OGX: An Open-Source, Vendor-Neutral Generative AI Application Server

[2608.14580] OGX: An Open-Source, Vendor-Neutral Generative AI Application Server Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Artificial Intelligence arXiv:2608.14580 (cs) [Submitted on 12 Jun 2026] Title: OGX: An Open-Source, Vendor-Neutral Generative AI Application Server Authors: Francisco Javier Arceo , Sébastien Han , Matthew Farrellee , Charlie Doern , Yuan Tang , Derek Higgins , Varsha Prasad Narsing , Gordon Sim , Sumanth Kamenani , Ben Browning , Raghotham Murthy View a PDF of the paper titled OGX: An Open-Source, Vendor-Neutral Generative AI Application Server, by Francisco Javier Arceo and 10 other authors View PDF HTML (experimental) Abstract: OGX (Open GenAI Stack) is an open-source AI application server and Python library that implements the APIs of major frontier labs (OpenAI, Anthropic, Google) with pluggable backend providers. Developers building agentic AI applications--such as retrieval-augmented generation pipelines, multi-turn agents, and tool-calling workflows--can develop against a single API surface and deploy with any combination of inference engine, vector database, and safety backend, without changing application code. OGX's primary focus is the Responses API for server-side agentic orchestration, conforming to the Open Responses specification. The server also supports the Anthropic Messages API and Google GenAI Interactions API, decoupling SDK choice from model and deployment decisions. With over 20 inference providers, 13 vector store backends, and a companion Kubernetes Operator for production deployment, OGX serves as the self-hosted, model-agnostic backend for AI-powered developer tools including Claude Code, Codex CLI, OpenCode, and OpenHands. The project has over 8,400 GitHub stars, 242 contributors, and 4,000 commits across nearly two years of public development. Subjects: Artificial Intelligence (cs.AI) ; Information Retrieval (cs.IR) ACM classes: I.2; H.3; K.6; I.2.11; I.2.7 Cite as: arXiv:2608.14580 [cs.AI] (or arXiv:2608.14580v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2608.14580 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Francisco Javier Arceo [ view email ] [v1] Fri, 12 Jun 2026 21:02:25 UTC (12 KB) Full-text links: Access Paper: View a PDF of the paper titled OGX: An Open-Source, Vendor-Neutral Generative AI Application Server, by Francisco Javier Arceo and 10 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.AI < prev | next > new | recent | 2026-08 Change to browse by: cs cs.IR References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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