⚠️ Recommending LangGraph Platform for new projects

[eyurtsev]

We have recently announced LangGraph Platform, a significantly enhanced solution for deploying agentic applications at scale.

We recommend using LangGraph Platform rather than LangServe for new projects.

LangGraph Platform incorporates key design patterns and capabilities essential for production-level deployment of large language model (LLM) applications.

In contrast to LangServe, LangGraph Platform provides comprehensive, out-of-the-box support for persistence, memory, double-texting handling, human-in-the-loop workflows, cron job scheduling, webhooks, high-load management, advanced streaming, support for long-running tasks, background task processing, and much more.

The LangGraph Platform ecosystem includes the following components:

• LangGraph Server: Provides an Assistants API for LLM applications (graphs) built with LangGraph. Available in both Python and JavaScript/TypeScript.
• LangGraph Studio: A specialized IDE for real-time visualization, debugging, and interaction via a graphical interface. Available as a web application or macOS desktop app, it's a substantial improvement over LangServe's playground.
• SDK: Enables programmatic interaction with the server, available in Python and JavaScript/TypeScript.
• RemoteGraph: Allows interaction with a remote graph as if it were running locally, serving as LangGraph's equivalent to LangServe's RemoteRunnable. Available in both Python and JavaScript/TypeScript.

If you're interested in migrating your LangServe code to LangGraph Platform please the LangGraph Platform Migration Guide for more information.

We will continue to accept bug fixes for LangServe from the community; however, we will not be accepting new feature contributions.

[ewiner]

My understanding is that LangServe and LangChain are open-source, while LangGraph Server is a commercial product with closed-source dependencies and limitations on free usage (according to the deployment options page). Is that correct?