LangChain
langchain-ai.github.io › langgraphjs › reference › classes › langgraph.CompiledStateGraph.html
CompiledStateGraph | LangGraph.js API Reference
langgraph · CompiledStateGraph · Final result from building and compiling a StateGraph. Should not be instantiated directly, only using the StateGraph .compile() instance method. S · U · N extends string = typeof START · I extends SDZod = StateDefinition · O extends SDZod = StateDefinition ...
Langchain
reference.langchain.com › python › langgraph › graphs
graphs | langgraph | LangChain Reference
Python API reference for graphs in langgraph. Part of the LangChain ecosystem.
Videos
03:09:52
LangGraph Complete Course for Beginners – Complex AI Agents with ...
Ep-12. Visualizing the compiled Graph using Mermaid
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Creating an AI agent! Explaining how to use LangGraph
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LangGraph Crash Course #32 - Human In The Loop - Review Tool Calls ...
14:17
LangGraph Tutorial: Build Your First AI Workflow Graph - YouTube
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LangGraph Builder - YouTube
Langchain
reference.langchain.com › javascript › interfaces › _langchain_langgraph.index.CompiledGraph.html
CompiledGraph | langchain.js
CompiledGraph · CompiledStateGraph · Defined in remotes/langchain-ai/langgraphjs/main/libs/langgraph-core/src/graph/graph.ts:572 · ~ Node · Return · Type ~ Node · Type ~ Run · Input ~ Run · Output auto · Validate builder cache? channels checkpointer?
Baihezi
baihezi.com › mirrors › langgraph › reference › graphs › index.html
Graphs - LangGraph
Compiles the state graph into a CompiledGraph object.
Langchain
reference.langchain.com › javascript › langchain-langgraph › index › CompiledGraph
CompiledGraph | @langchain/langgraph | LangChain Reference
JavaScript/TypeScript API reference for index.CompiledGraph in @langchain/langgraph. Part of the LangChain ecosystem.
LangChain
langchain-ai.github.io › langgraphjs › reference › classes › langgraph.CompiledGraph.html
CompiledGraph | API Reference
langgraph · CompiledGraph · The Pregel class is the core runtime engine of LangGraph, implementing a message-passing graph computation model inspired by Google's Pregel system. It provides the foundation for building reliable, controllable agent workflows that can evolve state over time.
Langfuse
langfuse.com › guides › cookbook › integration_langgraph
Open Source Observability for LangGraph - Langfuse
March 10, 2026 - This instructs the graph "any time this node is run, you can exit." graph_builder.set_finish_point("chatbot") # To be able to run our graph, call "compile()" on the graph builder.
GitHub
github.com › langchain-ai › langgraph
GitHub - langchain-ai/langgraph: Build resilient language agents as graphs. · GitHub
3 days ago - Build resilient language agents as graphs. Contribute to langchain-ai/langgraph development by creating an account on GitHub.
Starred by 30.9K users
Forked by 5.3K users
Languages Python
LangChain
langchain.com › langgraph
LangGraph: Agent Orchestration Framework for Reliable AI Agents
Build controllable agents with LangGraph, our low-level agent orchestration framework
GitHub
github.com › langgraph4j › langgraph4j
GitHub - langgraph4j/langgraph4j: 🚀 LangGraph for Java. A library for develop AI Agentic Architectures in the Java ecosystem. Designed to work seamlessly with both Langchain4j and Spring AI.
Once you've defined all your nodes and edges in a StateGraph, you compile() it into a CompiledGraph<S extends AgentState>. This compiled graph is an immutable, runnable representation of your logic.
Starred by 1.6K users
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Languages Java 58.4% | Jupyter Notebook 37.7% | JavaScript 2.5% | Mustache 0.7% | HTML 0.4% | Shell 0.2%
Reddit
reddit.com › r/agentsofai › how to store a compiled graph (in langraph)
r/AgentsOfAI on Reddit: How to store a compiled graph (in langraph)
September 29, 2025 -
I've been working with langraph quite a while. I have pretty complex graph involving tools n all... which takes around 20 secomds to compile. Which lags the chatbot initiation... Is there a way to store the compiled graph??? If yes pleaseeee let me know.
Top answer 1 of 2
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LangGraph provides several methods for storing compiled graphs. The recommended approach is to use their serialization API which can export to JSON format. You can also use Python's pickle module for temporary storage, though this isn't recommended for production use. Search of r/AgentsOfAI : store compiled graph langgraph Broader subreddit search: store compiled graph langgraph across AI subs For production use cases, consider using LangGraph's built-in persistence layer or integrating with vector databases like Chroma through MCP servers. Always check the official LangGraph documentation first. (I am a bot) source
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For storing compiled LangGraph workflows, check LangGraph's persistence documentation about serializing state graphs. Common approaches include exporting as JSON or using built-in serialization methods. Search of r/AgentsOfAI : store compiled graph langgraph Broader subreddit search: store compiled graph across AI subs (I am a bot) source
Langchain
docs.langchain.com › langgraph-platform › graph-rebuild
Rebuild graph at runtime - Docs by LangChain
from langchain_openai import ChatOpenAI from langgraph.graph import END, START, MessageGraph model = ChatOpenAI(temperature=0) graph_workflow = MessageGraph() graph_workflow.add_node("agent", model) graph_workflow.add_edge("agent", END) graph_workflow.add_edge(START, "agent") agent = graph_workflow.compile() To make the server aware of your graph, you need to specify a path to the variable that contains the CompiledStateGraph instance in your LangGraph API configuration (langgraph.json), e.g.:
Reddit
reddit.com › r/langchain › wait, get_graph() is a runnable method and not compiledgraph method?
r/LangChain on Reddit: wait, get_graph() is a Runnable method and not CompiledGraph method?
June 29, 2024 -
Does this mean we can visualise a chain too since it is a runnable primitive? That's true! We can visualise all the runnable objects (chains, retrievers, graphs, tools). Here is a How-to and API docs reference.
Actually I was surprised to to find this out. I posted this in hopes that other people will be just as surprised. Visualisation helps understand a lot better. We tend to log to LangSmith just to get the sense of our workflow. If a part of the sense can be made locally, why not.
Another point is that it shows how this graph workflow is embedded deep into langchain_core. If you want to build a decent performing AI system, Graphs will be your bet.
Also LangGraph recently added contribution guidelines so docs will get better, so will the code.
Langchain
reference.langchain.com › javascript › classes › _langchain_langgraph.index.CompiledStateGraph.html
CompiledStateGraph | langchain.js
Defines additional configuration that can be passed to the graph at runtime via LangGraphRunnableConfig. ... Constrains what types nodes in this graph can return. Useful for enforcing consistent return patterns across all nodes. ... The type of values that can be passed when resuming from an ...
DataCamp
datacamp.com › tutorial › langgraph-tutorial
LangGraph Tutorial: What Is LangGraph and How to Use It? | DataCamp
June 26, 2024 - Compile the graph to create a CompiledGraph object, and optionally, we can visualize the graph structure using the code below:
Medium
medium.com › @ashutoshsharmaengg › getting-started-with-langgraph-a-beginners-guide-to-building-intelligent-workflows-67eeee0899d0
Getting Started with LangGraph: A Beginner’s Guide to Building Intelligent Workflows
June 15, 2025 - A comprehensive guide to LangGraph, covering core concepts, graph construction, and tool calling. Learn to build advanced AI agent workflows from scratch.
Bsorrentino
bsorrentino.github.io › LangGraph-Swift › documentation › langgraph › stategraph › compiledgraph
Documentation
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