Langchain initialize agent. agents import initialize_agent from langchain.
- Langchain initialize agent. pull("hwchase17/openai from langchain. Why Use LangChain for AI Agents? Memory management: Enables agents to retain and recall past interactions. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. Class hierarchy: from langchain. from langchain. llms import OpenAI llm = OpenAI(temperature=0) tools = load_tools(["llm-math"], llm Jan 3, 2025 · Langchain is an advanced framework that helps developers build sophisticated applications powered by large language models (LLMs). 3. tools import BaseTool from langchain. 【解决方案】用initialize_agent llm就按照这篇文章配置任意一个 LangChain连接国内大模型测试|智谱ai、讯飞星火、通义千问 May 31, 2025 · 文章介绍多种代理类型及适用模型，如OpenAI Tools、OpenAI Functions等，阐述其支持特性。还给出ZERO_SHOT_REACT_DESCRIPTION等多种代理类型的代码示例，展示如何使用工具和模型实现相关功能，作者有丰富AI应用开发等经验。 1. Our goal with LangChainHub is to be a single stop shop for sharing prompts, chains, agents and more. CONVERSATIONAL_REACT_DESCRIPTION to initialize a conversation react agent in LangChain v0. Setting the global debug flag will cause all LangChain components with callback support (chains, models, agents, tools, retrievers) to print the inputs they receive and outputs they generate. jsOptions for the agent, including agentType, agentArgs, and other options for AgentExecutor. Class hierarchy: Learn how to build LangChain agents in Python. May 5, 2024 · 十、定义提示语 LangChain v0. As a starting point, we’re launching the hub with a repository of prompts used in LangChain. 2w次，点赞47次，收藏62次。langchain 中提供了内置工具的，但是基本不能用，除了一个计算器和一个执行 python 代码的，其他的都要 apiTool 模块相当于是使用外部工具，或者自定义工具。_langchain agent tool Aug 5, 2024 · Whether you are developing a conversational agent, an automated research assistant, or a complex data analysis tool, LangChain agents offer a robust solution to enhance your project’s capabilities. By leveraging agents, you can significantly enhance the capabilities of the OpenAI API and seamlessly integrate external tools. Agent [source] # Bases: BaseSingleActionAgent Deprecated since version 0. While it’s commonly known for its ability to generate text, Langchain goes beyond that by introducing agents and tools —two key components that enable more complex, multi-step workflows. What Can You Build with LangChain? Dec 9, 2024 · [docs] @abstractmethodasyncdefaplan(self,intermediate_steps:List[Tuple[AgentAction,str]],callbacks:Callbacks=None,**kwargs:Any,)->Union[AgentAction,AgentFinish Sep 10, 2023 · 少し余談ですが、langchainのチュートリアルによく出てくるinitialize_agent関数の戻り値はAgentではなくAgentExecutorです。 またinitialize_agentにはagentという引数を与えることができるのですが、このagentはAgentクラスではなくAgentTypeという文字列です。 May 25, 2025 · LangChain 是一個開源框架，讓你可以更方便地構建基於大型語言模型（LLMs）的應用程式。 它能幫你整合 prompt 模版、LLM記憶功能、串接外部感知工具、資料檢索與代理人（Agents），讓 LLM 從單純來回回答問題進化為解決任務的智慧系統，也提供非常好用的 Python 套件，方便你快速建構與整合語言模型和 May 22, 2024 · Learn how to build AI Agents with LangChain and GPT-4 from OpenAI. callbacks import BaseCallbackManager from langchain_core. LangGraph is an extension of LangChain specifically aimed at creating highly controllable and customizable agents. 27 # Main entrypoint into package. initialize_agent(tools: Sequence[BaseTool], llm: BaseLanguageModel, agent: Optional[AgentType] = None, callback_manager: Optional[BaseCallbackManager] = None, agent_path: Optional[str] = None, agent_kwargs: Optional[dict] = None, *, tags: Optional[Sequence[str]] = None, **kwargs: Any) → AgentExecutor [source Memory in Agent This notebook goes over adding memory to an Agent. In my current code I can't seem to handle the output of the agent and the prints i wrote never happen. initialize_agent(tools: Sequence[BaseTool], llm: BaseLanguageModel, agent: Optional[AgentType] = None, callback_manager: Optional[BaseCallbackManager] = None, agent_path: Optional[str] = None, agent_kwargs: Optional[dict] = None, *, tags: Optional[Sequence[str]] = None, **kwargs: Any) → AgentExecutor [source] ¶ Load LangChain's products work seamlessly together to provide an integrated solution for every step of the application development journey. Tools are essentially functions that extend the agent’s capabilities by from langchain. agents import AgentType, initialize_agent from langchain. It provides a standard interface for chains, many integrations with other tools, and end-to-end chains for common applications. Contribute to langchain-ai/langchain-mcp-adapters development by creating an account on GitHub. 