langgraph editor

This tool is designed to speed up your AI Agent development. It help to visually edit langgraph workflow. You can open the notebook in google's colab. Below is the interface of the tool. It is based on litegraph.js as its workflow engine (the same as ComfyUI). You can add, remove, and layout different nodes as you wish, get the workflow as you wish. As it is visualized and editable, it is easier for understanding and modifying.

Installation

Local machine

pip3 install -q tornado
git clone https://github.com/Erickrus/langgraph-editor

Google colab

ngrok or other NAT Traversal tool is required (e.g. cpolar) is used to display the iframe.

When using ngrok, you need input NGROK_AUTH_KEY and NGROK_BEARER_API_KEY.

Run

Local machine

open the url http://localhost:8082/static/index.html in your browser.

Google colab

In google colab, run through the cells, and you will see the interface.

Nodes

3 types of nodes are added, including:

• LangGraphNode: normal workflow node
• LangGraphConditionalNode: work as the conditional edge
• LangGraphEndNode: END

Compile the workflow to python code

When finish editing the workflow, click Compile menuitem to compile the workflow as a python script. The file will be saved as /content/output.py by default. Following is the output python script

from langgraph.graph import END, StateGraph
workflow = StateGraph(GraphState)

# Define the nodes
workflow.add_node("query", query) # query
workflow.add_node("web_search", web_search) # web_search

# Build graph
workflow.add_conditional_edge(
    "query",
    decide,
    {
        "end": END,
        "web_search": "web_search",

    })
workflow.set_entry_point("query")
workflow.add_edge("web_search", END)

# Compile
app = workflow.compile()

Load and Save workflow

The workflow can be loaded or saved locally from or to /content/workflow.json .