Langchain agent framework. You want flexibility across LLM providers.

Langchain agent framework. Jan 3, 2025 · LangChain is a robust framework for building applications powered by large language models (LLMs). LangChain works as a toolkit that allows you to chain multiple language models together to create seamless workflow and task automation. This will assume knowledge of LLMs and retrieval so if you haven't already explored those sections, it is recommended you do so. Discover no-code solutions like Lindy and developer-friendly options like LangChain or CrewAI. Jan 26, 2025 · So that’s calling LLM with tools without an agent framework in langchain. Everyone seems to have a slightly different definition of what an AI agent is. Agentic RAG is an agent based approach to perform question answering over Introduction LangChain is a framework for developing applications powered by large language models (LLMs). Tool integrations: Connect LLMs to APIs, search engines, databases, and more. The interfaces for core components like chat models, vector stores, tools and more are defined here. Jun 17, 2025 · In this tutorial we will build an agent that can interact with a search engine. You plan to integrate multiple data sources or APIs. LangChain is a robust framework that helps developers define the logic, tools, memory, and workflows an agent needs to function more intelligently and, in a goal driven manner. Contribute to langchain-ai/langgraph development by creating an account on GitHub. 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. Jun 16, 2025 · Teams can use the best AI agent frameworks to automate tasks. Jul 4, 2025 · Discover 7 essential steps to building multi-AI agent workflows with LangChain—plus real examples, key benefits, and best practices from Intuz. Apr 4, 2025 · Explore AI Agent Frameworks like Langchain, CrewAI, and Microsoft Semantic Kernel. By combining LLMs with customized tools and adaptable execution environments, LangChain enables developers to bring sophisticated ideas to life. 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. May 9, 2025 · In this article, we’ll explore how to build effective AI agents using LangChain, a popular framework for creating applications powered by large language models (LLMs). ReAct framework: Similar to a chain of thought reasoning, however, it retraces to a prior step. Are you familiar with common agent structures, or do you want something telling you how you should structure your agent? Agents The core idea of agents is to use a language model to choose a sequence of actions to take. In agents, a language model is used as a reasoning engine to determine which actions to take and in which order. By understanding this spectrum of autonomy, developers can make informed decisions about the appropriate level of AI independence for their specific use cases. See the full . Today we are taking a few steps to build towards this vision. Trajectory: Evaluate whether the agent took the expected path (e. This approach is characterized by the following algorithm: Apr 8, 2024 · A brief look at the components of multi-agent frameworks and the current cutting edge options. 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. 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. Its key features include: Chain-of-thought reasoning: Build multi-step workflows. Learn to build smarter, adaptive systems today. 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. Jul 23, 2025 · LangChain is an open-source framework designed to simplify the creation of applications using large language models (LLMs). 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. Introduction LangChain is a framework for developing applications powered by large language models (LLMs). It explains how to use LangGraph and Amazon Bedrock to build powerful, interactive multi-agent applications that use graph-based orchestration. They enable large language models (LLMs) to interact with external tools and systems, extending their capabilities beyond 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. This walkthrough showcases using an agent to implement the ReAct logic. As such, our goal is to make langgraph the agent framework that gives you the most control over how these agents communicate. Compare features, learn when to use each, and see how to track agent behavior with Langfuse New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications. We believe that this new Command type is an improvement in that direction. Jul 30, 2025 · While LangChain supports multi-agent architectures through its extended components, the core framework lacks native agent-to-agent communication mechanisms. You will be able to ask this agent questions, watch it call the search tool, and have conversations with it. Jun 30, 2025 · Choosing the right agentic AI framework depends on your goals, complexity, and constraints. If you need to use Sep 20, 2024 · These three questions should help you decide which framework to use in your next agent project. 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. What is Langchain? Langchain is a powerful Python framework designed to help developers build context-aware Dec 27, 2023 · Reduced development time: LangChain’s intuitive framework and pre-built tools make it easier to build and deploy agents without needing extensive coding expertise. You setup a prompt with a scratchpad for the agent and invoke. This covers basics like Feb 13, 2024 · Plan and execute agents promise faster, cheaper, and more performant task execution over previous agent designs. 