4k次，点赞10次，收藏3次。构建agent，这个方法是过时了吗？官方文档也没更新，官方示例也运行错误llm就按照这篇文章配置任意一个。有路过的大佬指点一二么？_langchain initialize agent May 14, 2024 · langchain. Jul 23, 2025 · LangChain is an open-source framework designed to simplify the creation of applications using large language models (LLMs). Class hierarchy: Jun 12, 2025 · Learn how to use MCP (Model Context Protocol) in LangChain to build modular, secure, and scalable LLM agents—complete setup guide AgentExecutor # class langchain. This will assume knowledge of LLMs and retrieval so if you haven't already explored those sections, it is recommended you do so. However, using print I would expect to see the output of the agent parsed and somehow manipulate it. 17 ¶ langchain. You can read the docs all day long, but the real magic — and the real headaches Mar 22, 2024 · Also, it's important to note that the initialize_agent function in LangChain version 0. We are going to use that LLMChain to create Jan 11, 2024 · LangChain v0. This covers basics like initializing an agent, creating tools, and adding memory. With built-in support for tool use, memory, and reasoning, LangChain makes it easy to build autonomous agents that perform multi-step tasks. 0 版本提供了一种新的初始化代理的方法。我们必须对每种类型使用明确定义的方法，而不是使用initialize_agent。还有一个称为 prompt 的附加参数。我们可以使用默认提示（您可以参考文档查看每个代理的提示）。 OpenAI 函数代理的默认提示示例： prompt = hub. LangChain Labs is a collection of agents and experimental AI products. For details, refer to the LangGraph documentation as well as guides for May 25, 2023 · Here is how you can do it. We'll start by installing the prerequisite libraries that we'll be using in this example. Code from langchain. 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. llms import GradientLLM agents # Agent is a class that uses an LLM to choose a sequence of actions to take. AgentOutputParser # class langchain. Below, create an example agent we will call to evaluate. base import BaseCallbackHandler from langchain_core. tools import Tool from langchain_openai import ChatOpenAI Jul 4, 2024 · Checked other resources I added a very descriptive title to this issue. Agents 🤖 Agents are like "tools" for LLMs. Dec 9, 2024 · langchain 0. Jul 24, 2024 · 文章浏览阅读1. Apr 23, 2025 · LangChain makes it easier to build smart, customizable AI agents — and I recently used it to build one myself. Apr 11, 2023 · I'm building my own agent with some custom tools. Agent that calls the language model and deciding the action. The main advantages of using the SQL Agent are: It can answer questions based on the databases' schema as well as on the databases' content (like describing a specific table). """ from typing import Any, Optional, Sequence from langchain_core. How can I initially prompt the agent with its main goal and task is? For example, you are a realtor connecting clients with agents etc. 2. Aug 21, 2023 · from langchain. 1に合わせつつ、エージェントの概念を langchain: 0. llms import OpenAI from langchain. Ensure that the LLM understands when and how to invoke these tools. 0 doesn't seem to directly accept an output_parser argument based on the source code. Whether you’re an indie developer experimenting with AI apps or a company needing offline capabilities, this setup is highly customizable and production-ready with the right tooling. 0: Use Use new agent constructor methods like create_react_agent, create_json_agent, create_structured_chat_agent, etc. initialize_agent ¶ langchain. Mar 28, 2023 · E. To achieve this, you can include the system message in the agent_kwargs when initializing the agent. ” 3. agents import AgentType, initialize_agent, load_tools from langchain. It offers free access to GPUs and a cloud-based Python notebook interface Dec 5, 2023 · 起始日期 | Start Date No response 实现PR | Implementation PR No response 相关Issues | Reference Issues No response 摘要 | Summary agent调用Qwen模型的代码示例 基本示例 | Basic Example agent_open_functions = initialize_age """Load agent. prompts import PromptTemplate, MessagesPlaceholder from langchain. 