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Basic Information

AgentLabs is an open-source universal frontend for AI agents designed to let teams ship AI-driven chat agents to public users while focusing on the backend. It provides a complete front-end stack including an authentication portal, a chat UI with realtime bidirectional streaming, analytics and payment features, and a backoffice to manage projects, users and agents. The project is Apache 2.0 licensed and maintained alongside a cloud hosted alpha offering and enterprise support. The repository includes SDKs for streaming backends and a self-hosting option using docker-compose. Documentation and examples are provided to help developers integrate the frontend with their agent backends. The emphasis is on handling user-facing, embedding and management concerns so developers can concentrate on agent logic and infrastructure.

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App Details

Features
The README highlights a set of ready-made components and capabilities: an Authentication Portal and registration flows, a chat-based Agent UI with realtime request/response streaming, a Backoffice for managing projects, agents and users, analytics and payment feature placeholders, and multi-agent support in the UI. SDKs listed include Python and TypeScript streaming backend SDKs. Deployment options include a cloud hosted alpha release and a self-hosted distribution via docker-compose. Roadmap and planned features include embeddable iFrame/chatbot support, moving login into the chat, support for interactive rich components in chat, and ongoing SDK improvements. The repo includes basic documentation and examples.
Use Cases
AgentLabs helps teams deliver production-ready, user-facing agent experiences without building the frontend stack from scratch. It provides out-of-the-box authentication, user management, a chat interface with realtime streaming, backoffice controls for projects and users, and integration points via backend SDKs, which together reduce the integration work required to expose agent functionality to end users. The repo supports both cloud-hosted usage and self-hosting with docker-compose, enabling flexible operational models. Built-in analytics and payment support are included to help commercialize agents. The project is in alpha and accompanied by documentation and examples to accelerate developer onboarding and deployment.

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