Langchain agent framework. You can use an agent with a different type of model than it is intended for, but it likely won't produce Jul 1, 2025 · Learn how LangChain agents use reasoning-action loops to tackle complex tasks, integrate tools, and refine outputs in real time. Their framework enables you to build layered LLM-powered applications that are context-aware and able to interact dynamically with their environment as agents, leading to simplified code for you and a more dynamic user experience for your customers. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. Auto-email agents that read emails, draft responses, and take follow-up actions. @langchain/community: Third party integrations. Nov 16, 2024 · 2. LangChain's agent framework represents a significant step forward in how we think about and implement AI systems. This document explains the purpose of the protocol and makes the case for each of the endpoints in the spec. (we're trying to fix this in LangChain as well - revamping the architecture to split out integrations, having langchain-core as a separate thing). While optimized for Gemini and the Google ecosystem, ADK is model-agnostic, deployment-agnostic, and is built for compatibility with other frameworks. As the name states, LangGraph was developed by the developer of LangChain and uses graph-based technology to initiate AI Agent systems. Learn how to build 3 types of planning agents in LangGraph in this post. Agents can be simple, consisting of a prompt and an LLM call, or more complex This project showcases the creation of a ReAct (Reasoning and Acting) agent using the LangChain library. 5 days ago · Author an AI agent in Python, using Mosaic AI Agent Framework and popular agent authoring libraries like LangGraph, PyFunc, and OpenAI. Apr 14, 2025 · This post demonstrates how to integrate open-source multi-agent framework, LangGraph, with Amazon Bedrock. LangGraph utilizes graphs to create a multi-agent or single agent structure. Its architecture allows developers to integrate LLMs with external data, prompt engineering, retrieval-augmented generation (RAG), semantic search, and agent workflows. Apr 10, 2025 · From LangChain to AutoGen: Meet the Python Frameworks Behind Smart Agents Agentic AI frameworks are software platforms designed to help developers create autonomous agents capable of interacting with environments, making decisions, and achieving goals with minimal human intervention. While both LangChain and LangGraph aim to simplify the development of AI agents, they cater to different needs and complexities. Aug 27, 2023 · C-O-T by Wei et al. We believe that this new Command type is an improvement in that direction. 0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. . Apr 12, 2024 · Master Agent Framework in Langchain — Create Simple yet very powerfull agents to automate everything. May 20, 2025 · Read how top AI agent frameworks, including LangGraph, LlamaIndex, CrewAI, Semantic Kernel, AutoGen, and Swarm, compare in terms of features, use cases & more. Same Mar 1, 2025 · Learn how LangGraph, an AI agent framework built by LangChain, allows developers to create complex and flexible agent workflows using stateful graphs and built-in memory management. The dependencies are very lightweight. For details, refer to the LangGraph documentation as well as guides for Feb 13, 2024 · Plan and execute agents promise faster, cheaper, and more performant task execution over previous agent designs. Most of the difference between these frameworks largely lies in the mental models and concepts they introduce. What is Agent Development Kit? Agent Development Kit (ADK) is a flexible and modular framework for developing and deploying AI agents. 1. At LangChain, we build tools to help developers build LLM applications, especially those that act as a reasoning engines and interact with external sources of data and computation. Jun 17, 2025 · LangChain supports the creation of agents, or systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. Agent Types This categorizes all the available agents along a few dimensions. Perhaps at the heart of LangChain’s capabilities are LangChain agents. Explore components, chains, agents, and its ecosystem for seamless development. This means not only interacting with other LangGraph agents, but all other types of agents as well, regardless of how they are built. Productionization 4 days ago · While LangChain supports multi-agent architectures through its extended components, the core framework lacks native agent-to-agent communication mechanisms. Multi-agent Workflows The LangGraph framework can also be used to create multi-agent workflows. This orchestration layer acts as the conductor, coordinating how agents interact, sequence their tasks, share context, and respond to failures all within a structured but flexible framework. To build such agents, you need powerful frameworks like LangChain and LangGraph. Deprecated since version 0. Hit the ground running using third-party integrations and Templates. Architecture LangChain is a framework that consists of a number of packages. