026quot;hf/e5-base-v2\u0026quot;)\n\nmq.index(\u0026quot;my-first-index\u0026quot;).add_documents([\n {\n \u0026quot;Title\u0026quot;: \u0026quot;The Travels of Marco Polo\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;A 13th-century travelogue describing Polo's travels\u0026quot;\n }, \n {\n \u0026quot;Title\u0026quot;: \u0026quot;Extravehicular Mobility Unit (EMU)\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;The EMU is a spacesuit that provides environmental protection, \u0026quot;\n \u0026quot;mobility, life support, and communications for astronauts\u0026quot;,\n \u0026quot;_id\u0026quot;: \u0026quot;article_591\u0026quot;\n }],\n tensor_fields=[\u0026quot;Description\u0026quot;]\n)\n\nresults = mq.index(\u0026quot;my-first-index\u0026quot;).search(\n q=\u0026quot;What is the best outfit to wear on the moon?\u0026quot;\n)\n\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eClient\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eurl\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'http://localhost:8882'\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003ecreate_index\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e, \u003cspan class=\"pl-s1\"\u003emodel\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"hf/e5-base-v2\"\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eadd_documents\u003c/span\u003e([\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"The Travels of Marco Polo\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A 13th-century travelogue describing Polo's travels\"\u003c/span\u003e\n }, \n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Extravehicular Mobility Unit (EMU)\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"The EMU is a spacesuit that provides environmental protection, \"\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"mobility, life support, and communications for astronauts\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"_id\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"article_591\"\u003c/span\u003e\n }],\n \u003cspan class=\"pl-s1\"\u003etensor_fields\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e[\u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e]\n)\n\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\n \u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"What is the best outfit to wear on the moon?\"\u003c/span\u003e\n)\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003e✨ Core Features\u003c/h2\u003e\u003ca id=\"user-content--core-features\" class=\"anchor\" aria-label=\"Permalink: ✨ Core Features\" href=\"#-core-features\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e🤖 State of the art embeddings\u003c/strong\u003e\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eUse the latest machine learning models from PyTorch, Huggingface, OpenAI and more.\u003c/li\u003e\n\u003cli\u003eStart with a pre-configured model or bring your own.\u003c/li\u003e\n\u003cli\u003eCPU and GPU support.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e⚡ Performance\u003c/strong\u003e\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eEmbeddings stored in in-memory HNSW indexes, achieving cutting edge search speeds.\u003c/li\u003e\n\u003cli\u003eScale to hundred-million document indexes with horizontal index sharding.\u003c/li\u003e\n\u003cli\u003eAsync and non-blocking data upload and search.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e🌌 Documents-in-documents-out\u003c/strong\u003e\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eVector generation, storage, and retrieval are provided out of the box.\u003c/li\u003e\n\u003cli\u003eBuild search, entity resolution, and data exploration application with using your text and images.\u003c/li\u003e\n\u003cli\u003eBuild complex semantic queries by combining weighted search terms.\u003c/li\u003e\n\u003cli\u003eFilter search results using Marqo’s query DSL.\u003c/li\u003e\n\u003cli\u003eStore unstructured data and semi-structured metadata together in documents, using a range of supported datatypes like bools, ints and keywords.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e🍱 Managed cloud\u003c/strong\u003e\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eLow latency optimised deployment of Marqo.\u003c/li\u003e\n\u003cli\u003eScale inference at the click of a button.\u003c/li\u003e\n\u003cli\u003eHigh availability.\u003c/li\u003e\n\u003cli\u003e24/7 support.\u003c/li\u003e\n\u003cli\u003eAccess control.\u003c/li\u003e\n\u003cli\u003eLearn more \u003ca href=\"https://www.marqo.ai/cloud\" rel=\"nofollow\"\u003ehere\u003c/a\u003e.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eIntegrations\u003c/h2\u003e\u003ca id=\"user-content-integrations\" class=\"anchor\" aria-label=\"Permalink: Integrations\" href=\"#integrations\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eMarqo is integrated into popular AI and data processing frameworks, with more on the way.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e💙 \u003ca href=\"https://github.com/deepset-ai/haystack\"\u003eHaystack\u003c/a\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eHaystack is an open-source framework for building applications that make use of NLP technology such as LLMs, embedding models and more. This \u003ca href=\"https://haystack.deepset.ai/integrations/marqo-document-store\" rel=\"nofollow\"\u003eintegration\u003c/a\u003e allows you to use Marqo as your Document Store for Haystack pipelines such as retrieval-augmentation, question answering, document search and more.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e🛹 \u003ca href=\"https://github.com/griptape-ai/griptape\"\u003eGriptape\u003c/a\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eGriptape enables safe and reliable deployment of LLM-based agents for enterprise applications, the MarqoVectorStoreDriver gives these agents access to scalable search with your own data. This integration lets you leverage open source or custom fine-tuned models through Marqo to deliver relevant results to your LLMs.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e🦜🔗 \u003ca href=\"https://github.com/langchain-ai/langchain\"\u003eLangchain\u003c/a\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThis integration lets you leverage open source or custom fine tuned models through Marqo for LangChain applications with a vector search component. The Marqo vector store implementation can plug into existing chains such as the Retrieval QA and Conversational Retrieval QA.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003e⋙ \u003ca href=\"https://github.com/DAGWorks-Inc/hamilton/\"\u003eHamilton\u003c/a\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThis integration lets you leverage open source or custom fine tuned models through Marqo for Hamilton LLM applications.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eLearn more about Marqo\u003c/h2\u003e\u003ca id=\"user-content-learn-more-about-marqo\" class=\"anchor\" aria-label=\"Permalink: Learn more about Marqo\" href=\"#learn-more-about-marqo\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003c/th\u003e\n\u003cth\u003e\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e📗 \u003ca href=\"#Getting-started\"\u003eQuick start\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eBuild your first application with Marqo in under 5 minutes.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🖼 \u003ca href=\"https://www.marqo.ai/blog/context-is-all-you-need-multimodal-vector-search-with-personalization\" rel=\"nofollow\"\u003eMarqo for image data\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eBuilding advanced image search with Marqo.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e📚 \u003ca href=\"https://www.marqo.ai/blog/how-i-used-marqo-to-create-a-multilingual-legal-databse-in-5-key-lines-of-code\" rel=\"nofollow\"\u003eMarqo for text\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eBuilding a multilingual database in Marqo.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🔮 \u003ca href=\"https://www.marqo.ai/blog/from-iron-manual-to-ironman-augmenting-gpt-with-marqo-for-fast-editable-memory-to-enable-context-aware-question-answering\" rel=\"nofollow\"\u003eIntegrating Marqo with GPT\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eMaking GPT a subject matter expert by using Marqo as a knowledge base.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🎨 \u003ca href=\"https://www.marqo.ai/blog/combining-stable-diffusion-with-semantic-search-generating-and-categorising-100k-hot-dogs\" rel=\"nofollow\"\u003e Marqo for Creative AI\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eCombining stable diffusion with semantic search to generate and categorise 100k images of hotdogs.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🔊 \u003ca href=\"https://www.marqo.ai/blog/speech-processing\" rel=\"nofollow\"\u003eMarqo and Speech Data\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eAdd diarisation and transcription to preprocess audio for Q\u0026amp;A with Marqo and ChatGPT.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🚫 \u003ca href=\"https://www.marqo.ai/blog/refining-image-quality-and-eliminating-nsfw-content-with-marqo\" rel=\"nofollow\"\u003eMarqo for content moderation\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eBuilding advanced image search with Marqo to find and remove content.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e☁️ \u003ca href=\"https://github.com/marqo-ai/getting_started_marqo_cloud\"\u003eGetting started with Marqo Cloud\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eGo through how to get set up and running with Marqo Cloud starting from your first time login through to building your first application with Marqo\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e👗 \u003ca href=\"https://github.com/marqo-ai/getting_started_marqo_cloud/blob/main/e-commerce-demo/README.md\"\u003eMarqo for e-commerce\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eThis project is a web application with frontend and backend using Python, Flask, ReactJS, and Typescript. The frontend is a ReactJS application that makes requests to the backend which is a Flask application. The backend makes requests to your Marqo cloud API.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🤖 \u003ca href=\"https://github.com/marqo-ai/getting_started_marqo_cloud/tree/main/chatbot-demo\"\u003eMarqo chatbot\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eIn this guide we will build a chat bot application using Marqo and OpenAI's ChatGPT API. We will start with an existing code base and then walk through how to customise the behaviour.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e🦾 \u003ca href=\"#-Core-Features\"\u003eFeatures\u003c/a\u003e\u003c/td\u003e\n\u003ctd\u003eMarqo's core features.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eGetting started\u003c/h2\u003e\u003ca id=\"user-content-getting-started\" class=\"anchor\" aria-label=\"Permalink: Getting started\" href=\"#getting-started\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003col dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eMarqo requires Docker. To install Docker go to the \u003ca href=\"https://docs.docker.com/get-docker/\" rel=\"nofollow\"\u003eDocker Official website\u003c/a\u003e. Ensure that docker has at least 8GB memory and 50GB storage.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eUse docker to run Marqo:\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"docker rm -f marqo\ndocker pull marqoai/marqo:latest\ndocker run --name marqo -p 8882:8882 marqoai/marqo:latest\"\u003e\u003cpre\u003edocker rm -f marqo\ndocker pull marqoai/marqo:latest\ndocker run --name marqo -p 8882:8882 marqoai/marqo:latest\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eNote: If your \u003ccode\u003emarqo\u003c/code\u003e container keeps getting killed, this is most likely due to a lack of memory being allocated to Docker. Increasing the memory limit for Docker to at least 6GB (8GB recommended) in your Docker settings may fix the problem.\u003c/p\u003e\n\u003col start=\"3\" dir=\"auto\"\u003e\n\u003cli\u003eInstall the Marqo client:\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"pip install marqo\"\u003e\u003cpre\u003epip install marqo\u003c/pre\u003e\u003c/div\u003e\n\u003col start=\"4\" dir=\"auto\"\u003e\n\u003cli\u003eStart indexing and searching! Let's look at a simple example below:\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"import marqo\n\nmq = marqo.Client(url='http://localhost:8882')\n\nmq.create_index(\u0026quot;my-first-index\u0026quot;)\n\nmq.index(\u0026quot;my-first-index\u0026quot;).add_documents([\n {\n \u0026quot;Title\u0026quot;: \u0026quot;The Travels of Marco Polo\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;A 13th-century travelogue describing Polo's travels\u0026quot;\n }, \n {\n \u0026quot;Title\u0026quot;: \u0026quot;Extravehicular Mobility Unit (EMU)\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;The EMU is a spacesuit that provides environmental protection, \u0026quot;\n \u0026quot;mobility, life support, and communications for astronauts\u0026quot;,\n \u0026quot;_id\u0026quot;: \u0026quot;article_591\u0026quot;\n }],\n tensor_fields=[\u0026quot;Description\u0026quot;]\n)\n\nresults = mq.index(\u0026quot;my-first-index\u0026quot;).search(\n q=\u0026quot;What is the best outfit to wear on the moon?