Query Response

Query data

Score

Prompt

System Prompt

You are a reporter for a major world newspaper. Write your response as if you were writing a short, high-quality news article for your paper. Limit your response to one paragraph. Use the following article for context: Timescale Bolsters AI-Ready PostgreSQL with pgai Vectorizer - InfoQ<link rel="stylesheet" type="text/css" href="https://cdn.infoq.com/statics_s1_20241119073511/styles/style_en.css"/> <link rel="stylesheet" href="https://cdn.infoq.com/statics_s1_20241119073511/styles/icons.css"> <link rel="stylesheet" type="text/css" media="screen" href="https://cdn.infoq.com/statics_s1_20241119073511/styles/style_extra.css"/><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-W9GJ5DL" height="0" width="0" style="display:none;visibility:hidden"></iframe>BTInfoQ Software Architects' NewsletterA monthly overview of things you need to know as an architect or aspiring architect.View an exampleEnter your e-mail addressSelect your countrySelect a countryI consent to InfoQ.com handling my data as explained in thisPrivacy Notice.We protect your privacy.CloseToggle NavigationFacilitating the Spread of Knowledge and Innovation in Professional Software DevelopmentEnglish editionEnglish editionChinese editionJapanese editionFrench editionWrite for InfoQSearchSign Up / LoginEmailPasswordForgot password ?InfoQ Account EmailBack to loginResend ActivationBack to loginLogin with:GoogleMicrosoftTwitterFacebookDon't have an InfoQ account?Sign UpLogo - Back to homepageNewsArticlesPresentationsPodcastsGuidesTopicsDevelopmentJavaKotlin.NetC#SwiftGoRustJavaScriptFeatured in DevelopmentBeyond the Breach: Proactive Defense in the Age of Advanced ThreatsMichael Brunton-Spall discusses some of the most advanced attacks that are in the public domain, mostly attributed in public by commercial organizations.All in developmentArchitecture & DesignArchitectureEnterprise ArchitectureScalability/PerformanceDesignCase StudiesMicroservicesService MeshPatternsSecurityFeatured in Architecture & DesignTransforming Legacy Healthcare Systems: A Journey to Cloud-Native ArchitectureDiscover how Livi navigated the complexities of transitioning MJog, a legacy healthcare system, to a cloud-native architecture, sharing valuable insights for successful tech modernization. Our experience illustrates that transitioning from legacy systems to cloud-based microservices is not a one-time project but an ongoing journey.All in architecture-designAI, ML & Data EngineeringBig DataMachine LearningNoSQLDatabaseData AnalyticsStreamingFeatured in AI, ML & Data EngineeringNavigating LLM Deployment: Tips, Tricks, and TechniquesMeryem Arik discusses some of the best practices in model optimization, serving and monitoring - with practical tips and real case-studies.All in ai-ml-data-engCulture & MethodsAgileDiversityLeadershipLean/KanbanPersonal GrowthScrumSociocracySoftware CraftmanshipTeam CollaborationTestingUXFeatured in Culture & MethodsTrends in Engineering Leadership: Observability, Agile Backlash, and Building Autonomous TeamsIn this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Chris Cooney about emerging trends in software engineering such as the backlash against "Agile" practices, the growing importance of observability and people-focused metrics, and strategies for aligning teams around common goals while still preserving their autonomy.All in culture-methodsDevOpsInfrastructureContinuous DeliveryAutomationContainersCloudObservabilityFeatured in DevOpsProactive Approaches to Securing Linux Systems and Engineering ApplicationsMaintaining a strong security posture is challenging, especially with Linux. An effective approach is proactive and includes patch management, optimized resource allocation, and effective alerting.All in devopsEventsHelpful linksAbout InfoQInfoQ EditorsWrite for InfoQAbout C4MediaDiversityChoose your languageEn中文日本FrQCon San FranciscoLevel up your software skills by uncovering the emerging trends you should focus on. Register now.QCon LondonDiscover emerging trends, insights, and real-world best practices in software development & tech leadership. Join now.InfoQ Dev Summit BostonLearn how senior software developers are solving the challenges you face. Register now with early bird tickets.The Software Architects' NewsletterYour monthly guide to all the topics, technologies and techniques that every professional needs to know about. Subscribe for free.InfoQ HomepageNewsTimescale Bolsters AI-Ready PostgreSQL with pgai VectorizerDevOpsTimescale