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. Dec 10, 2024 · Conclusion Building agentic and multi-agent systems is all about communication. Jun 11, 2025 · Author an AI agent in Python, using Mosaic AI Agent Framework and popular agent authoring libraries like LangGraph, PyFunc, and OpenAI. If you need to use Oct 29, 2024 · A. Intended Model Type Whether this agent is intended for Chat Models (takes in messages, outputs message) or LLMs (takes in string, outputs string). No third-party integrations are defined here. The downside is that it adds another dependency to your project, which means there’s a higher chance of something breaking with future updates. Mar 19, 2025 · Get an overview of the leading open-source AI agent frameworks—LangGraph, OpenAI Agents SDK, Smolagents, CrewAI, AutoGen, Semantic Kernel, LlamaIndex agents, Strands Agents, and Pydantic AI agents. Just like in the self-reflecting AI agent, the LLM can take on multiple roles, each acting as a different AI agent. Quick Start For a quick start to working with agents, please check out this getting started guide. The framework is built from the ground up without dependencies on Langchain or other agent frameworks, giving developers complete control over system behavior. It explains how to use LangGraph and Amazon Bedrock to build powerful, interactive multi-agent applications that use graph-based orchestration. The core idea of agents is to use a language model to choose a sequence of actions to take. Apr 4, 2025 · LangChain Agent Framework enables developers to create intelligent systems with language models, tools for external interactions, and more. How to: pass in callbacks at runtime How to: attach callbacks to a module How to: pass callbacks into a module constructor How to: create custom callback handlers How to: use callbacks in Nov 19, 2024 · LangGraph is a multi-agent framework. Why do LLMs need to use Tools? Jul 3, 2025 · LangChain has emerged as a go-to framework for developers building LLM-powered applications, simplifying the handling of complex workflows with its modular tools and robust abstractions. @langchain/core: Base abstractions and LangChain Expression Language. g. By integrating tools and crafting intelligent agents, developers can automate complex workflows. Mar 10, 2025 · How LangChain provides a flexible, chain-of-thought framework for everything from simple chat to multi-step agent orchestration, How smolagent ’s code-generation paradigm can handle advanced logic and tool usage with remarkable transparency. Today we are taking a few steps to build towards this vision. Apr 29, 2025 · LangChain Multi-Agent Orchestration One of the defining advances in LangChain’s 2025 evolution is its sophisticated multi-agent orchestration engine. In agents, a language model is used as a reasoning engine to determine which actions to take and in which order. Then, we'll go through the three most effective types of evaluations to run on chat bots: Final response: Evaluate the agent's final response. It provides a standard interface for chains, many integrations with other tools, and end-to-end chains for common applications. One of its most exciting aspects is the Agents Jun 28, 2024 · “What is an agent?” I get asked this question almost daily. ADK was designed to make agent development feel more like software development, to make it easier for May 2, 2023 · LangChain is a framework for developing applications powered by language models. Its comprehensive set of tools and components allows you to build end-to-end AI solutions using almost any LLM. LangChain works as a toolkit that allows you to chain multiple language models together to create seamless workflow and task automation. This blog post will guide you through the process of creating such an agent using LangChain, a framework for developing LLM-powered applications, and Llama 3. Build agents any way you want, then deploy and scale with ease LangGraph Platform works with any agent framework, enabling stateful UXs like human-in-the-loop and streaming-native deployments. For a given state of the world it think about what its next immediate action should be, and then does that action. See the full Apr 17, 2025 · Explore the key differences between LangGraph, AutoGen, and CrewAI to choose the ideal multi-agent framework for your AI development needs. Productionization: Use LangSmith to inspect, monitor Feb 9, 2025 · LangChain is a highly flexible, open-source framework known for its modular approach to LLM application development. Jan 23, 2024 · LangGraph is not the first framework to support multi-agent workflows. Mar 6, 2025 · As Harrison Chase, CEO of LangChain, explains, “Multi-agent systems are the future of AI, but we need open standards for both collaboration and rigorous assessment. Jun 30, 2025 · LangChain agents are one of the most powerful features of the framework. Sep 9, 2024 · Compare a LangGraph, LlamaIndex Workflows, and pure code agent side-by-side to see the strengths and weaknesses of each approach. It gives developers full control to wire together language models, memory stores, tools, and prompts. Mar 6, 2025 · Overview of LangChain vs. Jan 21, 2025 · LangChain Overview LangChain is an AI agent framework designed to help developers build, manage, and deploy custom AI agents. This walkthrough showcases using an agent to implement the ReAct logic. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support. LangChain is designed for connecting LLMs to data sources with minimal setup. We are announcing: * Agent Protocol: a common interface for agent 3 days ago · LangChain is the most widely adopted open-source framework for building LLM-powered agents. , prompts, models, tools) using the LangChain Expression Language LangChain is another open-source framework for building LLM-powered applications, including chatbots such as ChatGPT and AI agents. Mar 24, 2025 · This Agent SDK, vs LangChain vs CrewAI guide explores when to use each framework to maximize the efficiency and performance of your AI agents Nov 25, 2024 · Discover how to build autonomous AI agents using LangGraph, CrewAI, and OpenAI Swarm. Feb 6, 2025 · LangChain is an open-source framework designed to simplify the creation of applications using large language models (LLMs). The interfaces for core components like chat models, vector stores, tools and more are defined here. Agents The core idea of agents is to use a language model to choose a sequence of actions to take. Agent Protocol is our attempt at codifying the framework-agnostic APIs that are needed to serve LLM agents in production. Library modules include: Quick Start To best understand the agent framework, let’s build an agent that has two tools: one to look things up online, and one to look up specific data that we’ve loaded into a index. Are you familiar with common agent structures, or do you want something telling you how you should structure your agent? Apr 18, 2023 · In the traditional LangChain Agent framework (and the AutoGPT framework), the agent thinks one step ahead at a time. Self-ask Tools for every task LangChain offers an extensive library of off-the-shelf tools u2028and an intuitive framework for customizing your own. Agentic is in the tradition of opinionated frameworks. Introduction LangChain is a framework for developing applications powered by large language models (LLMs). LangGraph The first AI Agent framework we will discuss is LangGraph. Single step: Evaluate any agent step Nov 25, 2024 · Discover the leading frameworks to build performant and trusted AI agents tailored for business enterprises. Jan 3, 2025 · Langchain LangChain is a robust framework for building applications powered by large language models (LLMs). My Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. Nov 22, 2024 · LangChain is a powerful framework designed to build AI-powered applications by connecting language models with various tools, APIs, and data sources. These agents are increasingly important in areas like workflow automation, smart assistants, research agents Feb 22, 2025 · What is LangChain? LangChain is an open-source framework that enables the development of context-aware AI agents by integrating Large Language Models (LLMs) like OpenAI’s GPT-4, knowledge graphs, APIs, and external tools. LangGraph is an extension of LangChain specifically aimed at creating highly controllable and customizable agents. Trajectory: Evaluate whether the agent took the expected path (e. They let your application go beyond static chains by making decisions dynamically—choosing which tools to use and how to use them based on the task. Using IBM Granite models and LangChain, the agent is built following the principles outlined in the framework for LLM-based autonomous agents. Why Use LangChain for AI Agents? Memory management: Enables agents to retain and recall past interactions. Understand core components, compare LangChain vs AutoGen vs CrewAI, and build agents easily with our guide. It provides a standardized interface for working with various agent types, allowing developers to leverage the strengths of different agent libraries while maintaining a consistent programming model. It breaks down a query into actionable sub-tasks, and each task is followed Build controllable agents with LangGraph, our low-level agent orchestration framework. What is LangChain? LangChain is an open source orchestration framework for application development using large language models (LLMs). Discover top AI agent frameworks for 2025 & find the best fit for your project’s needs, from multitasking tools to memory-enabled agents. I don't think any other agent frameworks give you the same level of controllability We've also tried to learn from LangChain, and conciously keep LangGraph very low level and free of integrations. We've tried to encode lots of sensible defaults and best practices into the design, testing and deployment of agents. Below is a detailed walkthrough of LangChain’s main modules, their roles, and code examples, following the latest In this tutorial, we'll build a customer support bot that helps users navigate a digital music store. Dec 26, 2024 · Creating AI agents that can interact with the real world is a great area of research and development. We finish by listing some roadmap items for the future. LangGraph offers a more flexible and full-featured framework for building agents, including support for tool-calling, persistence of state, and human-in-the-loop