The open-source, extensible framework for building and deploying cross-platform AI agents with multi-model support.
Lobe Chat is a cutting-edge, open-source framework designed for the 2026 AI landscape, serving as a modular UI for Large Language Models (LLMs). Built on Next.js and TypeScript, it provides a high-performance, mobile-first interface that supports a vast array of models including OpenAI, Anthropic, Google Gemini, and local providers via Ollama. Its technical architecture is centered around a robust plugin system and a dedicated Agent Marketplace, allowing developers to extend functionality through function calling and tool-use capabilities. In the 2026 market, Lobe Chat positions itself as the premier alternative to proprietary chat interfaces by offering end-to-end data sovereignty through self-hosting and client-side database encryption. It bridges the gap between raw API endpoints and user-centric applications, providing native support for multimodal interactions including Vision, Text-to-Speech (TTS), and Speech-to-Text (STT). Its roadmap focuses on 'AI-native' workflows, where agents can interact with local files (RAG) and external web services autonomously, making it a critical tool for enterprises seeking to build custom, private AI ecosystems without vendor lock-in.
Dynamically switch between OpenAI, Anthropic, Gemini, and local models in a single chat thread.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Extensible function-calling framework compatible with OpenAI plugin standards.
Deep integration with GPT-4-vision and Claude-3-opus for image analysis.
Native bridge for Ollama and LocalAI via local network proxies.
Integration with OpenAI Whisper and Microsoft Edge TTS for realistic voice interaction.
Progressive Web App architecture for native-like performance on iOS, Android, and Desktop.
In-browser document parsing and vector search for private knowledge base interactions.
Employees need to query sensitive internal documents without leaking data to public AI trainers.
Registry Updated:2/7/2026
Marketing teams need to analyze images and generate text descriptions simultaneously.
Developers working offline or in air-gapped environments need coding assistance.