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 Apr 26, 2025 · 🧩 LangChain: Modular Framework for LLM Workflows Launched in early 2023, LangChain quickly became a go-to framework for building AI applications where LLMs interact with tools. The core idea of agents is to use a language model to choose a sequence of actions to take. By leveraging LangChain’s robust framework, the system integrates multiple Jun 26, 2025 · This article explains how to use LangChain with models deployed in Azure AI Foundry portal to build advance intelligent applications. Jun 28, 2024 · “What is an agent?” I get asked this question almost daily. Source: LangChain Interrupt 2025 Keynote If you’re building AI applications for enterprise, LangChain provides building blocks for multi-agent architectures and a range of Large Language Models (LLMs) and vector store integrations provided by 3rd parties. Build resilient language agents as graphs. 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. It provides a standard interface for chains, many integrations with other tools, and end-to-end chains for common applications. That means there are two main considerations when thinking about different multi-agent workflows: What are the multiple independent agents? How are those agents connected? This thinking lends itself incredibly well to a graph representation, such as that provided by langgraph. It provides standardized interfaces for models, embeddings, vector stores, tools, and memory. Nov 25, 2024 · Discover how to build autonomous AI agents using LangGraph, CrewAI, and OpenAI Swarm. It breaks down a query into actionable sub-tasks, and each task is followed Apr 18, 2023 · The stereotypical LangChain Agent is based on the Reasoning and Acting (ReAct) framework proposed by Yao et all in November of 2022. Sep 18, 2024 · Best Practices for Using Langchain Agents Tool Selection: Choose the right tools for your agent based on the task at hand. Why Use LangChain for AI Agents? Memory management: Enables agents to retain and recall past interactions. LangGraph is our controllable agent orchestration framework, with out-of-the-box state management and human-in-the-loop capabilities. This framework offers the building blocks required to develop anything from a basic search assistant to a sophisticated AI system communicating with several data sources and APIs. Mar 7, 2025 · In this post, we’ll focus on four notable AI agent frameworks: CrewAI, AutoGen, LangChain, and Pydantic AI. This means not only interacting with other LangGraph agents, but all other types of agents as well, regardless of how they are built. Use LangChain when you need fast integration and experimentation; use LangGraph when you need to build agents that can reliably handle complex tasks. We are announcing: * Agent Protocol: a common interface for agent Explore a detailed, developer-tested comparison of top AI agent frameworks in 2025, including LangGraph, DSPy, Agno and more. What is LangChain? LangChain is an open source orchestration framework for application development using 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. 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. g. May 19, 2025 · Learn about LangChain's Open Agent Network, its features, and how to get stared to make first no-code AI agent for free. Architecture LangChain is a framework that consists of a number of packages. note Jan 23, 2024 · Each agent can have its own prompt, LLM, tools, and other custom code to best collaborate with the other agents. Apr 29, 2025 · At the heart of this evolution lies LangChain, a powerful framework redefining the way developers build, orchestrate, and scale multi-agent systems. Let’s get into it. Why is Langchain Popular? Langchain’s popularity stems from its versatility and ease of use. Multi-agent Workflows The LangGraph framework can also be used to create multi-agent workflows. Compare features, architectures, and use cases to choose the right framework for your needs. Dec 29, 2024 · This guide explores the implementation of a multi-agent system designed to handle various tasks autonomously. In 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. As the name states, LangGraph was developed by the developer of LangChain and uses graph-based technology to initiate AI Agent systems. May 4, 2025 · LangChain was designed with agentic capabilities in mind. 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. Quick Start For a quick start to working with agents, please check out this getting started guide. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. Jul 2, 2025 · TL;DR Agents need context to perform tasks. Deploy and scale with LangGraph Platform, with APIs for state management, a visual studio for debugging, and multiple deployment options. Explore agents, tools, memory, and real-world AI applications in this practical guide. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. Productionization Build controllable agents with LangGraph, our low-level agent orchestration framework. Dec 10, 2024 · Conclusion Building agentic and multi-agent systems is all about communication. Although you have detailed control over the AI agent you build with LangChain, you need advanced coding skills. 