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. We will first create it WITHOUT memory, but we will then show how to add memory in. initialize. AgentExecutor [source] # Bases: Chain Agent that is using tools. As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization, chatbots, and code analysis. Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. Nov 9, 2023 · Regarding the initialize_agent function in the LangChain framework, it is used to load an agent executor given a set of tools and a language model. Parameters tools (Sequence[BaseTool]) – List of tools this agent has access to. Load an agent executor given tools and LLM. For details, refer to the LangGraph documentation as well as guides for Valid options are: `zero-shot-react-description` `react-docstore` `self-ask-with-search` `conversational-react-description` If None and agent_path is also None, will default to `zero-shot-react-description`. callbacks. Is there an alternative way to pass a custom output parser? System Info langchain==0. agents. In this comprehensive guide, we’ll Feb 16, 2025 · This article explores LangChain’s Tools and Agents, how they work, and how you can leverage them to build intelligent AI-powered applications. prompts import PromptTemplate llm = OpenAI(model_name='text-davinci-003', temperature = 0. _api import deprecated from langchain_core. For a quick start to working with agents, please check out this getting started guide. This agent uses a search tool to look up answers to the simpler questions in order to answer the original complex question. g. In this comprehensive guide, we’ll Jan 11, 2024 · LangChain v0. callback_manager: CallbackManager to use. I used the GitHub search to find a similar question and di In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. instead. from langch May 4, 2025 · Learn how to build agentic AI systems using LangChain, including agents, memory, tool integrations, and best practices to Mar 24, 2025 · langchain 已弃用 initialize_agent 函数后的替代方案 LangChain 的 initialize_agent 函数已被弃用。本文将介绍几种替代方法，帮助您在项目中继续使用 LangChain 的 Agent 功能。 LangChain 之前的 initialize_agent 函数用于初始化 Agent。由于其设计上的局限性，该函数已被弃用，开发者需要采用更灵活和强大的方法来构建 May 8, 2025 · LangChain is a powerful framework for building agentic AI systems powered by large language models (LLMs). Aug 26, 2024 · 文章浏览阅读2. Load the LLM First, let's load the language model we're going to Oct 4, 2023 · 🤖 Hello, Based on the information you provided and the context from the LangChain repository, it seems you want to instantiate an OpenAI Functions Agent with both memory and a custom system message. Here's how you can do it: May 8, 2025 · 本文通过示例介绍如何用 LangChain 构建具备联网搜索能力的 AI Agent，结合 DeepSeek 模型与 DuckDuckGo 实现中文问题自动回答。> 专栏系列第 2 篇 · 智能体纪元 在上一篇文章中我们介绍了 AI Agent 的基本概念和生态全景，这一篇我们将动手实战：用 LangChain 构建 Mar 26, 2024 · Based on your request, it seems you want to identify which retrieval tools were used and the context they provided to the language model when invoking an agent using the initialize_agent function from langchain. import os from langchain. Mar 25, 2024 · Previously I used initialize_agent method by passing agent=AgentType. The function takes several parameters including tools, llm, agent, callback_manager, agent_path, agent_kwargs, tags, and **kwargs. Instead of using initialize_agent, we have to use a clearly defined method for every type. It requires the agent class, the language model, and an optional list of tools as input. Intermediate agent actions and tool output messages will be passed in here. This is generally the most reliable way to create agents. 