\u0026quot;\n)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eClient\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eurl\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e'http://localhost:8882'\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003ecreate_index\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eadd_documents\u003c/span\u003e([\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"The Travels of Marco Polo\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A 13th-century travelogue describing Polo's travels\"\u003c/span\u003e\n }, \n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Extravehicular Mobility Unit (EMU)\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"The EMU is a spacesuit that provides environmental protection, \"\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"mobility, life support, and communications for astronauts\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"_id\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"article_591\"\u003c/span\u003e\n }],\n \u003cspan class=\"pl-s1\"\u003etensor_fields\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e[\u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e]\n)\n\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\n \u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"What is the best outfit to wear on the moon?\"\u003c/span\u003e\n)\u003c/pre\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ccode\u003emq\u003c/code\u003e is the client that wraps the \u003ccode\u003emarqo\u003c/code\u003e API.\u003c/li\u003e\n\u003cli\u003e\u003ccode\u003ecreate_index()\u003c/code\u003e creates a new index with default settings. You have the option to specify what model to use. For example, \u003ccode\u003emq.create_index(\"my-first-index\", model=\"hf/all_datasets_v4_MiniLM-L6\")\u003c/code\u003e will create an index with the default text model \u003ccode\u003ehf/all_datasets_v4_MiniLM-L6\u003c/code\u003e. Experimentation with different models is often required to achieve the best retrieval for your specific use case. Different models also offer a tradeoff between inference speed and relevancy. See \u003ca href=\"https://docs.marqo.ai/1.0.0/Models-Reference/dense_retrieval/\" rel=\"nofollow\"\u003ehere\u003c/a\u003e for the full list of models.\u003c/li\u003e\n\u003cli\u003e\u003ccode\u003eadd_documents()\u003c/code\u003e takes a list of documents, represented as python dicts for indexing. \u003ccode\u003etensor_fields\u003c/code\u003e refers to the fields that will be indexed as vector collections and made searchable.\u003c/li\u003e\n\u003cli\u003eYou can optionally set a document's ID with the special \u003ccode\u003e_id\u003c/code\u003e field. Otherwise, Marqo will generate one.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eLet's have a look at the results:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"# let's print out the results:\nimport pprint\npprint.pprint(results)\n\n{\n 'hits': [\n {\n 'Title': 'Extravehicular Mobility Unit (EMU)',\n 'Description': 'The EMU is a spacesuit that provides environmental protection, mobility, life support, and'\n 'communications for astronauts',\n '_highlights': [{\n 'Description': 'The EMU is a spacesuit that provides environmental protection, '\n 'mobility, life support, and communications for astronauts'\n }],\n '_id': 'article_591',\n '_score': 0.61938936\n },\n {\n 'Title': 'The Travels of Marco Polo',\n 'Description': \u0026quot;A 13th-century travelogue describing Polo's travels\u0026quot;,\n '_highlights': [{'Title': 'The Travels of Marco Polo'}],\n '_id': 'e00d1a8d-894c-41a1-8e3b-d8b2a8fce12a',\n '_score': 0.60237324\n }\n ],\n 'limit': 10,\n 'processingTimeMs': 49,\n 'query': 'What is the best outfit to wear on the moon?'\n}\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e# let's print out the results:\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003epprint\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e)\n\n{\n \u003cspan class=\"pl-s\"\u003e'hits'\u003c/span\u003e: [\n {\n \u003cspan class=\"pl-s\"\u003e'Title'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'Extravehicular Mobility Unit (EMU)'\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'Description'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'The EMU is a spacesuit that provides environmental protection, mobility, life support, and'\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e'communications for astronauts'\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'_highlights'\u003c/span\u003e: [{\n \u003cspan class=\"pl-s\"\u003e'Description'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'The EMU is a spacesuit that provides environmental protection, '\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e'mobility, life support, and communications for astronauts'\u003c/span\u003e\n }],\n \u003cspan class=\"pl-s\"\u003e'_id'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'article_591'\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'_score'\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e0.61938936\u003c/span\u003e\n },\n {\n \u003cspan class=\"pl-s\"\u003e'Title'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'The Travels of Marco Polo'\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'Description'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A 13th-century travelogue describing Polo's travels\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'_highlights'\u003c/span\u003e: [{\u003cspan class=\"pl-s\"\u003e'Title'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'The Travels of Marco Polo'\u003c/span\u003e}],\n \u003cspan class=\"pl-s\"\u003e'_id'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'e00d1a8d-894c-41a1-8e3b-d8b2a8fce12a'\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'_score'\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e0.60237324\u003c/span\u003e\n }\n ],\n \u003cspan class=\"pl-s\"\u003e'limit'\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e10\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'processingTimeMs'\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e49\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e'query'\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e'What is the best outfit to wear on the moon?'\u003c/span\u003e\n}\u003c/pre\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eEach hit corresponds to a document that matched the search query.\u003c/li\u003e\n\u003cli\u003eThey are ordered from most to least matching.\u003c/li\u003e\n\u003cli\u003e\u003ccode\u003elimit\u003c/code\u003e is the maximum number of hits to be returned. This can be set as a parameter during search.\u003c/li\u003e\n\u003cli\u003eEach hit has a \u003ccode\u003e_highlights\u003c/code\u003e field. This was the part of the document that matched the query the best.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eOther basic operations\u003c/h2\u003e\u003ca id=\"user-content-other-basic-operations\" class=\"anchor\" aria-label=\"Permalink: Other basic operations\" href=\"#other-basic-operations\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eGet document\u003c/h3\u003e\u003ca id=\"user-content-get-document\" class=\"anchor\" aria-label=\"Permalink: Get document\" href=\"#get-document\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eRetrieve a document by ID.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"result = mq.index(\u0026quot;my-first-index\u0026quot;).get_document(document_id=\u0026quot;article_591\u0026quot;)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresult\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eget_document\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003edocument_id\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"article_591\"\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eNote that by adding the document using \u003ccode\u003eadd_documents\u003c/code\u003e again using the same \u003ccode\u003e_id\u003c/code\u003e will cause a document to be updated.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eGet index stats\u003c/h3\u003e\u003ca id=\"user-content-get-index-stats\" class=\"anchor\" aria-label=\"Permalink: Get index stats\" href=\"#get-index-stats\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eGet information about an index.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"results = mq.index(\u0026quot;my-first-index\u0026quot;).get_stats()\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eget_stats\u003c/span\u003e()\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eLexical search\u003c/h3\u003e\u003ca id=\"user-content-lexical-search\" class=\"anchor\" aria-label=\"Permalink: Lexical search\" href=\"#lexical-search\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003ePerform a keyword search.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"result = mq.index(\u0026quot;my-first-index\u0026quot;).search('marco polo', search_method=marqo.SearchMethods.LEXICAL)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresult\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e'marco polo'\u003c/span\u003e, \u003cspan class=\"pl-s1\"\u003esearch_method\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eSearchMethods\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eLEXICAL\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eMulti modal and cross modal search\u003c/h3\u003e\u003ca id=\"user-content-multi-modal-and-cross-modal-search\" class=\"anchor\" aria-label=\"Permalink: Multi modal and cross modal search\" href=\"#multi-modal-and-cross-modal-search\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eTo power image and text search, Marqo allows users to plug and play with CLIP models from HuggingFace. \u003cstrong\u003eNote that if you do not configure multi modal search, image urls will be treated as strings.\u003c/strong\u003e To start indexing and searching with images, first create an index with a CLIP configuration, as below:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"settings = {\n \u0026quot;treat_urls_and_pointers_as_images\u0026quot;:True, # allows us to find an image file and index it \n \u0026quot;model\u0026quot;:\u0026quot;ViT-L/14\u0026quot;\n}\nresponse = mq.create_index(\u0026quot;my-multimodal-index\u0026quot;, **settings)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003esettings\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e {\n \u003cspan class=\"pl-s\"\u003e\"treat_urls_and_pointers_as_images\"\u003c/span\u003e:\u003cspan class=\"pl-c1\"\u003eTrue\u003c/span\u003e, \u003cspan class=\"pl-c\"\u003e# allows us to find an image file and index it \u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"model\"\u003c/span\u003e:\u003cspan class=\"pl-s\"\u003e\"ViT-L/14\"\u003c/span\u003e\n}\n\u003cspan class=\"pl-s1\"\u003eresponse\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003ecreate_index\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-multimodal-index\"\u003c/span\u003e, \u003cspan class=\"pl-c1\"\u003e**\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003esettings\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eImages can then be added within documents as follows. You can use urls from the internet (for example S3) or from the disk of the machine:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"response = mq.index(\u0026quot;my-multimodal-index\u0026quot;).add_documents([{\n \u0026quot;My_Image\u0026quot;: \u0026quot;https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_realistic.png\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;The hippopotamus, also called the common hippopotamus or river hippopotamus, is a large semiaquatic mammal native to sub-Saharan Africa\u0026quot;,\n \u0026quot;_id\u0026quot;: \u0026quot;hippo-facts\u0026quot;\n}], tensor_fields=[\u0026quot;My_Image\u0026quot;])\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresponse\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eadd_documents\u003c/span\u003e([{\n \u003cspan class=\"pl-s\"\u003e\"My_Image\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_realistic.png\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"The hippopotamus, also called the common hippopotamus or river hippopotamus, is a large semiaquatic mammal native to sub-Saharan Africa\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"_id\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"hippo-facts\"\u003c/span\u003e\n}], \u003cspan class=\"pl-s1\"\u003etensor_fields\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e[\u003cspan class=\"pl-s\"\u003e\"My_Image\"\u003c/span\u003e])\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eYou can then search the image field using text.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"results = mq.index(\u0026quot;my-multimodal-index\u0026quot;).search('animal')\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e'animal'\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eSearching using an image\u003c/h3\u003e\u003ca id=\"user-content-searching-using-an-image\" class=\"anchor\" aria-label=\"Permalink: Searching using an image\" href=\"#searching-using-an-image\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eSearching using an image can be achieved by providing the image link.