Bolsters AI-Ready PostgreSQL with pgai VectorizerLikeBookmarksNov 20, 20242 min readbyMohit PalriwalWrite for InfoQFeed your curiosity.Help 550k+ globalsenior developerseach month stay ahead.Get in touchTimescale recently expanded its PostgreSQL AI offeringswithpgai Vectorizer. This update enables developers to create, store, and manage vector embeddings alongside relational data without the need for external tools or additional infrastructure.TimescaleDB, an open-source extension for PostgreSQL tailored for time-series data, first augmented PostgreSQL withreal-time analyticsfeatures. Now, Timescale is enhancing AI integration with the pgai suite and the introduction of pgai Vectorizer, enabling developers to conduct AI development seamlessly within PostgreSQL.Contributors have noted some challenges during the development process. One contributor,Tostino,highlighted issues with the OpenAI API compliance, noting that the current implementation lacks several arguments necessary for using proxy solutions or custom samplers on open-source inference servers. Additionally, Tostino suggested that functions providing a "simple" wrapper should be built on top of raw functions returning JSON, rather than strict data types, to enhance flexibility.Building AI systems like search engines and AI agents often requires complex workflows. The pgai Vectorizer streamlines this by integrating the entire AI workflow into PostgreSQL, allowing developers to create advanced AI applications quickly and efficiently using familiar SQL commandsSourceTimescaleargues that the standard approach of treating vector embeddings as standalone data leads to synchronization issues and stale data.The Institute for Ethical AI & Machine Learning comments:TimescaleDB proposes treating embeddings as derived data similar to database indexes, which is interesting given recent extensions from DBs like planetscale to integrate embeddings natively into indexes, similarly through a "native vectorizer" abstraction. In this case however they still leverage the OSS pgai Vectorizer for PostgreSQL which helps automating the synchronization of embeddings with their source data within the database,Thepgvectorandpgvectorscaleextensions allow you to store vector embeddings in your database and perform fast and efficient vector searches. Thepgai Vectorizerbuilds on top of these extensions to automatically create and synchronize embeddings for any text data in your database.With one line of code, you can define a vectorizer that creates embeddings for data in a table.Suvarna Kadam, a machine learning consultantcomments:pgai Vectorizer makes it possible to use one SQL command that will manage your vector embeddings "without" the usual engineering challenges to keep it in sync with your source data!SELECT ai.create_vectorizer(      <table_name>::regclass,     destination => <embedding_table_name>,     embedding => ai.embedding_openai(<model_name>, <dimensions>),     chunking => ai.chunking_recursive_character_text_splitter(<column_name>) );In the same week,Neon Database Labs also introduced Pgrag, an experimental PostgreSQL extension aimed at supporting end-to-end retrieval-augmented-generation (RAG) pipelines, further expanding their own AI capabilities.In addition to the recent launch of the pgai Vectorizer, there has beencommunity interest in expanding the range of supported embedding models beyond OpenAI. Contributorclaudeomusicinquired about the possibility of making the choice of embedding models configurable, highlighting the importance of flexibility for users. In response,alejandrodnmfrom Timescale confirmed that while the current Vectorizer feature supports only OpenAI models, there are plans to include other providers in the future. The team is open to contributions from the community to help achieve this goal. Another contributor,wang, shared his workaround on How to use with Openrouter.To quickly try out embeddings using a pre-built Docker developer environment, see theVectorizer quick start. For more detailed technical specifications, see theVectorizer API reference.About the AuthorMohit PalriwalShow moreShow lessRate this ArticleAdoptionStyleAuthor ContactedThis content is in theDevOpstopicRelated Topics:DevOpsAI, ML & Data EngineeringReal-Time DataSQLDatabaseTime Series DataRelational DatabasesPostgresOpen SourceRelated EditorialRelated Sponsored ContentPopular across InfoQAWS Amplify and Amazon S3 Integration Simplifies Static Website HostingAnthropic Releases New Claude Models and Computer Use FeatureMeta Releases