LangChain
LangChain is an open-source framework for developing applications powered by Large Language Models (LLMs), streamlining the integration of powerful LLMs like Op...
LangGraph is a powerful tool for creating dynamic, stateful, multi-actor workflows with LLMs, supporting cycles, branching, persistence, and human-agent collaboration.
LangGraph is an advanced library designed for building stateful, multi-actor applications using Large Language Models (LLMs). Developed by LangChain Inc, LangGraph extends the capabilities of the LangChain library by introducing cyclic computational abilities. This allows for the creation of complex, agent-like behaviors where an LLM can operate in a loop, making decisions at each step.
LangGraph is a powerful tool that enables developers to create intricate workflows involving multiple actors and steps. Unlike traditional Directed Acyclic Graphs (DAGs) used in LangChain, LangGraph supports cycles, making it ideal for applications that require repeated decision-making and state management.
A stateful graph is the core concept of LangGraph. Each node in the graph represents a computational step, and the graph maintains a state that is updated as the computation progresses. This stateful nature allows for more dynamic and flexible workflows.
Nodes are the fundamental building blocks of a LangGraph. Each node performs a specific function or computation, such as processing input, making decisions, or interacting with external APIs.
Edges connect nodes and define the flow of computation within the graph. LangGraph supports conditional edges, allowing the flow to change dynamically based on the current state.
LangGraph allows for the implementation of loops and conditionals within your applications, providing greater flexibility and control over the flow of computations.
One of the standout features of LangGraph is its built-in persistence. It automatically saves the state after each step, enabling error recovery, human-in-the-loop workflows, and even time travel to previous states for different actions.
LangGraph supports human-agent collaboration by allowing interruptions in the graph execution. Users can approve or edit the next action planned by the agent, ensuring better control and reliability.
For better user experience, LangGraph includes native support for streaming outputs, both token-by-token and for intermediate steps, offering dynamic and interactive user interactions.
While LangGraph can be used independently, it integrates seamlessly with LangChain and LangSmith, providing a comprehensive suite for building and managing LLM-based applications.
To install LangGraph, you can use the following command:
pip install -U langgraph
For the JavaScript version, use:
npm install @langchain/langgraph
LangGraph is ideal for creating workflows that involve multiple agents or actors, each performing specific tasks and making decisions in a coordinated manner.
LangGraph’s ability to handle cycles and state persistence makes it perfect for applications requiring complex decision-making and error recovery mechanisms.
With built-in support for human-in-the-loop interactions, LangGraph ensures that agents can collaborate effectively with human users, making it suitable for applications requiring high reliability and control.
LangGraph is a library developed by LangChain Inc for building stateful, multi-actor applications with LLMs. It introduces cyclic computational abilities, enabling complex workflows and agent-like behaviors.
While LangChain is based on Directed Acyclic Graphs (DAGs), LangGraph supports cycles, persistence, and more dynamic state management, making it suitable for complex, iterative workflows.
Key features include cycles and branching, state persistence, human-in-the-loop support, streaming outputs, and seamless integration with LangChain and LangSmith.
LangGraph is ideal for developers building advanced AI workflows, especially those requiring multi-agent coordination, human-agent collaboration, and robust error recovery.
Start building your own AI solutions and dynamic workflows using LangGraph and FlowHunt's intuitive platform.
LangChain is an open-source framework for developing applications powered by Large Language Models (LLMs), streamlining the integration of powerful LLMs like Op...
Large Language Model Meta AI (LLaMA) is a cutting-edge natural language processing model developed by Meta. With up to 65 billion parameters, LLaMA excels at un...
LazyGraphRAG is an innovative approach to Retrieval-Augmented Generation (RAG), optimizing efficiency and reducing costs in AI-driven data retrieval by combinin...