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"results = mq.index(\u0026quot;my-multimodal-index\u0026quot;).search('https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_statue.png')\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e'https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_statue.png'\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eSearching using weights in queries\u003c/h3\u003e\u003ca id=\"user-content-searching-using-weights-in-queries\" class=\"anchor\" aria-label=\"Permalink: Searching using weights in queries\" href=\"#searching-using-weights-in-queries\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eQueries can also be provided as dictionaries where each key is a query and their corresponding values are weights. This allows for more advanced queries consisting of multiple components with weightings towards or against them, queries can have negations via negative weighting.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe example below shows the application of this to a scenario where a user may want to ask a question but also negate results that match a certain semantic criterion.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"import marqo\nimport pprint\n\nmq = marqo.Client(url=\u0026quot;http://localhost:8882\u0026quot;)\n\nmq.create_index(\u0026quot;my-weighted-query-index\u0026quot;)\n\nmq.index(\u0026quot;my-weighted-query-index\u0026quot;).add_documents(\n [\n {\n \u0026quot;Title\u0026quot;: \u0026quot;Smartphone\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;A smartphone is a portable computer device that combines mobile telephone \u0026quot;\n \u0026quot;functions and computing functions into one unit.\u0026quot;,\n },\n {\n \u0026quot;Title\u0026quot;: \u0026quot;Telephone\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;A telephone is a telecommunications device that permits two or more users to\u0026quot;\n \u0026quot;conduct a conversation when they are too far apart to be easily heard directly.\u0026quot;,\n },\n {\n \u0026quot;Title\u0026quot;: \u0026quot;Thylacine\u0026quot;,\n \u0026quot;Description\u0026quot;: \u0026quot;The thylacine, also commonly known as the Tasmanian tiger or Tasmanian wolf, \u0026quot;\n \u0026quot;is an extinct carnivorous marsupial.\u0026quot;\n \u0026quot;The last known of its species died in 1936.\u0026quot;,\n }\n ],\n tensor_fields=[\u0026quot;Description\u0026quot;]\n)\n\n# initially we ask for a type of communications device which is popular in the 21st century\nquery = {\n # a weighting of 1.1 gives this query slightly more importance\n \u0026quot;I need to buy a communications device, what should I get?\u0026quot;: 1.1,\n # a weighting of 1 gives this query a neutral importance\n # this will lead to 'Smartphone' being the top result\n \u0026quot;The device should work like an intelligent computer.\u0026quot;: 1.0,\n}\n\nresults = mq.index(\u0026quot;my-weighted-query-index\u0026quot;).search(q=query)\n\nprint(\u0026quot;Query 1:\u0026quot;)\npprint.pprint(results)\n\n# now we ask for a type of communications which predates the 21st century\nquery = {\n # a weighting of 1 gives this query a neutral importance\n \u0026quot;I need to buy a communications device, what should I get?\u0026quot;: 1.0,\n # a weighting of -1 gives this query a negation effect\n # this will lead to 'Telephone' being the top result\n \u0026quot;The device should work like an intelligent computer.\u0026quot;: -0.3,\n}\n\nresults = mq.index(\u0026quot;my-weighted-query-index\u0026quot;).search(q=query)\n\nprint(\u0026quot;\\nQuery 2:\u0026quot;)\npprint.pprint(results)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eClient\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eurl\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"http://localhost:8882\"\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003ecreate_index\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-weighted-query-index\"\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-weighted-query-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eadd_documents\u003c/span\u003e(\n [\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Smartphone\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A smartphone is a portable computer device that combines mobile telephone \"\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"functions and computing functions into one unit.\"\u003c/span\u003e,\n },\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Telephone\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A telephone is a telecommunications device that permits two or more users to\"\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"conduct a conversation when they are too far apart to be easily heard directly.\"\u003c/span\u003e,\n },\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Thylacine\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"The thylacine, also commonly known as the Tasmanian tiger or Tasmanian wolf, \"\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"is an extinct carnivorous marsupial.\"\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"The last known of its species died in 1936.\"\u003c/span\u003e,\n }\n ],\n \u003cspan class=\"pl-s1\"\u003etensor_fields\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e[\u003cspan class=\"pl-s\"\u003e\"Description\"\u003c/span\u003e]\n)\n\n\u003cspan class=\"pl-c\"\u003e# initially we ask for a type of communications device which is popular in the 21st century\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003equery\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e {\n \u003cspan class=\"pl-c\"\u003e# a weighting of 1.1 gives this query slightly more importance\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"I need to buy a communications device, what should I get?\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e1.1\u003c/span\u003e,\n \u003cspan class=\"pl-c\"\u003e# a weighting of 1 gives this query a neutral importance\u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e# this will lead to 'Smartphone' being the top result\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"The device should work like an intelligent computer.\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e,\n}\n\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-weighted-query-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003equery\u003c/span\u003e)\n\n\u003cspan class=\"pl-en\"\u003eprint\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"Query 1:\"\u003c/span\u003e)\n\u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003epprint\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e)\n\n\u003cspan class=\"pl-c\"\u003e# now we ask for a type of communications which predates the 21st century\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003equery\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e {\n \u003cspan class=\"pl-c\"\u003e# a weighting of 1 gives this query a neutral importance\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"I need to buy a communications device, what should I get?\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e,\n \u003cspan class=\"pl-c\"\u003e# a weighting of -1 gives this query a negation effect\u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e# this will lead to 'Telephone' being the top result\u003c/span\u003e\n \u003cspan class=\"pl-s\"\u003e\"The device should work like an intelligent computer.\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e-\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e0.3\u003c/span\u003e,\n}\n\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-weighted-query-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003equery\u003c/span\u003e)\n\n\u003cspan class=\"pl-en\"\u003eprint\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"\u003cspan class=\"pl-cce\"\u003e\\n\u003c/span\u003eQuery 2:\"\u003c/span\u003e)\n\u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003epprint\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eCreating and searching indexes with multimodal combination fields\u003c/h3\u003e\u003ca id=\"user-content-creating-and-searching-indexes-with-multimodal-combination-fields\" class=\"anchor\" aria-label=\"Permalink: Creating and searching indexes with multimodal combination fields\" href=\"#creating-and-searching-indexes-with-multimodal-combination-fields\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eMarqo lets you have indexes with multimodal combination fields. Multimodal combination fields can combine text and images into one field. This allows scoring of documents across the combined text and image fields together. It also allows for a single vector representation instead of needing many which saves on storage. The relative weighting of each component can be set per document.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe example below demonstrates this with retrieval of caption and image pairs using multiple types of queries.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"import marqo\nimport pprint\n\nmq = marqo.Client(url=\u0026quot;http://localhost:8882\u0026quot;)\n\nsettings = {\u0026quot;treat_urls_and_pointers_as_images\u0026quot;: True, \u0026quot;model\u0026quot;: \u0026quot;ViT-L/14\u0026quot;}\n\nmq.create_index(\u0026quot;my-first-multimodal-index\u0026quot;, **settings)\n\nmq.index(\u0026quot;my-first-multimodal-index\u0026quot;).add_documents(\n [\n {\n \u0026quot;Title\u0026quot;: \u0026quot;Flying Plane\u0026quot;,\n \u0026quot;caption\u0026quot;: \u0026quot;An image of a passenger plane flying in front of the moon.\u0026quot;,\n \u0026quot;image\u0026quot;: \u0026quot;https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image2.jpg\u0026quot;,\n },\n {\n \u0026quot;Title\u0026quot;: \u0026quot;Red Bus\u0026quot;,\n \u0026quot;caption\u0026quot;: \u0026quot;A red double decker London bus traveling to Aldwych\u0026quot;,\n \u0026quot;image\u0026quot;: \u0026quot;https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image4.jpg\u0026quot;,\n },\n {\n \u0026quot;Title\u0026quot;: \u0026quot;Horse Jumping\u0026quot;,\n \u0026quot;caption\u0026quot;: \u0026quot;A person riding a horse over a jump in a competition.\u0026quot;,\n \u0026quot;image\u0026quot;: \u0026quot;https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image1.jpg\u0026quot;,\n },\n ],\n # Create the mappings, here we define our captioned_image mapping \n # which weights the image more heavily than the caption - these pairs \n # will be represented by a single vector in the index\n mappings={\n \u0026quot;captioned_image\u0026quot;: {\n \u0026quot;type\u0026quot;: \u0026quot;multimodal_combination\u0026quot;,\n \u0026quot;weights\u0026quot;: {\n \u0026quot;caption\u0026quot;: 0.3,\n \u0026quot;image\u0026quot;: 0.7\n }\n }\n },\n # We specify which fields to create vectors for. \n # Note that captioned_image is treated as a single field.\n tensor_fields=[\u0026quot;captioned_image\u0026quot;]\n)\n\n# Search this index with a simple text query\nresults = mq.index(\u0026quot;my-first-multimodal-index\u0026quot;).search(\n q=\u0026quot;Give me some images of vehicles and modes of transport. I am especially interested in air travel and commercial aeroplanes.\u0026quot;\n)\n\nprint(\u0026quot;Query 1:\u0026quot;)\npprint.pprint(results)\n\n# search the index with a query that uses weighted components\nresults = mq.index(\u0026quot;my-first-multimodal-index\u0026quot;).search(\n q={\n \u0026quot;What are some vehicles and modes of transport?\u0026quot;: 1.0,\n \u0026quot;Aeroplanes and other things that fly\u0026quot;: -1.0\n },\n)\nprint(\u0026quot;\\nQuery 2:\u0026quot;)\npprint.pprint(results)\n\nresults = mq.index(\u0026quot;my-first-multimodal-index\u0026quot;).search(\n q={\u0026quot;Animals of the Perissodactyla order\u0026quot;: -1.0}\n)\nprint(\u0026quot;\\nQuery 3:\u0026quot;)\npprint.pprint(results)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003eimport\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emarqo\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eClient\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eurl\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"http://localhost:8882\"\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003esettings\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e {\u003cspan class=\"pl-s\"\u003e\"treat_urls_and_pointers_as_images\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003eTrue\u003c/span\u003e, \u003cspan class=\"pl-s\"\u003e\"model\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"ViT-L/14\"\u003c/span\u003e}\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003ecreate_index\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-multimodal-index\"\u003c/span\u003e, \u003cspan class=\"pl-c1\"\u003e**\u003c/span\u003e\u003cspan class=\"pl-s1\"\u003esettings\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003eadd_documents\u003c/span\u003e(\n [\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Flying Plane\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"caption\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"An image of a passenger plane flying in front of the moon.