Beta (#855)

README.md

@@ -216,4 +216,4 @@ final_state["messages"][-1].content
 * [How-to Guides](https://langchain-ai.github.io/langgraph/how-tos/): Accomplish specific things within LangGraph, from streaming, to adding memory & persistence, to common design patterns (branching, subgraphs, etc.), these are the place to go if you want to copy and run a specific code snippet.
 * [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
 * [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
-* [Cloud (alpha)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.
+* [Cloud (beta)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.

docs/docs/cloud/index.md

@@ -1,4 +1,4 @@
-# LangGraph Cloud (alpha)
+# LangGraph Cloud (beta)
 
 !!! danger "Important"
     LangGraph Cloud is a closed source, paid product in an invite-only stage. We are currently focused on providing high bandwidth support to make our select early customers successful. If you are interested in applying for access, please fill out [this form](https://airtable.com/app5PiMJxXukqPLq3/pagveJsW7XOjDspqw/form).

docs/mkdocs.yml

@@ -167,7 +167,7 @@ nav:
       - Checkpointing: reference/checkpoints.md
       - Prebuilt Components: reference/prebuilt.md
       - Errors: reference/errors.md
-  - "Cloud (alpha)":
+  - "Cloud (beta)":
       - "cloud/index.md"
       - Tutorials:
           - Quick Start: "cloud/quick_start.md"

libs/langgraph/README.md

@@ -216,4 +216,4 @@ final_state["messages"][-1].content
 * [How-to Guides](https://langchain-ai.github.io/langgraph/how-tos/): Accomplish specific things within LangGraph, from streaming, to adding memory & persistence, to common design patterns (branching, subgraphs, etc.), these are the place to go if you want to copy and run a specific code snippet.
 * [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
 * [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
-* [Cloud (alpha)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.
+* [Cloud (beta)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.