workflows. In this comprehensive guide, we’ll Apr 20, 2025 · Declarative vs non-declarative Agent abstractions Multi agent Common Questions What is the value of a framework? As the models get better, will everything become agents instead of workflows? What did OpenAI get wrong in their take? How do all the agent frameworks compare? Throughout this blog I will make repeated references to a few materials: Jul 1, 2025 · Learn how LangChain agents use reasoning-action loops to tackle complex tasks, integrate tools, and refine outputs in real time. Agents are systems that take a high-level task and use an LLM as a reasoning engine to decide what actions to take and execute those actions. This tutorial demonstrates the creation of a queryable knowledge agent designed to process large text documents (like books) and answer user queries accurately. Although you have detailed control over the AI agent you build with LangChain, you need advanced coding skills. The LangChain libraries themselves are made up of several different packages. It’s particularly popular with developers who need fine-grained control over their AI agents’ workflows. The ReAct framework is a powerful approach that combines reasoning capabilities with actionable outputs, enabling language models to interact with external tools and answer complex questions May 1, 2024 · This method of using the same LLM in two different roles in a cyclical manner is facilitated by the LangGraph framework from LangChain. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks, components, and third-party integrations. js to build stateful agents with first-class streaming and human-in-the-loop New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications. Unlike AutoGen’s message-passing system or CrewAI’s role-based teams, LangChain’s base architecture routes everything through a central orchestrator rather than enabling direct agent Jan 16, 2025 · The Langchain Agent UI, powered by the open source CoAgent framework, simplifies the creation of adaptive, production-ready AI agents by integrating memory, knowledge, tools, and reasoning. Nov 6, 2024 · LangChain is revolutionizing how we build AI applications by providing a powerful framework for creating agents that can think, reason, and take actions. May 18, 2025 · The swarms framework is a powerful and flexible system designed to facilitate the creation, management, and coordination of multiple AI agents. Agentic makes it easy to create AI agents - autonomous software programs that understand natural language and can use tools to do work on your behalf. What is an Agent? Dec 16, 2024 · Discover LangChain: an orchestration framework for LLM applications. Nov 6, 2024 · In this article, we’ll break down the concept of agents, and show how you can create a simple agent using Azure Openai credentials and Langchain framework. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. Emphasize is on how to use LangChain /Agents capabilities to monitor an API’s health and send email alerts if the service is down. A simple guide to help you choose the right tools for building smarter, autonomous AI workflows. This includes systems that are commonly referred to as “agents”. We recommend that you use LangGraph for building agents. This guide provides explanations of the key concepts behind the LangChain framework and AI applications more broadly. 3, a state-of-the-art Jul 4, 2025 · LangChain is a modular framework designed to build applications powered by large language models (LLMs). Mar 6, 2025 · The Agent Protocol, launched in November last year, allows LangChain agents to talk to agents created with AutoGen, CrewAI or any other framework. Compare features, learn when to use each, and see how to track agent behavior with Langfuse Sep 20, 2024 · These three questions should help you decide which framework to use in your next agent project. Agentic is a few different things: A lightweight agent framework. Contribute to langchain-ai/langgraph development by creating an account on GitHub. Apr 4, 2025 · Explore AI Agent Frameworks like Langchain, CrewAI, and Microsoft Semantic Kernel. Apr 8, 2024 · A brief look at the components of multi-agent frameworks and the current cutting edge options. These systems represent a shift from static prompt-response LLMs to interactive, goal-oriented agents. This means we can detail every step and direction the agents take in a way that the graph could be. langchain-core This package contains base abstractions for different components and ways to compose them together. One useful application is building agents capable of searching the web to gather information and complete tasks. By understanding this spectrum of autonomy, developers can make informed decisions about the appropriate level of AI independence for their specific use cases. LangChain is a framework designed for building applications that integrate Large Language Models (LLMs) with various external tools and APIs, enabling developers to create intelligent agents capable of performing complex tasks. Aug 28, 2024 · LangChain’s 90k GitHub stars are all the credibility it needs—right now, it is the hottest framework to build LLM-based applications. Let’s