Llama Deploy enables you to transform your LlamaIndex data indexes into production-ready AI agents. By configuring deployment targets such as AWS Lambda, Vercel Functions, or Docker containers, you get secure, auto-scaled chat APIs that serve responses from your custom index. It handles endpoint creation, request routing, token-based authentication, and performance monitoring out of the box. Llama Deploy streamlines the end-to-end process of deploying conversational AI, from local testing to production, ensuring low-latency and high availability.

vagent_comm is an API client framework that simplifies message exchange between Python applications and VAgent AI agents. It supports secure token authentication, automatic JSON formatting, and dual transport via WebSocket and HTTP REST. Developers can establish sessions, send text or data payloads, handle streaming responses, and manage retries on errors. The library’s asynchronous interface and built-in session management allow seamless integration into chatbots, virtual assistant backends, and automated workflows.