\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"image\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image2.jpg\"\u003c/span\u003e,\n },\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Red Bus\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"caption\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A red double decker London bus traveling to Aldwych\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"image\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image4.jpg\"\u003c/span\u003e,\n },\n {\n \u003cspan class=\"pl-s\"\u003e\"Title\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"Horse Jumping\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"caption\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"A person riding a horse over a jump in a competition.\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"image\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image1.jpg\"\u003c/span\u003e,\n },\n ],\n \u003cspan class=\"pl-c\"\u003e# Create the mappings, here we define our captioned_image mapping \u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e# which weights the image more heavily than the caption - these pairs \u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e# will be represented by a single vector in the index\u003c/span\u003e\n \u003cspan class=\"pl-s1\"\u003emappings\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e{\n \u003cspan class=\"pl-s\"\u003e\"captioned_image\"\u003c/span\u003e: {\n \u003cspan class=\"pl-s\"\u003e\"type\"\u003c/span\u003e: \u003cspan class=\"pl-s\"\u003e\"multimodal_combination\"\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"weights\"\u003c/span\u003e: {\n \u003cspan class=\"pl-s\"\u003e\"caption\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e0.3\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"image\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e0.7\u003c/span\u003e\n }\n }\n },\n \u003cspan class=\"pl-c\"\u003e# We specify which fields to create vectors for. \u003c/span\u003e\n \u003cspan class=\"pl-c\"\u003e# Note that captioned_image is treated as a single field.\u003c/span\u003e\n \u003cspan class=\"pl-s1\"\u003etensor_fields\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e[\u003cspan class=\"pl-s\"\u003e\"captioned_image\"\u003c/span\u003e]\n)\n\n\u003cspan class=\"pl-c\"\u003e# Search this index with a simple text query\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\n \u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e\u003cspan class=\"pl-s\"\u003e\"Give me some images of vehicles and modes of transport. I am especially interested in air travel and commercial aeroplanes.\"\u003c/span\u003e\n)\n\n\u003cspan class=\"pl-en\"\u003eprint\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"Query 1:\"\u003c/span\u003e)\n\u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003epprint\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e)\n\n\u003cspan class=\"pl-c\"\u003e# search the index with a query that uses weighted components\u003c/span\u003e\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\n \u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e{\n \u003cspan class=\"pl-s\"\u003e\"What are some vehicles and modes of transport?\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e,\n \u003cspan class=\"pl-s\"\u003e\"Aeroplanes and other things that fly\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e-\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e\n },\n)\n\u003cspan class=\"pl-en\"\u003eprint\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"\u003cspan class=\"pl-cce\"\u003e\\n\u003c/span\u003eQuery 2:\"\u003c/span\u003e)\n\u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003epprint\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e)\n\n\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-multimodal-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003esearch\u003c/span\u003e(\n \u003cspan class=\"pl-s1\"\u003eq\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e{\u003cspan class=\"pl-s\"\u003e\"Animals of the Perissodactyla order\"\u003c/span\u003e: \u003cspan class=\"pl-c1\"\u003e-\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e}\n)\n\u003cspan class=\"pl-en\"\u003eprint\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"\u003cspan class=\"pl-cce\"\u003e\\n\u003c/span\u003eQuery 3:\"\u003c/span\u003e)\n\u003cspan class=\"pl-s1\"\u003epprint\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003epprint\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e)\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDelete documents\u003c/h3\u003e\u003ca id=\"user-content-delete-documents\" class=\"anchor\" aria-label=\"Permalink: Delete documents\" href=\"#delete-documents\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eDelete documents.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"\nresults = mq.index(\u0026quot;my-first-index\u0026quot;).delete_documents(ids=[\u0026quot;article_591\u0026quot;, \u0026quot;article_602\u0026quot;])\n\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003edelete_documents\u003c/span\u003e(\u003cspan class=\"pl-s1\"\u003eids\u003c/span\u003e\u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e[\u003cspan class=\"pl-s\"\u003e\"article_591\"\u003c/span\u003e, \u003cspan class=\"pl-s\"\u003e\"article_602\"\u003c/span\u003e])\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDelete index\u003c/h3\u003e\u003ca id=\"user-content-delete-index\" class=\"anchor\" aria-label=\"Permalink: Delete index\" href=\"#delete-index\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eDelete an index.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-python notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"results = mq.index(\u0026quot;my-first-index\u0026quot;).delete()\"\u003e\u003cpre\u003e\u003cspan class=\"pl-s1\"\u003eresults\u003c/span\u003e \u003cspan class=\"pl-c1\"\u003e=\u003c/span\u003e \u003cspan class=\"pl-s1\"\u003emq\u003c/span\u003e.\u003cspan class=\"pl-c1\"\u003eindex\u003c/span\u003e(\u003cspan class=\"pl-s\"\u003e\"my-first-index\"\u003c/span\u003e).\u003cspan class=\"pl-c1\"\u003edelete\u003c/span\u003e()\u003c/pre\u003e\u003c/div\u003e\n\u003ch2 dir=\"auto\"\u003e\u003c/h2\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eRunning Marqo open source in production\u003c/h2\u003e\u003ca id=\"user-content-running-marqo-open-source-in-production\" class=\"anchor\" aria-label=\"Permalink: Running Marqo open source in production\" href=\"#running-marqo-open-source-in-production\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eWe support Kubernetes templates for Marqo which you can deploy on a cloud provider of your choice. Marqo's Kubernetes implementation allows you to deploy clusters with replicas, multiple storage shards and multiple inference nodes. The repo can be found here: \u003ca href=\"https://github.com/marqo-ai/marqo-on-kubernetes\"\u003ehttps://github.com/marqo-ai/marqo-on-kubernetes\u003c/a\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eIf you're looking for a fully managed cloud service, you can sign up for Marqo Cloud here: \u003ca href=\"https://cloud.marqo.ai\" rel=\"nofollow\"\u003ehttps://cloud.marqo.ai\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDocumentation\u003c/h2\u003e\u003ca id=\"user-content-documentation\" class=\"anchor\" aria-label=\"Permalink: Documentation\" href=\"#documentation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe full documentation for Marqo can be found here \u003ca href=\"https://docs.marqo.ai/\" rel=\"nofollow\"\u003ehttps://docs.marqo.ai/\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eWarning\u003c/h2\u003e\u003ca id=\"user-content-warning\" class=\"anchor\" aria-label=\"Permalink: Warning\" href=\"#warning\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eNote that you should not run other applications on Marqo's Vespa cluster as Marqo automatically changes and adapts the settings on the cluster.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eContributors\u003c/h2\u003e\u003ca id=\"user-content-contributors\" class=\"anchor\" aria-label=\"Permalink: Contributors\" href=\"#contributors\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eMarqo is a community project with the goal of making tensor search accessible to the wider developer community. We are glad that you are interested in helping out! Please read \u003ca href=\"/marqo-ai/marqo/blob/mainline/CONTRIBUTING.md\"\u003ethis\u003c/a\u003e to get started.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDev setup\u003c/h2\u003e\u003ca id=\"user-content-dev-setup\" class=\"anchor\" aria-label=\"Permalink: Dev setup\" href=\"#dev-setup\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003col dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eCreate a virtual env \u003ccode\u003epython -m venv ./venv\u003c/code\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eActivate the virtual environment \u003ccode\u003esource ./venv/bin/activate\u003c/code\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eInstall requirements from the requirements file: \u003ccode\u003epip install -r requirements.txt\u003c/code\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eRun tests by running the tox file. CD into this dir and then run \"tox\".\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eIf you update dependencies, make sure to delete the .tox dir and rerun.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eMerge instructions:\u003c/h2\u003e\u003ca id=\"user-content-merge-instructions\" class=\"anchor\" aria-label=\"Permalink: Merge instructions:\" href=\"#merge-instructions\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003col dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eRun the full test suite (by using the command \u003ccode\u003etox\u003c/code\u003e in this dir).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eCreate a pull request with an attached github issue.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eSupport\u003c/h2\u003e\u003ca id=\"user-content-support\" class=\"anchor\" aria-label=\"Permalink: Support\" href=\"#support\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eAsk questions and share your creations with the community on our \u003ca href=\"https://community.marqo.ai\" rel=\"nofollow\"\u003eDiscourse forum\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003eJoin our \u003ca href=\"https://bit.ly/marqo-community-slack\" rel=\"nofollow\"\u003eSlack community\u003c/a\u003e and chat with other community members about ideas.\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/article\u003e","loaded":true,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":[{"level":2,"text":"Marqo","anchor":"marqo","htmlText":"Marqo"},{"level":2,"text":"✨ Core Features","anchor":"-core-features","htmlText":"✨ Core Features"},{"level":2,"text":"Integrations","anchor":"integrations","htmlText":"Integrations"},{"level":2,"text":"Learn more about Marqo","anchor":"learn-more-about-marqo","htmlText":"Learn more about Marqo"},{"level":2,"text":"Getting started","anchor":"getting-started","htmlText":"Getting started"},{"level":2,"text":"Other basic operations","anchor":"other-basic-operations","htmlText":"Other basic operations"},{"level":3,"text":"Get document","anchor":"get-document","htmlText":"Get document"},{"level":3,"text":"Get index stats","anchor":"get-index-stats","htmlText":"Get index stats"},{"level":3,"text":"Lexical search","anchor":"lexical-search","htmlText":"Lexical search"},{"level":3,"text":"Multi modal and cross modal search","anchor":"multi-modal-and-cross-modal-search","htmlText":"Multi modal and cross modal search"},{"level":3,"text":"Searching using an image","anchor":"searching-using-an-image","htmlText":"Searching using an image"},{"level":3,"text":"Searching using weights in queries","anchor":"searching-using-weights-in-queries","htmlText":"Searching using weights in queries"},{"level":3,"text":"Creating and searching indexes with multimodal combination fields","anchor":"creating-and-searching-indexes-with-multimodal-combination-fields","htmlText":"Creating and searching indexes with multimodal combination fields"},{"level":3,"text":"Delete documents","anchor":"delete-documents","htmlText":"Delete documents"},{"level":3,"text":"Delete index","anchor":"delete-index","htmlText":"Delete index"},{"level":2,"text":"Running Marqo open source in production","anchor":"running-marqo-open-source-in-production","htmlText":"Running Marqo open source in production"},{"level":2,"text":"Documentation","anchor":"documentation","htmlText":"Documentation"},{"level":2,"text":"Warning","anchor":"warning","htmlText":"Warning"},{"level":2,"text":"Contributors","anchor":"contributors","htmlText":"Contributors"},{"level":2,"text":"Dev setup","anchor":"dev-setup","htmlText":"Dev setup"},{"level":2,"text":"Merge instructions:","anchor":"merge-instructions","htmlText":"Merge instructions:"},{"level":2,"text":"Support","anchor":"support","htmlText":"Support"}],"siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Fmarqo-ai%2Fmarqo"}},{"displayName":"CODE_OF_CONDUCT.md","repoName":"marqo","refName":"mainline","path":"CODE_OF_CONDUCT.md","preferredFileType":"code_of_conduct","tabName":"Code of 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1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Marqo is more than a vector database, it's an end-to-end vector search engine for both text and images. Vector generation, storage and retrieval are handled out of the box through a single API. No need to bring your own embeddings.