understand why LangChain is the go-to framework for building agentic AI. The core strength of LangChain is its ability to build applications involving LLMs and complex workflows. Feb 24, 2025 · A step-by-step guide on how to build a context-aware agent that fetches real-time data, and deploy it in real-world use cases. Two prominent contenders in this space are smolagents (from Hugging Face) and LangGraph (from LangChain). ReAct framework: Similar to a chain of thought reasoning, however, it retraces to a prior step. langchain The main Apr 18, 2025 · Discover the most popular AI agent frameworks like LangChain and AutoGen. Jun 26, 2025 · This article explains how to use LangChain with models deployed in Azure AI Foundry portal to build advance intelligent applications. As such, our goal is to make langgraph the agent framework that gives you the most control over how these agents communicate. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks and components. Feb 9, 2024 · LangChain Libraries: the core of the framework that contains modules, known as primitives, and a runtime for creating chains and agents. langchain: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. , of tool calls) to arrive at the final answer. Let’s get into it. Everyone seems to have a slightly different definition of what an AI agent is. It can be easily integrated with APIs, databases, and external tools, making it highly flexible for How to: use legacy LangChain Agents (AgentExecutor) How to: migrate from legacy LangChain agents to LangGraph Callbacks Callbacks allow you to hook into the various stages of your LLM application's execution. LangGraph is our controllable agent orchestration framework, with out-of-the-box state management and human-in-the-loop capabilities. Oct 21, 2024 · LangChain is an established framework with tons of community support, documentation, and useful tools. In chains, a sequence of actions is hardcoded (in code). The main thing this affects is the prompting strategy used. This covers basics like Introduction LangChain is a framework for developing applications powered by large language models (LLMs). Use LangGraph. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source components and third-party integrations. Setup: LangSmith By definition, agents take a self-determined, input Dec 10, 2024 · Compare the top 3 agentic AI frameworks of 2024: LangGraph, AutoGen, and CrewAI. LangGraph LangGraph is a framework built upon the Langchain library and uses its many functions and tools. This will assume knowledge of LLMs and retrieval so if you haven’t already explored those sections, it is recommended you do so. Jan 29, 2025 · The rise of large language models (LLMs) has spurred the development of frameworks to build AI agents capable of dynamic decision-making and task execution. This article delves into the features and capabilities of both these models, providing a detailed comparison of smolagents vs Mar 5, 2025 · LangChain provides a flexible and customizable environment for building agents with its LangGraph framework 1. Apr 15, 2025 · Langchain focuses on modularity and composability, allowing developers to build agents and workflows by combining components (e. Understand their key importance in AI development. LangGraph When building applications with Large Language Models (LLMs), choosing the right framework can significantly impact your project's efficiency and scalability. Compare features, architectures, and use cases to choose the right framework for your needs. Build resilient language agents as graphs. LangChain: simplifying LLM interactions LangChain is an open-source Apr 28, 2025 · Explore LLM agent frameworks in 2025. Learn when to use each framework—and when to build your own solution—from an AI strategist's hands-on experience implementing multi-agent AI systems. Available in both Python- and Javascript-based libraries, LangChain’s tools and APIs simplify the process of building LLM-driven applications like chatbots and AI agents. At its core, CrewAI enables agents to assume specific roles within a crew, share goals, and operate as a cohesive unit. Are you already using LlamaIndex or LangChain for significant pieces of your project? If yes, explore that option first. For a video guide of this, see our walkthrough on YouTube. They are autonomous or semi-autonomous tools that can perform tasks, make Dec 12, 2024 · Build LangChain agents step by step to create AI assistants that automate tasks and integrate advanced tools seamlessly. The framework's components align seamlessly with the agent's workflow to ensure adaptability Dec 23, 2024 · LangChain is the most widely adopted framework for building AI agents. Use LangChain when you need fast integration and experimentation; use LangGraph when you need to build agents that can reliably handle complex tasks. It employs a modular architecture, with each module representing abstractions that encapsulate the complex concepts and steps necessary to work with LLMs. It gives developers the core components to wire up tools, prompts, memory, and reasoning, with full control over how agents operate. tdqefvpud sztac fmu vowl euqw ftsd qswgty dtwln beh hbsels