NotebookLlama: Open-Source PDF to Podcast ToolkitCrossing the Feedback Chasm - a Conversation with Ken FinniganThoughtworks Technology Radar Oct 2024 - From Coding Assistance to AI EvolutionMonorepos: beyond the Technicalities<div class="widget related__content article__widget"> <h3 class="widget__heading">Related Content</h3> <ul class="no-style cards" data-horizontal="true" data-size="xs" data-tax=""> </ul> </div>The InfoQNewsletterA round-up of last week’s content on InfoQ sent out every Tuesday. Join a community of over 250,000 senior developers.View an exampleEnter your e-mail addressSelect your countrySelect a countryI consent to InfoQ.com handling my data as explained in thisPrivacy Notice.We protect your privacy.DevelopmentCarle Lerche Talking at Qcon SF About Rust: A Productive Language for Writing Database ApplicationsGoogle Introduces Gemini AI Features to Android StudioGitHub Universe 2024 Unveils AI Innovations and Developer-Centric ToolsArchitecture & DesignTransforming Legacy Healthcare Systems: A Journey to Cloud-Native ArchitectureNew "Laws" Announced at iSAQB Software Architecture GatheringImproving Developer Experience Using Automated Data CI/CD PipelinesCulture & MethodsTrends in Engineering Leadership: Observability, Agile Backlash, and Building Autonomous TeamsUsing DORA for Sustainable Engineering Performance ImprovementMonorepos: beyond the TechnicalitiesAI, ML & Data EngineeringQCon SF: Large Scale Search and Ranking Systems at NetflixNavigating LLM Deployment: Tips, Tricks, and TechniquesQCon SF: Using Metaflow to Support Diverse ML Systems at NetflixDevOpsTimescale Bolsters AI-Ready PostgreSQL with pgai VectorizerKubeCon + CloudNativeCon NA 2024: Key Announcements and Project UpdatesThoughtworks Technology Radar Oct 2024 - From Coding Assistance to AI EvolutionThe InfoQNewsletterA round-up of last week’s content on InfoQ sent out every Tuesday. Join a community of over 250,000 senior developers.View an exampleGet a quick overview of content published on a variety of innovator and early adopter technologiesLearn what you don’t know that you don’t knowStay up to date with the latest information from the topics you are interested inEnter your e-mail addressSelect your countrySelect a countryI consent to InfoQ.com handling my data as explained in thisPrivacy Notice.We protect your privacy.QCon San FranciscoNovember 18-22, 2024.QCon San Francisco International Software Conference returns on November 18-24. More than 1000 software professionals will join together and learn about the emerging trends they should pay attention to in 2024, how to adopt them, how to avoid pitfalls, and how to embrace the best practices.Join the experience and get implementable ideas to shape your projects that last beyond the conference.Register NowHomeCreate accountLoginQCon ConferencesEventsWrite for InfoQInfoQ EditorsAbout InfoQAbout C4MediaMedia KitInfoQ Developer Marketing BlogDiversityEventsQCon San FranciscoNOVEMBER 18-22, 2024QCon LondonAPRIL 7-9, 2025InfoQ Dev Summit BostonJune 9-10, 2025Follow us onYoutube223K FollowersLinkedin21K FollowersRSS19K ReadersX53.4k FollowersFacebook21K LikesAlexaNewStay in the knowThe InfoQ PodcastEngineering Culture PodcastThe Software Architects' NewsletterGeneral Feedbackfeedback@infoq.comAdvertisingsales@infoq.comEditorialeditors@infoq.comMarketingmarketing@infoq.comInfoQ.com and all content copyright © 2006-2024 C4Media Inc.Privacy Notice,Terms And Conditions,Cookie PolicyBT<img height="1" width="1" src="https://www.facebook.com/tr?id=842388869148196&ev=PageView&noscript=1"/>

User Query

what is pgvector?

Result

Source

https://www.infoq.com/news/2024/11/timescale-pgai-vectorizer/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=DevOps

Response

pgvector is an open-source PostgreSQL extension that enables the storage and efficient querying of vector embeddings directly within a PostgreSQL database. It supports the management of high-dimensional vector data commonly used in AI and machine learning applications, such as those generated by natural language processing models for semantic search and recommendation systems. By integrating vector search capabilities natively into PostgreSQL, pgvector facilitates fast similarity searches and enhances AI workflows without requiring separate infrastructure. The TimescaleDB ecosystem, for example, builds upon pgvector with tools like the pgai Vectorizer to automate the creation and synchronization of embeddings, streamlining advanced AI applications inside the database environment.