</p> <p dir="auto"><strong>Why Marqo?</strong></p> <p dir="auto">Vector similarity alone is not enough for vector search. Vector search requires more than a vector database - it also requires machine learning (ML) deployment and management, preprocessing and transformations of inputs as well as the ability to modify search behavior without retraining a model. Marqo contains all these pieces, enabling developers to build vector search into their application with minimal effort. A full list of features can be found <a href="#-core-features">below</a>.</p> <p dir="auto"><strong>Why bundle embedding generation with vector search?</strong></p> <p dir="auto">Vector databases are specialized components for vector similarity and only service one component of a vector search system. They are “vectors in - vectors out”. They still require the production of vectors, management of the ML models, associated orchestration and processing of the inputs. Marqo makes this easy by being “documents in, documents out”. Preprocessing of text and images, embedding the content, storing meta-data and deployment of inference and storage is all taken care of by Marqo.</p> <p dir="auto"><strong>Quick start</strong></p> <p dir="auto">Here is a code snippet for a minimal example of vector search with Marqo (see <a href="#getting-started">Getting Started</a>):</p> <ol dir="auto"> <li> <p dir="auto">Marqo requires Docker. To install Docker go to the <a href="https://docs.docker.com/get-docker/" rel="nofollow">Docker Official website</a>. Ensure that docker has at least 8GB memory and 50GB storage. In Docker desktop, you can do this by clicking the settings icon, then resources, and selecting 8GB memory.</p> </li> <li> <p dir="auto">Use docker to run Marqo:</p> </li> </ol> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content=" docker rm -f marqo docker pull marqoai/marqo:latest docker run --name marqo -it -p 8882:8882 marqoai/marqo:latest "><pre>docker rm -f marqo docker pull marqoai/marqo:latest docker run --name marqo -it -p 8882:8882 marqoai/marqo:latest </pre></div> <ol start="3" dir="auto"> <li>Install the Marqo client:</li> </ol> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install marqo"><pre>pip install marqo</pre></div> <ol start="4" dir="auto"> <li>Start indexing and searching! Let's look at a simple example below:</li> </ol> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import marqo mq = marqo.Client(url='http://localhost:8882') mq.create_index("my-first-index", model="hf/e5-base-v2") mq.index("my-first-index").add_documents([ { "Title": "The Travels of Marco Polo", "Description": "A 13th-century travelogue describing Polo's travels" }, { "Title": "Extravehicular Mobility Unit (EMU)", "Description": "The EMU is a spacesuit that provides environmental protection, " "mobility, life support, and communications for astronauts", "_id": "article_591" }], tensor_fields=["Description"] ) results = mq.index("my-first-index").search( q="What is the best outfit to wear on the moon?" ) "><pre><span class="pl-k">import</span> <span class="pl-s1">marqo</span> <span class="pl-s1">mq</span> <span class="pl-c1">=</span> <span class="pl-s1">marqo</span>.<span class="pl-c1">Client</span>(<span class="pl-s1">url</span><span class="pl-c1">=</span><span class="pl-s">'http://localhost:8882'</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">create_index</span>(<span class="pl-s">"my-first-index"</span>, <span class="pl-s1">model</span><span class="pl-c1">=</span><span class="pl-s">"hf/e5-base-v2"</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">add_documents</span>([ { <span class="pl-s">"Title"</span>: <span class="pl-s">"The Travels of Marco Polo"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"A 13th-century travelogue describing Polo's travels"</span> }, { <span class="pl-s">"Title"</span>: <span class="pl-s">"Extravehicular Mobility Unit (EMU)"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"The EMU is a spacesuit that provides environmental protection, "</span> <span class="pl-s">"mobility, life support, and communications for astronauts"</span>, <span class="pl-s">"_id"</span>: <span class="pl-s">"article_591"</span> }], <span class="pl-s1">tensor_fields</span><span class="pl-c1">=</span>[<span class="pl-s">"Description"</span>] ) <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">search</span>( <span class="pl-s1">q</span><span class="pl-c1">=</span><span class="pl-s">"What is the best outfit to wear on the moon?"</span> )</pre></div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">✨ Core Features</h2><a id="user-content--core-features" class="anchor" aria-label="Permalink: ✨ Core Features" href="#-core-features"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><strong>🤖 State of the art embeddings</strong></p> <ul dir="auto"> <li>Use the latest machine learning models from PyTorch, Huggingface, OpenAI and more.</li> <li>Start with a pre-configured model or bring your own.</li> <li>CPU and GPU support.</li> </ul> <p dir="auto"><strong>⚡ Performance</strong></p> <ul dir="auto"> <li>Embeddings stored in in-memory HNSW indexes, achieving cutting edge search speeds.</li> <li>Scale to hundred-million document indexes with horizontal index sharding.</li> <li>Async and non-blocking data upload and search.</li> </ul> <p dir="auto"><strong>🌌 Documents-in-documents-out</strong></p> <ul dir="auto"> <li>Vector generation, storage, and retrieval are provided out of the box.</li> <li>Build search, entity resolution, and data exploration application with using your text and images.</li> <li>Build complex semantic queries by combining weighted search terms.</li> <li>Filter search results using Marqo’s query DSL.</li> <li>Store unstructured data and semi-structured metadata together in documents, using a range of supported datatypes like bools, ints and keywords.</li> </ul> <p dir="auto"><strong>🍱 Managed cloud</strong></p> <ul dir="auto"> <li>Low latency optimised deployment of Marqo.</li> <li>Scale inference at the click of a button.</li> <li>High availability.</li> <li>24/7 support.</li> <li>Access control.</li> <li>Learn more <a href="https://www.marqo.ai/cloud" rel="nofollow">here</a>.</li> </ul> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Integrations</h2><a id="user-content-integrations" class="anchor" aria-label="Permalink: Integrations" href="#integrations"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Marqo is integrated into popular AI and data processing frameworks, with more on the way.</p> <p dir="auto"><strong>💙 <a href="https://github.com/deepset-ai/haystack">Haystack</a></strong></p> <p dir="auto">Haystack is an open-source framework for building applications that make use of NLP technology such as LLMs, embedding models and more. This <a href="https://haystack.deepset.ai/integrations/marqo-document-store" rel="nofollow">integration</a> allows you to use Marqo as your Document Store for Haystack pipelines such as retrieval-augmentation, question answering, document search and more.</p> <p dir="auto"><strong>🛹 <a href="https://github.com/griptape-ai/griptape">Griptape</a></strong></p> <p dir="auto">Griptape enables safe and reliable deployment of LLM-based agents for enterprise applications, the MarqoVectorStoreDriver gives these agents access to scalable search with your own data. This integration lets you leverage open source or custom fine-tuned models through Marqo to deliver relevant results to your LLMs.</p> <p dir="auto"><strong>🦜🔗 <a href="https://github.com/langchain-ai/langchain">Langchain</a></strong></p> <p dir="auto">This integration lets you leverage open source or custom fine tuned models through Marqo for LangChain applications with a vector search component. The Marqo vector store implementation can plug into existing chains such as the Retrieval QA and Conversational Retrieval QA.</p> <p dir="auto"><strong>⋙ <a href="https://github.com/DAGWorks-Inc/hamilton/">Hamilton</a></strong></p> <p dir="auto">This integration lets you leverage open source or custom fine tuned models through Marqo for Hamilton LLM applications.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Learn more about Marqo</h2><a id="user-content-learn-more-about-marqo" class="anchor" aria-label="Permalink: Learn more about Marqo" href="#learn-more-about-marqo"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <markdown-accessiblity-table><table> <thead> <tr> <th></th> <th></th> </tr> </thead> <tbody> <tr> <td>📗 <a href="#Getting-started">Quick start</a></td> <td>Build your first application with Marqo in under 5 minutes.</td> </tr> <tr> <td>🖼 <a href="https://www.marqo.ai/blog/context-is-all-you-need-multimodal-vector-search-with-personalization" rel="nofollow">Marqo for image data</a></td> <td>Building advanced image search with Marqo.</td> </tr> <tr> <td>📚 <a href="https://www.marqo.ai/blog/how-i-used-marqo-to-create-a-multilingual-legal-databse-in-5-key-lines-of-code" rel="nofollow">Marqo for text</a></td> <td>Building a multilingual database in Marqo.</td> </tr> <tr> <td>🔮 <a href="https://www.marqo.ai/blog/from-iron-manual-to-ironman-augmenting-gpt-with-marqo-for-fast-editable-memory-to-enable-context-aware-question-answering" rel="nofollow">Integrating Marqo with GPT</a></td> <td>Making GPT a subject matter expert by using Marqo as a knowledge base.</td> </tr> <tr> <td>🎨 <a href="https://www.marqo.ai/blog/combining-stable-diffusion-with-semantic-search-generating-and-categorising-100k-hot-dogs" rel="nofollow"> Marqo for Creative AI</a></td> <td>Combining stable diffusion with semantic search to generate and categorise 100k images of hotdogs.</td> </tr> <tr> <td>🔊 <a href="https://www.marqo.ai/blog/speech-processing" rel="nofollow">Marqo and Speech Data</a></td> <td>Add diarisation and transcription to preprocess audio for Q&A with Marqo and ChatGPT.</td> </tr> <tr> <td>🚫 <a href="https://www.marqo.ai/blog/refining-image-quality-and-eliminating-nsfw-content-with-marqo" rel="nofollow">Marqo for content moderation</a></td> <td>Building advanced image search with Marqo to find and remove content.</td> </tr> <tr> <td>☁️ <a href="https://github.com/marqo-ai/getting_started_marqo_cloud">Getting started with Marqo Cloud</a></td> <td>Go through how to get set up and running with Marqo Cloud starting from your first time login through to building your first application with Marqo</td> </tr> <tr> <td>👗 <a href="https://github.com/marqo-ai/getting_started_marqo_cloud/blob/main/e-commerce-demo/README.md">Marqo for e-commerce</a></td> <td>This project is a web application with frontend and backend using Python, Flask, ReactJS, and Typescript. The frontend is a ReactJS application that makes requests to the backend which is a Flask application. The backend makes requests to your Marqo cloud API.</td> </tr> <tr> <td>🤖 <a href="https://github.com/marqo-ai/getting_started_marqo_cloud/tree/main/chatbot-demo">Marqo chatbot</a></td> <td>In this guide we will build a chat bot application using Marqo and OpenAI's ChatGPT API. We will start with an existing code base and then walk through how to customise the behaviour.</td> </tr> <tr> <td>🦾 <a href="#-Core-Features">Features</a></td> <td>Marqo's core features.</td> </tr> </tbody> </table></markdown-accessiblity-table> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Getting started</h2><a id="user-content-getting-started" class="anchor" aria-label="Permalink: Getting started" href="#getting-started"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ol dir="auto"> <li> <p dir="auto">Marqo requires Docker. To install Docker go to the <a href="https://docs.docker.com/get-docker/" rel="nofollow">Docker Official website</a>. Ensure that docker has at least 8GB memory and 50GB storage.</p> </li> <li> <p dir="auto">Use docker to run Marqo:</p> </li> </ol> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="docker rm -f marqo docker pull marqoai/marqo:latest docker run --name marqo -p 8882:8882 marqoai/marqo:latest"><pre>docker rm -f marqo docker pull marqoai/marqo:latest docker run --name marqo -p 8882:8882 marqoai/marqo:latest</pre></div> <p dir="auto">Note: If your <code>marqo</code> container keeps getting killed, this is most likely due to a lack of memory being allocated to Docker. Increasing the memory limit for Docker to at least 6GB (8GB recommended) in your Docker settings may fix the problem.</p> <ol start="3" dir="auto"> <li>Install the Marqo client:</li> </ol> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="pip install marqo"><pre>pip install marqo</pre></div> <ol start="4" dir="auto"> <li>Start indexing and searching! Let's look at a simple example below:</li> </ol> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import marqo mq = marqo.Client(url='http://localhost:8882') mq.create_index("my-first-index") mq.index("my-first-index").add_documents([ { "Title": "The Travels of Marco Polo", "Description": "A 13th-century travelogue describing Polo's travels" }, { "Title": "Extravehicular Mobility Unit (EMU)", "Description": "The EMU is a spacesuit that provides environmental protection, " "mobility, life support, and communications for astronauts", "_id": "article_591" }], tensor_fields=["Description"] ) results = mq.index("my-first-index").search( q="What is the best outfit to wear on the moon?" )"><pre><span class="pl-k">import</span> <span class="pl-s1">marqo</span> <span class="pl-s1">mq</span> <span class="pl-c1">=</span> <span class="pl-s1">marqo</span>.