LangGraph Studio primarily works with applications created using the LangGraph CLI. This is because LangGraph Studio is designed to work within the LangGraph ecosystem, which involves defining workflows, agents, and actions using LangGraph's specific structure and configuration format.
To clarify:
LangGraph CLI: This tool is used to create, configure, and initialize applications that are compatible with LangGraph Studio. It allows you to define the graph, agents, tasks, and workflows in a way that LangGraph Studio can interpret and visualize.
Regular Python Apps: If you have a regular Python app that doesn't adhere to LangGraph's predefined structure (i.e., it's not set up using the LangGraph CLI), you can't directly load it into LangGraph Studio without adapting it to the LangGraph framework.
Integration Options:
If you have a regular Python app that you want to integrate with LangGraph Studio, you would likely need to refactor it into the LangGraph framework, defining tasks, agents, and workflows in a way LangGraph Studio can handle.
Alternatively, you could wrap your existing Python logic in a way that it becomes part of the LangGraph structure by using LangGraph’s APIs and conventions for agents and workflows.
In summary, LangGraph Studio is tailored to apps created with LangGraph CLI, but with some effort, it is possible to adapt a regular Python application to fit into the LangGraph model for integration.
References:
OpenAI
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