1. Dec 26, 2024 · Creating AI agents that can interact with the real world is a great area of research and development. Jun 4, 2025 · In this blog post, we’ll explore what Langchain agents are, how they interact with local LLMs, and why running them locally is gaining momentum. May 2, 2023 · LangChain is a framework for developing applications powered by language models. Jun 5, 2025 · In Python, LangChain is now more downloaded than OpenAI on PyPI. May 28, 2025 · TL;DR Key Takeaways : The Open Agent Platform by LangChain is an open source framework designed to simplify the creation, testing, and deployment of intelligent agents, catering to both 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. 3, a state-of-the-art The framework is built from the ground up without dependencies on Langchain or other agent frameworks, giving developers complete control over system behavior. This includes systems that are commonly referred to as “agents”. By integrating tools and crafting intelligent agents, developers can automate complex workflows. 0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. May 22, 2025 · Compare LangChain and AutoGen—two top AI agent frameworks in 2025. Jul 6, 2025 · LangChain is a modular, open-source Python framework to simplify the building of advanced LLM applications. A simple guide to help you choose the right tools for building smarter, autonomous AI workflows. When to Use LangChain You need highly customized task flows and agent control. Why do LLMs need to use Tools? Aug 27, 2023 · C-O-T by Wei et al. langchain-core This package contains base abstractions for different components and ways to compose them together. Nov 13, 2024 · LangChain's agent framework represents a significant step forward in how we think about and implement AI systems. Dec 6, 2024 · Langchain is particularly useful for building conversational agents, information retrieval systems, and other applications where structured interaction with LLMs is essential. ##langchain agent Using an agent is much friendlier when invoking tools. In this post, we break down some common strategies — write, select, compress, and isolate — for context engineering Jun 26, 2025 · Discover how LangChain agents are transforming AI with advanced tools, APIs, and workflows. Oct 29, 2024 · A. Apr 20, 2025 · OpenAI’s guide on building agents (which I don’t think is particularly good) Anthropic’s guide on building effective agents (which I like a lot) LangGraph (our framework for building reliable agents) Background info Helpful context to set the stage for the rest of the blog. Context engineering is the art and science of filling the context window with just the right information at each step of an agent’s trajectory. What is an agent Apr 12, 2024 · Master Agent Framework in Langchain — Create Simple yet very powerfull agents to automate everything. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support. js to build stateful agents with first-class streaming and human-in-the-loop Jun 5, 2025 · Here’s a common scenario when building AI agents that might feel confusing: How can you use the latest Gemini models and an open-source framework like LangChain and LangGraph to create multimodal agents that can detect objects? Sep 9, 2024 · Compare a LangGraph, LlamaIndex Workflows, and pure code agent side-by-side to see the strengths and weaknesses of each approach. 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 The first AI Agent framework we will discuss is LangGraph. They are autonomous or semi-autonomous tools that can perform tasks, make Apr 24, 2025 · Major Agentic AI Frameworks LangChain LangChain is a Python framework for building agentic applications by chaining LLM reasoning with external tools, APIs, and memory modules Introduction | 🦜️🔗 LangChain. Perhaps at the heart of LangChain’s capabilities are LangChain agents. Setup: LangSmith By definition, agents take a self-determined, input-dependent LangChain’s ecosystem While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications. Deprecated since version 0. Jun 2, 2024 · LangChain offers a robust framework for working with agents, including: - A standard interface for agents. Apr 4, 2025 · Your ideas may become a reality using LangChain’s Agent framework. , of tool calls) to arrive at the final answer. Ensure that the LLM understands when and how to invoke these tools. 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. 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. Just like in the self-reflecting AI agent, the LLM can take on multiple roles, each acting as a different AI agent. 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. One of its most exciting aspects is the Agents Jun 17, 2025 · Build a smart agent with LangChain that allows LLMs to look for the latest trends, search the web, and summarize results using real-time tool calling. LangGraph provides control for custom agent and multi-agent workflows, seamless human-in-the-loop interactions, and native streaming support for enhanced agent reliability and execution. 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. 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 Apr 18, 2025 · Discover the most popular AI agent frameworks like LangChain and AutoGen. 