<span class="pl-c1">Client</span>(<span class="pl-s1">url</span><span class="pl-c1">=</span><span class="pl-s">'http://localhost:8882'</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">create_index</span>(<span class="pl-s">"my-first-index"</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">add_documents</span>([ { <span class="pl-s">"Title"</span>: <span class="pl-s">"The Travels of Marco Polo"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"A 13th-century travelogue describing Polo's travels"</span> }, { <span class="pl-s">"Title"</span>: <span class="pl-s">"Extravehicular Mobility Unit (EMU)"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"The EMU is a spacesuit that provides environmental protection, "</span> <span class="pl-s">"mobility, life support, and communications for astronauts"</span>, <span class="pl-s">"_id"</span>: <span class="pl-s">"article_591"</span> }], <span class="pl-s1">tensor_fields</span><span class="pl-c1">=</span>[<span class="pl-s">"Description"</span>] ) <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">search</span>( <span class="pl-s1">q</span><span class="pl-c1">=</span><span class="pl-s">"What is the best outfit to wear on the moon?"</span> )</pre></div> <ul dir="auto"> <li><code>mq</code> is the client that wraps the <code>marqo</code> API.</li> <li><code>create_index()</code> creates a new index with default settings. You have the option to specify what model to use. For example, <code>mq.create_index("my-first-index", model="hf/all_datasets_v4_MiniLM-L6")</code> will create an index with the default text model <code>hf/all_datasets_v4_MiniLM-L6</code>. Experimentation with different models is often required to achieve the best retrieval for your specific use case. Different models also offer a tradeoff between inference speed and relevancy. See <a href="https://docs.marqo.ai/1.0.0/Models-Reference/dense_retrieval/" rel="nofollow">here</a> for the full list of models.</li> <li><code>add_documents()</code> takes a list of documents, represented as python dicts for indexing. <code>tensor_fields</code> refers to the fields that will be indexed as vector collections and made searchable.</li> <li>You can optionally set a document's ID with the special <code>_id</code> field. Otherwise, Marqo will generate one.</li> </ul> <p dir="auto">Let's have a look at the results:</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="# let's print out the results: import pprint pprint.pprint(results) { 'hits': [ { 'Title': 'Extravehicular Mobility Unit (EMU)', 'Description': 'The EMU is a spacesuit that provides environmental protection, mobility, life support, and' 'communications for astronauts', '_highlights': [{ 'Description': 'The EMU is a spacesuit that provides environmental protection, ' 'mobility, life support, and communications for astronauts' }], '_id': 'article_591', '_score': 0.61938936 }, { 'Title': 'The Travels of Marco Polo', 'Description': "A 13th-century travelogue describing Polo's travels", '_highlights': [{'Title': 'The Travels of Marco Polo'}], '_id': 'e00d1a8d-894c-41a1-8e3b-d8b2a8fce12a', '_score': 0.60237324 } ], 'limit': 10, 'processingTimeMs': 49, 'query': 'What is the best outfit to wear on the moon?' }"><pre><span class="pl-c"># let's print out the results:</span> <span class="pl-k">import</span> <span class="pl-s1">pprint</span> <span class="pl-s1">pprint</span>.<span class="pl-c1">pprint</span>(<span class="pl-s1">results</span>) { <span class="pl-s">'hits'</span>: [ { <span class="pl-s">'Title'</span>: <span class="pl-s">'Extravehicular Mobility Unit (EMU)'</span>, <span class="pl-s">'Description'</span>: <span class="pl-s">'The EMU is a spacesuit that provides environmental protection, mobility, life support, and'</span> <span class="pl-s">'communications for astronauts'</span>, <span class="pl-s">'_highlights'</span>: [{ <span class="pl-s">'Description'</span>: <span class="pl-s">'The EMU is a spacesuit that provides environmental protection, '</span> <span class="pl-s">'mobility, life support, and communications for astronauts'</span> }], <span class="pl-s">'_id'</span>: <span class="pl-s">'article_591'</span>, <span class="pl-s">'_score'</span>: <span class="pl-c1">0.61938936</span> }, { <span class="pl-s">'Title'</span>: <span class="pl-s">'The Travels of Marco Polo'</span>, <span class="pl-s">'Description'</span>: <span class="pl-s">"A 13th-century travelogue describing Polo's travels"</span>, <span class="pl-s">'_highlights'</span>: [{<span class="pl-s">'Title'</span>: <span class="pl-s">'The Travels of Marco Polo'</span>}], <span class="pl-s">'_id'</span>: <span class="pl-s">'e00d1a8d-894c-41a1-8e3b-d8b2a8fce12a'</span>, <span class="pl-s">'_score'</span>: <span class="pl-c1">0.60237324</span> } ], <span class="pl-s">'limit'</span>: <span class="pl-c1">10</span>, <span class="pl-s">'processingTimeMs'</span>: <span class="pl-c1">49</span>, <span class="pl-s">'query'</span>: <span class="pl-s">'What is the best outfit to wear on the moon?'</span> }</pre></div> <ul dir="auto"> <li>Each hit corresponds to a document that matched the search query.</li> <li>They are ordered from most to least matching.</li> <li><code>limit</code> is the maximum number of hits to be returned. This can be set as a parameter during search.</li> <li>Each hit has a <code>_highlights</code> field. This was the part of the document that matched the query the best.</li> </ul> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Other basic operations</h2><a id="user-content-other-basic-operations" class="anchor" aria-label="Permalink: Other basic operations" href="#other-basic-operations"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Get document</h3><a id="user-content-get-document" class="anchor" aria-label="Permalink: Get document" href="#get-document"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Retrieve a document by ID.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="result = mq.index("my-first-index").get_document(document_id="article_591")"><pre><span class="pl-s1">result</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">get_document</span>(<span class="pl-s1">document_id</span><span class="pl-c1">=</span><span class="pl-s">"article_591"</span>)</pre></div> <p dir="auto">Note that by adding the document using <code>add_documents</code> again using the same <code>_id</code> will cause a document to be updated.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Get index stats</h3><a id="user-content-get-index-stats" class="anchor" aria-label="Permalink: Get index stats" href="#get-index-stats"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Get information about an index.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="results = mq.index("my-first-index").get_stats()"><pre><span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">get_stats</span>()</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Lexical search</h3><a id="user-content-lexical-search" class="anchor" aria-label="Permalink: Lexical search" href="#lexical-search"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Perform a keyword search.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="result = mq.index("my-first-index").search('marco polo', search_method=marqo.SearchMethods.LEXICAL)"><pre><span class="pl-s1">result</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">search</span>(<span class="pl-s">'marco polo'</span>, <span class="pl-s1">search_method</span><span class="pl-c1">=</span><span class="pl-s1">marqo</span>.<span class="pl-c1">SearchMethods</span>.<span class="pl-c1">LEXICAL</span>)</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Multi modal and cross modal search</h3><a id="user-content-multi-modal-and-cross-modal-search" class="anchor" aria-label="Permalink: Multi modal and cross modal search" href="#multi-modal-and-cross-modal-search"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">To power image and text search, Marqo allows users to plug and play with CLIP models from HuggingFace. <strong>Note that if you do not configure multi modal search, image urls will be treated as strings.</strong> To start indexing and searching with images, first create an index with a CLIP configuration, as below:</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="settings = { "treat_urls_and_pointers_as_images":True, # allows us to find an image file and index it "model":"ViT-L/14" } response = mq.create_index("my-multimodal-index", **settings)"><pre><span class="pl-s1">settings</span> <span class="pl-c1">=</span> { <span class="pl-s">"treat_urls_and_pointers_as_images"</span>:<span class="pl-c1">True</span>, <span class="pl-c"># allows us to find an image file and index it </span> <span class="pl-s">"model"</span>:<span class="pl-s">"ViT-L/14"</span> } <span class="pl-s1">response</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">create_index</span>(<span class="pl-s">"my-multimodal-index"</span>, <span class="pl-c1">**</span><span class="pl-s1">settings</span>)</pre></div> <p dir="auto">Images can then be added within documents as follows. You can use urls from the internet (for example S3) or from the disk of the machine:</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="response = mq.index("my-multimodal-index").add_documents([{ "My_Image": "https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_realistic.png", "Description": "The hippopotamus, also called the common hippopotamus or river hippopotamus, is a large semiaquatic mammal native to sub-Saharan Africa", "_id": "hippo-facts" }], tensor_fields=["My_Image"])"><pre><span class="pl-s1">response</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-multimodal-index"</span>).<span class="pl-c1">add_documents</span>([{ <span class="pl-s">"My_Image"</span>: <span class="pl-s">"https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_realistic.png"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"The hippopotamus, also called the common hippopotamus or river hippopotamus, is a large semiaquatic mammal native to sub-Saharan Africa"</span>, <span class="pl-s">"_id"</span>: <span class="pl-s">"hippo-facts"</span> }], <span class="pl-s1">tensor_fields</span><span class="pl-c1">=</span>[<span class="pl-s">"My_Image"</span>])</pre></div> <p dir="auto">You can then search the image field using text.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="results = mq.index("my-multimodal-index").search('animal')"><pre><span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-multimodal-index"</span>).<span class="pl-c1">search</span>(<span class="pl-s">'animal'</span>)</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Searching using an image</h3><a id="user-content-searching-using-an-image" class="anchor" aria-label="Permalink: Searching using an image" href="#searching-using-an-image"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Searching using an image can be achieved by providing the image link.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="results = mq.index("my-multimodal-index").search('https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_statue.png')"><pre><span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-multimodal-index"</span>).<span class="pl-c1">search</span>(<span class="pl-s">'https://raw.githubusercontent.com/marqo-ai/marqo-api-tests/mainline/assets/ai_hippo_statue.png'</span>)</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Searching using weights in queries</h3><a id="user-content-searching-using-weights-in-queries" class="anchor" aria-label="Permalink: Searching using weights in queries" href="#searching-using-weights-in-queries"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Queries can also be provided as dictionaries where each key is a query and their corresponding values are weights. This allows for more advanced queries consisting of multiple components with weightings towards or against them, queries can have negations via negative weighting.</p> <p dir="auto">The example below shows the application of this to a scenario where a user may want to ask a question but also negate results that match a certain semantic criterion.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import marqo import pprint mq = marqo.Client(url="http://localhost:8882") mq.create_index("my-weighted-query-index") mq.index("my-weighted-query-index").add_documents( [ { "Title": "Smartphone", "Description": "A smartphone is a portable computer device that combines mobile telephone " "functions and computing functions into one unit.", }, { "Title": "Telephone", "Description": "A telephone is a telecommunications device that permits two or more users to" "conduct a conversation when they are too far apart to be easily heard directly.", }, { "Title": "Thylacine", "Description": "The thylacine, also commonly known as the Tasmanian tiger or Tasmanian wolf, " "is an extinct carnivorous marsupial." "The last known of its species died in 1936.", } ], tensor_fields=["Description"] ) # initially we ask for a type of communications device which is popular in the 21st century query = { # a weighting of 1.1 gives this query slightly more importance "I need to buy a communications device, what should I get?": 1.1, # a weighting of 1 gives this query a neutral importance # this will lead to 'Smartphone' being the top result "The device should work like an intelligent computer.": 1.0, } results = mq.index("my-weighted-query-index").search(q=query) print("Query 1:") pprint.pprint(results) # now we ask for a type of communications which predates the 21st century query = { # a weighting of 1 gives this query a neutral importance "I need to buy a communications device, what should I get?": 1.0, # a weighting of -1 gives this query a negation effect # this will lead to 'Telephone' being the top result "The device should work like an intelligent computer.": -0.3, } results = mq.index("my-weighted-query-index").search(q=query) print("\nQuery 2:") pprint.pprint(results)"><pre><span class="pl-k">import</span> <span class="pl-s1">marqo</span> <span class="pl-k">import</span> <span class="pl-s1">pprint</span> <span class="pl-s1">mq</span> <span class="pl-c1">=</span> <span class="pl-s1">marqo</span>.<span class="pl-c1">Client</span>(<span class="pl-s1">url</span><span class="pl-c1">=</span><span class="pl-s">"http://localhost:8882"</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">create_index</span>(<span class="pl-s">"my-weighted-query-index"</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-weighted-query-index"</span>).<span class="pl-c1">add_documents</span>( [ { <span class="pl-s">"Title"</span>: <span class="pl-s">"Smartphone"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"A smartphone is a portable computer device that combines mobile telephone "</span> <span class="pl-s">"functions and computing functions into one unit."</span>, }, { <span class="pl-s">"Title"</span>: <span class="pl-s">"Telephone"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"A telephone is a telecommunications device that permits two or more users to"</span> <span class="pl-s">"conduct a conversation when they are too far apart to be easily heard directly."</span>, }, { <span class="pl-s">"Title"</span>: <span class="pl-s">"Thylacine"</span>, <span class="pl-s">"Description"</span>: <span class="pl-s">"The thylacine, also commonly known as the Tasmanian tiger or Tasmanian wolf, "</span> <span class="pl-s">"is an extinct carnivorous marsupial."</span> <span class="pl-s">"The last known of its species died in 1936."</span>, } ], <span class="pl-s1">tensor_fields</span><span class="pl-c1">=</span>[<span class="pl-s">"Description"</span>] ) <span class="pl-c"># initially we ask for a type of communications device which is popular in the 21st century</span> <span class="pl-s1">query</span> <span class="pl-c1">=</span> { <span class="pl-c"># a weighting of 1.1 gives this query slightly more importance</span> <span class="pl-s">"I need to buy a communications device, what should I get?"</span>: <span class="pl-c1">1.1</span>, <span class="pl-c"># a weighting of 1 gives this query a neutral importance</span> <span class="pl-c"># this will lead to 'Smartphone' being the top result</span> <span class="pl-s">"The device should work like an intelligent computer."</span>: <span class="pl-c1">1.0</span>, } <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-weighted-query-index"</span>).<span class="pl-c1">search</span>(<span class="pl-s1">q</span><span class="pl-c1">=</span><span class="pl-s1">query</span>) <span class="pl-en">print</span>(<span class="pl-s">"Query 1:"</span>) <span class="pl-s1">pprint</span>.<span class="pl-c1">pprint</span>(<span class="pl-s1">results</span>) <span class="pl-c"># now we ask for a type of communications which predates the 21st century</span> <span class="pl-s1">query</span> <span class="pl-c1">=</span> { <span class="pl-c"># a weighting of 1 gives this query a neutral importance</span> <span class="pl-s">"I need to buy a communications device, what should I get?"</span>: <span class="pl-c1">1.0</span>, <span class="pl-c"># a weighting of -1 gives this query a negation effect</span> <span class="pl-c"># this will lead to 'Telephone' being the top result</span> <span class="pl-s">"The device should work like an intelligent computer."</span>: <span class="pl-c1">-</span><span class="pl-c1">0.3</span>, } <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-weighted-query-index"</span>).<span class="pl-c1">search</span>(<span class="pl-s1">q</span><span class="pl-c1">=</span><span class="pl-s1">query</span>) <span class="pl-en">print</span>(<span class="pl-s">"<span class="pl-cce">\n</span>Query 2:"</span>) <span class="pl-s1">pprint</span>.<span class="pl-c1">pprint</span>(<span class="pl-s1">results</span>)</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Creating and searching indexes with multimodal combination fields</h3><a id="user-content-creating-and-searching-indexes-with-multimodal-combination-fields" class="anchor" aria-label="Permalink: Creating and searching indexes with multimodal combination fields" href="#creating-and-searching-indexes-with-multimodal-combination-fields"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Marqo lets you have indexes with multimodal combination fields. Multimodal combination fields can combine text and images into one field. This allows scoring of documents across the combined text and image fields together. It also allows for a single vector representation instead of needing many which saves on storage. The relative weighting of each component can be set per document.</p> <p dir="auto">The example below demonstrates this with retrieval of caption and image pairs using multiple types of queries.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import marqo import pprint mq = marqo.Client(url="http://localhost:8882") settings = {"treat_urls_and_pointers_as_images": True, "model": "ViT-L/14"} mq.create_index("my-first-multimodal-index", **settings) mq.index("my-first-multimodal-index").add_documents( [ { "Title": "Flying Plane", "caption": "An image of a passenger plane flying in front of the moon.", "image": "https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image2.jpg", }, { "Title": "Red Bus", "caption": "A red double decker London bus traveling to Aldwych", "image": "https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image4.jpg", }, { "Title": "Horse Jumping", "caption": "A person riding a horse over a jump in a competition.", "image": "https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image1.jpg", }, ], # Create the mappings, here we define our captioned_image mapping # which weights the image more heavily than the caption - these pairs # will be represented by a single vector in the index mappings={ "captioned_image": { "type": "multimodal_combination", "weights": { "caption": 0.3, "image": 0.7 } } }, # We specify which fields to create vectors for. # Note that captioned_image is treated as a single field. tensor_fields=["captioned_image"] ) # Search this index with a simple text query results = mq.index("my-first-multimodal-index").search( q="Give me some images of vehicles and modes of transport. I am especially interested in air travel and commercial aeroplanes." ) print("Query 1:") pprint.pprint(results) # search the index with a query that uses weighted components results = mq.index("my-first-multimodal-index").search( q={ "What are some vehicles and modes of transport?": 1.0, "Aeroplanes and other things that fly": -1.0 }, ) print("\nQuery 2:") pprint.pprint(results) results = mq.index("my-first-multimodal-index").search( q={"Animals of the Perissodactyla order": -1.0} ) print("\nQuery 3:") pprint.pprint(results)"><pre><span class="pl-k">import</span> <span class="pl-s1">marqo</span> <span class="pl-k">import</span> <span class="pl-s1">pprint</span> <span class="pl-s1">mq</span> <span class="pl-c1">=</span> <span class="pl-s1">marqo</span>.<span class="pl-c1">Client</span>(<span class="pl-s1">url</span><span class="pl-c1">=</span><span class="pl-s">"http://localhost:8882"</span>) <span class="pl-s1">settings</span> <span class="pl-c1">=</span> {<span class="pl-s">"treat_urls_and_pointers_as_images"</span>: <span class="pl-c1">True</span>, <span class="pl-s">"model"</span>: <span class="pl-s">"ViT-L/14"</span>} <span class="pl-s1">mq</span>.<span class="pl-c1">create_index</span>(<span class="pl-s">"my-first-multimodal-index"</span>, <span class="pl-c1">**</span><span class="pl-s1">settings</span>) <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-multimodal-index"</span>).<span class="pl-c1">add_documents</span>( [ { <span class="pl-s">"Title"</span>: <span class="pl-s">"Flying Plane"</span>, <span class="pl-s">"caption"</span>: <span class="pl-s">"An image of a passenger plane flying in front of the moon."</span>, <span class="pl-s">"image"</span>: <span class="pl-s">"https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image2.jpg"</span>, }, { <span class="pl-s">"Title"</span>: <span class="pl-s">"Red Bus"</span>, <span class="pl-s">"caption"</span>: <span class="pl-s">"A red double decker London bus traveling to Aldwych"</span>, <span class="pl-s">"image"</span>: <span class="pl-s">"https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image4.jpg"</span>, }, { <span class="pl-s">"Title"</span>: <span class="pl-s">"Horse Jumping"</span>, <span class="pl-s">"caption"</span>: <span class="pl-s">"A person riding a horse over a jump in a competition."</span>, <span class="pl-s">"image"</span>: <span class="pl-s">"https://raw.githubusercontent.com/marqo-ai/marqo/mainline/examples/ImageSearchGuide/data/image1.jpg"</span>, }, ], <span class="pl-c"># Create the mappings, here we define our captioned_image mapping </span> <span class="pl-c"># which weights the image more heavily than the caption - these pairs </span> <span class="pl-c"># will be represented by a single vector in the index</span> <span class="pl-s1">mappings</span><span class="pl-c1">=</span>{ <span class="pl-s">"captioned_image"</span>: { <span class="pl-s">"type"</span>: <span class="pl-s">"multimodal_combination"</span>, <span class="pl-s">"weights"</span>: { <span class="pl-s">"caption"</span>: <span class="pl-c1">0.3</span>, <span class="pl-s">"image"</span>: <span class="pl-c1">0.7</span> } } }, <span class="pl-c"># We specify which fields to create vectors for. </span> <span class="pl-c"># Note that captioned_image is treated as a single field.</span> <span class="pl-s1">tensor_fields</span><span class="pl-c1">=</span>[<span class="pl-s">"captioned_image"</span>] ) <span class="pl-c"># Search this index with a simple text query</span> <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-multimodal-index"</span>).<span class="pl-c1">search</span>( <span class="pl-s1">q</span><span class="pl-c1">=</span><span class="pl-s">"Give me some images of vehicles and modes of transport. I am especially interested in air travel and commercial aeroplanes."</span> ) <span class="pl-en">print</span>(<span class="pl-s">"Query 1:"</span>) <span class="pl-s1">pprint</span>.<span class="pl-c1">pprint</span>(<span class="pl-s1">results</span>) <span class="pl-c"># search the index with a query that uses weighted components</span> <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-multimodal-index"</span>).<span class="pl-c1">search</span>( <span class="pl-s1">q</span><span class="pl-c1">=</span>{ <span class="pl-s">"What are some vehicles and modes of transport?"</span>: <span class="pl-c1">1.0</span>, <span class="pl-s">"Aeroplanes and other things that fly"</span>: <span class="pl-c1">-</span><span class="pl-c1">1.0</span> }, ) <span class="pl-en">print</span>(<span class="pl-s">"<span class="pl-cce">\n</span>Query 2:"</span>) <span class="pl-s1">pprint</span>.<span class="pl-c1">pprint</span>(<span class="pl-s1">results</span>) <span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-multimodal-index"</span>).<span class="pl-c1">search</span>( <span class="pl-s1">q</span><span class="pl-c1">=</span>{<span class="pl-s">"Animals of the Perissodactyla order"</span>: <span class="pl-c1">-</span><span class="pl-c1">1.0</span>} ) <span class="pl-en">print</span>(<span class="pl-s">"<span class="pl-cce">\n</span>Query 3:"</span>) <span class="pl-s1">pprint</span>.<span class="pl-c1">pprint</span>(<span class="pl-s1">results</span>)</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Delete documents</h3><a id="user-content-delete-documents" class="anchor" aria-label="Permalink: Delete documents" href="#delete-documents"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Delete documents.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content=" results = mq.index("my-first-index").delete_documents(ids=["article_591", "article_602"]) "><pre><span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">delete_documents</span>(<span class="pl-s1">ids</span><span class="pl-c1">=</span>[<span class="pl-s">"article_591"</span>, <span class="pl-s">"article_602"</span>])</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Delete index</h3><a id="user-content-delete-index" class="anchor" aria-label="Permalink: Delete index" href="#delete-index"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Delete an index.</p> <div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="results = mq.index("my-first-index").delete()"><pre><span class="pl-s1">results</span> <span class="pl-c1">=</span> <span class="pl-s1">mq</span>.<span class="pl-c1">index</span>(<span class="pl-s">"my-first-index"</span>).