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. Feb 21, 2024 · Reflection is a prompting strategy used to improve the quality and success rate of agents and similar AI systems. In chains, a sequence of actions is hardcoded (in code). LangGraph is an extension of LangChain specifically aimed at creating highly controllable and customizable agents. The dependencies are kept purposefully very lightweight May 7, 2025 · Learn how to build agentic systems using Python and LangChain. Apr 17, 2025 · Explore the key differences between LangGraph, AutoGen, and CrewAI to choose the ideal multi-agent framework for your AI development needs. You want flexibility across LLM providers. You’re experimenting with reasoning patterns or agent collaboration. Learn how to build 3 types of planning agents in LangGraph in this post. No third-party integrations are defined here. 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. This post outlines how to build 3 reflection techniques using LangGraph, including implementations of Reflexion and Language Agent Tree Search. In this comprehensive guide, we’ll 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. - A variety of pre-built agents to choose from. Agent Protocol is our attempt at codifying the framework-agnostic APIs that are needed to serve LLM agents in production. Jun 13, 2025 · LangChain, Microsoft AutoGen, LangGraph, CrewAI, Semantic Kernel, and Nemo Microservices are 6 best open-source AI agent frameworks for developers in 2025. Using IBM Granite models and LangChain, the agent is built following the principles outlined in the framework for LLM-based autonomous agents. This means we can detail every step and direction the agents take in a way that the graph could be. (we're trying to fix this in LangChain as well - revamping the architecture to split out integrations, having langchain-core as a separate thing). 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. At its core, CrewAI enables agents to assume specific roles within a crew, share goals, and operate as a cohesive unit. Dec 12, 2024 · Build LangChain agents step by step to create AI assistants that automate tasks and integrate advanced tools seamlessly. Each of these platforms approaches the idea of AI “agents” differently. This document explains the purpose of the protocol and makes the case for each of the endpoints in the spec. Mar 31, 2024 · In Native RAG the user is fed into the RAG pipeline which does retrieval, reranking, synthesis and generates a response. This tutorial demonstrates the creation of a queryable knowledge agent designed to process large text documents (like books) and answer user queries accurately. Its comprehensive set of tools and components allows you to build end-to-end AI solutions using almost any LLM. The framework's components align seamlessly with the agent's workflow to ensure adaptability Jan 3, 2025 · LangChain agents are a pivotal component of the LangChain framework. Memory modules: Let agents remember past interactions. , prompts, models, tools) using the LangChain Expression Language LangChain is designed for connecting LLMs to data sources with minimal setup. When to Use OpenAI Agents You want to launch quickly with 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. For details, refer to the LangGraph documentation as well as guides for Nov 11, 2024 · Conclusion LangChain’s Agent Framework is an exciting advancement for AI developers, offering the building blocks to create smart, autonomous systems. LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source components and third-party integrations. Apr 14, 2025 · This post demonstrates how to integrate open-source multi-agent framework, LangGraph, with Amazon Bedrock. We’ll also walk through a practical setup, list the tools you’ll need, and discuss use cases where local LLM agents make the most sense. Single step: Evaluate any agent step Jan 21, 2025 · LangChain Overview LangChain is an AI agent framework designed to help developers build, manage, and deploy custom AI agents. For a video guide of this, see our walkthrough on YouTube. What is an Agent? In this tutorial, we'll build a customer support bot that helps users navigate a digital music store. 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. Are you already using LlamaIndex or LangChain for significant pieces of your project? If yes, explore that option first. Oct 21, 2024 · LangChain is an established framework with tons of community support, documentation, and useful tools. To improve your LLM application development, pair LangChain with: LangSmith - Helpful for agent evals and observability. Apr 11, 2024 · Quickstart 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. My Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. We recommend that you use LangGraph for building agents. Learn their strengths, architectures, best use cases, and which is best for your next AI-powered application. Use LangGraph. Understand their key importance in AI development. Nov 19, 2024 · LangGraph is a multi-agent framework. This guide provides explanations of the key concepts behind the LangChain framework and AI applications more broadly. One useful application is building agents capable of searching the web to gather information and complete tasks. 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 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 Apr 15, 2025 · Langchain focuses on modularity and composability, allowing developers to build agents and workflows by combining components (e. nwcehwo sbsxom gpxtd orscyvdnq vuragr qvbwq wemhqjk hbu juhsok cvira