<span class="pl-c1">delete</span>()</pre></div> <h2 dir="auto"></h2> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Running Marqo open source in production</h2><a id="user-content-running-marqo-open-source-in-production" class="anchor" aria-label="Permalink: Running Marqo open source in production" href="#running-marqo-open-source-in-production"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">We support Kubernetes templates for Marqo which you can deploy on a cloud provider of your choice. Marqo's Kubernetes implementation allows you to deploy clusters with replicas, multiple storage shards and multiple inference nodes. The repo can be found here: <a href="https://github.com/marqo-ai/marqo-on-kubernetes">https://github.com/marqo-ai/marqo-on-kubernetes</a></p> <p dir="auto">If you're looking for a fully managed cloud service, you can sign up for Marqo Cloud here: <a href="https://cloud.marqo.ai" rel="nofollow">https://cloud.marqo.ai</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Documentation</h2><a id="user-content-documentation" class="anchor" aria-label="Permalink: Documentation" href="#documentation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The full documentation for Marqo can be found here <a href="https://docs.marqo.ai/" rel="nofollow">https://docs.marqo.ai/</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Warning</h2><a id="user-content-warning" class="anchor" aria-label="Permalink: Warning" href="#warning"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Note that you should not run other applications on Marqo's Vespa cluster as Marqo automatically changes and adapts the settings on the cluster.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Contributors</h2><a id="user-content-contributors" class="anchor" aria-label="Permalink: Contributors" href="#contributors"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Marqo is a community project with the goal of making tensor search accessible to the wider developer community. We are glad that you are interested in helping out! Please read <a href="/marqo-ai/marqo/blob/mainline/CONTRIBUTING.md">this</a> to get started.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Dev setup</h2><a id="user-content-dev-setup" class="anchor" aria-label="Permalink: Dev setup" href="#dev-setup"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ol dir="auto"> <li> <p dir="auto">Create a virtual env <code>python -m venv ./venv</code>.</p> </li> <li> <p dir="auto">Activate the virtual environment <code>source ./venv/bin/activate</code>.</p> </li> <li> <p dir="auto">Install requirements from the requirements file: <code>pip install -r requirements.txt</code>.</p> </li> <li> <p dir="auto">Run tests by running the tox file. CD into this dir and then run "tox".</p> </li> <li> <p dir="auto">If you update dependencies, make sure to delete the .tox dir and rerun.</p> </li> </ol> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Merge instructions:</h2><a id="user-content-merge-instructions" class="anchor" aria-label="Permalink: Merge instructions:" href="#merge-instructions"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ol dir="auto"> <li> <p dir="auto">Run the full test suite (by using the command <code>tox</code> in this dir).</p> </li> <li> <p dir="auto">Create a pull request with an attached github issue.</p> </li> </ol> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Support</h2><a id="user-content-support" class="anchor" aria-label="Permalink: Support" href="#support"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <ul dir="auto"> <li>Ask questions and share your creations with the community on our <a href="https://community.marqo.ai" rel="nofollow">Discourse forum</a>.</li> <li>Join our <a href="https://bit.ly/marqo-community-slack" rel="nofollow">Slack community</a> and chat with other community members about ideas.</li> </ul> </article></div></div></div></div></div> <!-- --> <!-- --> <script type="application/json" id="__PRIMER_DATA_:R0:__">{"resolvedServerColorMode":"day"}</script></div> </react-partial> <input type="hidden" data-csrf="true" value="DO8IadRaJ6mv3kb926xSx7ylNSMy3pXQSdYKhIGlye2acJVTA6jHyMKXO9pE9q6eHA6V/b3X9346gQD39XtfXA==" /> </div> <div data-view-component="true" class="Layout-sidebar"> <div class="BorderGrid about-margin" data-pjax> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <div class="hide-sm hide-md"> <h2 class="mb-3 h4">About</h2> <p class="f4 my-3"> Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai </p> <div class="my-3 d-flex flex-items-center"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link flex-shrink-0 mr-2"> <path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path> </svg> <span class="flex-auto min-width-0 css-truncate css-truncate-target width-fit"> <a title="https://www.marqo.ai/" role="link" target="_blank" rel="noopener noreferrer nofollow" class="text-bold" href="https://www.marqo.ai/">www.marqo.ai/</a> </span> </div> <h3 class="sr-only">Topics</h3> <div class="my-3"> <div class="f6"> <a href="/topics/search-engine" title="Topic: search-engine" data-view-component="true" class="topic-tag topic-tag-link"> search-engine </a> <a href="/topics/machine-learning" title="Topic: machine-learning" data-view-component="true" class="topic-tag topic-tag-link"> machine-learning </a> <a href="/topics/natural-language-processing" title="Topic: natural-language-processing" data-view-component="true" class="topic-tag topic-tag-link"> natural-language-processing </a> <a href="/topics/information-retrieval" title="Topic: information-retrieval" data-view-component="true" class="topic-tag topic-tag-link"> information-retrieval </a> <a href="/topics/deep-learning" title="Topic: deep-learning" data-view-component="true" class="topic-tag topic-tag-link"> deep-learning </a> <a href="/topics/transformers" title="Topic: transformers" data-view-component="true" class="topic-tag topic-tag-link"> transformers </a> <a href="/topics/machinelearning" title="Topic: machinelearning" data-view-component="true" class="topic-tag topic-tag-link"> machinelearning </a> <a href="/topics/gpt" title="Topic: gpt" data-view-component="true" class="topic-tag topic-tag-link"> gpt </a> <a href="/topics/visual-search" title="Topic: visual-search" data-view-component="true" class="topic-tag topic-tag-link"> visual-search </a> <a href="/topics/multi-modal" title="Topic: multi-modal" data-view-component="true" class="topic-tag topic-tag-link"> multi-modal </a> <a href="/topics/clip" title="Topic: clip" data-view-component="true" class="topic-tag topic-tag-link"> clip </a> <a href="/topics/knn" title="Topic: knn" data-view-component="true" class="topic-tag topic-tag-link"> knn </a> <a href="/topics/semantic-search" title="Topic: semantic-search" data-view-component="true" class="topic-tag topic-tag-link"> semantic-search </a> <a href="/topics/hacktoberfest" title="Topic: hacktoberfest" data-view-component="true" class="topic-tag topic-tag-link"> hacktoberfest </a> <a href="/topics/hnsw" title="Topic: hnsw" data-view-component="true" class="topic-tag topic-tag-link"> hnsw </a> <a href="/topics/vector-search" title="Topic: vector-search" data-view-component="true" class="topic-tag topic-tag-link"> vector-search </a> <a href="/topics/vision-language" title="Topic: vision-language" data-view-component="true" class="topic-tag topic-tag-link"> vision-language </a> <a href="/topics/large-language-models" title="Topic: large-language-models" data-view-component="true" class="topic-tag topic-tag-link"> large-language-models </a> <a href="/topics/tensor-search" title="Topic: tensor-search" data-view-component="true" class="topic-tag topic-tag-link"> tensor-search </a> <a href="/topics/chatgpt" title="Topic: chatgpt" data-view-component="true" class="topic-tag topic-tag-link"> chatgpt </a> </div> </div> <h3 class="sr-only">Resources</h3> <div class="mt-2"> <a class="Link--muted" data-analytics-event="{"category":"Repository Overview","action":"click","label":"location:sidebar;file:readme"}" href="#readme-ov-file"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-book mr-2"> <path d="M0 1.75A.75.75 0 0 1 .75 1h4.253c1.227 0 2.317.59 3 1.501A3.743 3.743 0 0 1 11.006 1h4.245a.75.75 0 0 1 .75.75v10.5a.75.75 0 0 1-.75.75h-4.507a2.25 2.25 0 0 0-1.591.659l-.622.621a.75.75 0 0 1-1.06 0l-.622-.621A2.25 2.25 0 0 0 5.258 13H.75a.75.75 0 0 1-.75-.75Zm7.251 10.324.004-5.073-.002-2.253A2.25 2.25 0 0 0 5.003 2.5H1.5v9h3.757a3.75 3.75 0 0 1 1.994.574ZM8.755 4.75l-.004 7.322a3.752 3.752 0 0 1 1.992-.572H14.5v-9h-3.495a2.25 2.25 0 0 0-2.25 2.25Z"></path> </svg> Readme </a> </div> <h3 class="sr-only">License</h3> <div class="mt-2"> <a href="#Apache-2.0-1-ov-file" class="Link--muted" data-analytics-event="{"category":"Repository 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0-1.5h2.5V3.5h-.984a.245.245 0 0 0-.124.033l-1.289.737c-.265.15-.564.23-.869.23h-.162l2.112 4.692a.75.75 0 0 1-.154.838l-.53-.53.529.531-.001.002-.002.002-.006.006-.016.015-.045.04c-.21.176-.441.327-.686.45C4.556 10.78 3.88 11 3 11a4.498 4.498 0 0 1-2.023-.454 3.544 3.544 0 0 1-.686-.45l-.045-.04-.016-.015-.006-.006-.004-.004v-.001a.75.75 0 0 1-.154-.838L2.178 4.5H1.75a.75.75 0 0 1 0-1.5h2.234a.249.249 0 0 0 .125-.033l1.288-.737c.265-.15.564-.23.869-.23h.984V.75a.75.75 0 0 1 1.5 0Zm2.945 8.477c.285.135.718.273 1.305.273s1.02-.138 1.305-.273L13 6.327Zm-10 0c.285.135.718.273 1.305.273s1.02-.138 1.305-.273L3 6.327Z"></path> </svg> Security policy </a> </div> <include-fragment src="/marqo-ai/marqo/hovercards/citation/sidebar_partial?tree_name=mainline"> </include-fragment> <div class="mt-2"> <a href="/marqo-ai/marqo/activity" data-view-component="true" class="Link Link--muted"><svg text="gray" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" 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0 1 0-1.5Z"></path> </svg> <span class="color-fg-muted">Custom properties</span></a> </div> <h3 class="sr-only">Stars</h3> <div class="mt-2"> <a href="/marqo-ai/marqo/stargazers" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-star mr-2"> <path d="M8 .25a.75.75 0 0 1 .673.418l1.882 3.815 4.21.612a.75.75 0 0 1 .416 1.279l-3.046 2.97.719 4.192a.751.751 0 0 1-1.088.791L8 12.347l-3.766 1.98a.75.75 0 0 1-1.088-.79l.72-4.194L.818 6.374a.75.75 0 0 1 .416-1.28l4.21-.611L7.327.668A.75.75 0 0 1 8 .25Zm0 2.445L6.615 5.5a.75.75 0 0 1-.564.41l-3.097.45 2.24 2.184a.75.75 0 0 1 .216.664l-.528 3.084 2.769-1.456a.75.75 0 0 1 .698 0l2.77 1.456-.53-3.084a.75.75 0 0 1 .216-.664l2.24-2.183-3.096-.45a.75.75 0 0 1-.564-.41L8 2.694Z"></path> </svg> <strong>4.8k</strong> stars</a> </div> <h3 class="sr-only">Watchers</h3> <div class="mt-2"> <a href="/marqo-ai/marqo/watchers" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-eye mr-2"> <path d="M8 2c1.981 0 3.671.992 4.933 2.078 1.27 1.091 2.187 2.345 2.637 3.023a1.62 1.62 0 0 1 0 1.798c-.45.678-1.367 1.932-2.637 3.023C11.67 13.008 9.981 14 8 14c-1.981 0-3.671-.992-4.933-2.078C1.797 10.83.88 9.576.43 8.898a1.62 1.62 0 0 1 0-1.798c.45-.677 1.367-1.931 2.637-3.022C4.33 2.992 6.019 2 8 2ZM1.679 7.932a.12.12 0 0 0 0 .136c.411.622 1.241 1.75 2.366 2.717C5.176 11.758 6.527 12.5 8 12.5c1.473 0 2.825-.742 3.955-1.715 1.124-.967 1.954-2.096 2.366-2.717a.12.12 0 0 0 0-.136c-.412-.621-1.242-1.75-2.366-2.717C10.824 4.242 9.473 3.5 8 3.5c-1.473 0-2.825.742-3.955 1.715-1.124.967-1.954 2.096-2.366 2.717ZM8 10a2 2 0 1 1-.001-3.999A2 2 0 0 1 8 10Z"></path> </svg> <strong>39</strong> watching</a> </div> <h3 class="sr-only">Forks</h3> <div class="mt-2"> <a href="/marqo-ai/marqo/forks" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo-forked mr-2"> <path d="M5 5.372v.878c0 .414.336.75.75.75h4.5a.75.75 0 0 0 .75-.75v-.878a2.25 2.25 0 1 1 1.5 0v.878a2.25 2.25 0 0 1-2.25 2.25h-1.5v2.128a2.251 2.251 0 1 1-1.5 0V8.5h-1.5A2.25 2.25 0 0 1 3.5 6.25v-.878a2.25 2.25 0 1 1 1.5 0ZM5 3.25a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Zm6.75.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5Zm-3 8.75a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Z"></path> </svg> <strong>202</strong> forks</a> </div> <div class="mt-2"> <a class="Link--muted" href="/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Fmarqo-ai%2Fmarqo&report=marqo-ai+%28user%29"> Report repository </a> </div> </div> </div> </div> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <h2 class="h4 mb-3" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame"> <a href="/marqo-ai/marqo/releases" data-view-component="true" class="Link--primary no-underline Link">Releases <span title="74" data-view-component="true" class="Counter">74</span></a></h2> <a class="Link--primary d-flex no-underline" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame" href="/marqo-ai/marqo/releases/tag/2.17.1"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-tag flex-shrink-0 mt-1 color-fg-success"> <path d="M1 7.775V2.75C1 1.784 1.784 1 2.75 1h5.025c.464 0 .91.184 1.238.513l6.25 6.25a1.75 1.75 0 0 1 0 2.474l-5.026 5.026a1.75 1.75 0 0 1-2.474 0l-6.25-6.25A1.752 1.752 0 0 1 1 7.775Zm1.5 0c0 .066.026.13.073.177l6.25 6.25a.25.25 0 0 0 .354 0l5.025-5.025a.25.25 0 0 0 0-.354l-6.25-6.25a.25.25 0 0 0-.177-.073H2.75a.25.25 0 0 0-.25.25ZM6 5a1 1 0 1 1 0 2 1 1 0 0 1 0-2Z"></path> </svg> <div class="ml-2 min-width-0"> <div class="d-flex"> <span class="css-truncate 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