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. agents import AgentAction from langchain_openai import OpenAI # First, define custom callback handler implementations class MyCustomHandlerOne(BaseCallbackHandler): def on_llm_start( Capturing Trajectory The easiest way to return an agent's trajectory (without using tracing callbacks like those in LangSmith) for evaluation is to initialize the agent with return_intermediate_steps=True. For an in depth explanation, please check out this conceptual Jan 17, 2025 · Privileged issue I am a LangChain maintainer, or was asked directly by a LangChain maintainer to create an issue here. 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. In this article, we will explore agents, tools, and the difference between Jun 18, 2024 · Welcome to our latest article on Langchain agents! In this guide, we'll dive into the innovative approach to building agents introduced in Langchain update 0. fromAgentAndTools Dec 27, 2023 · If you don’t describe the tools well, the agent won’t know how to use them properly. LangChain 🔌 MCP. Google Colab is an ideal environment for prototyping LangChain agents. LangChain 是一个用于开发由语言模型驱动的应用程序的框架。 我们相信，最强大和不同的应用程序不仅将通过 API 调用语言模型，还将： 数据感知：将语言模型与其他数据源连接在一起。 主动性：允许语言模型与其环境进行交互。 因此，LangChain 框架的设计目标是为了实现这些类型的应用程序。 组件：LangChain 为处理语言模型所需的组件提供模块化的抽象。 LangChain 还为所有这些抽象提供了实现的集合。 这些组件旨在易于使用，无论您是否使用 LangChain 框架的其余部分。 用例特定链：链可以被看作是以特定方式组装这些组件，以便最好地完成特定用例。 这旨在成为一个更高级别的接口，使人们可以轻松地开始特定的用例。 这些链也旨在可定制化。 🦜🔗 Build context-aware reasoning applications. Conversational ReAct This agent is designed for use in conversational settings. agents import initialize_agent, load_tools from langchain. LangChain is an open source framework for building applications based on large language models (LLMs). Learn the essentials of LangSmith — our platform for LLM application development, whether you're building with LangChain or not. 1では別の書き方が推奨されます。 （もちろん'zero-shot-react-description'もなくなっています） エージェントやツールの概念は参考にできるのですが、書き方を0. LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. llm: Language model to use as the Sep 18, 2024 · Best Practices for Using Langchain Agents Tool Selection: Choose the right tools for your agent based on the task at hand. agents import initialize_agent, Tool May 3, 2023 · From what I understand, you opened this issue to seek guidance on customizing the prompt for the zero-shot agent created using the initialize_agent function. agent import AgentExecutor from langchain. 0 version provided a new approach of initializing agents. prompts import ChatPromptTemplate from langchain_core. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. I searched the LangChain documentation with the integrated search. agents # Agent is a class that uses an LLM to choose a sequence of actions to take. 0: Use new agent constructor methods like create_react_agent, create_json_agent, create_structured_chat_agent, etc. In Agents, a language model is used as a reasoning engine to determine which actions to take and in which order. Before going through this notebook, please walkthrough the following notebooks, as this will build on top of both of them: Memory in LLMChain Custom Agents In order to add a memory to an agent we are going to perform the following steps: We are going to create an LLMChain with memory. LangChain implements a standard interface for large language models and related technologies, such as embedding models and vector stores, and integrates with hundreds of providers. agents import initialize_agent # Imports the initialize_agent function agent = initialize_agent(tool_list, # Provides the list of tools Jun 2, 2024 · The `initialize_agent` function is a convenience function provided by LangChain to simplify agent creation. This walkthrough showcases the self-ask with search agent. For an in depth explanation, please check out this conceptual 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. 0. 0 Custom agent This notebook goes through how to create your own custom agent. agents import load_tools from langchain. memory import ConversationBufferMemory from langchain. You are having conversations with customers. The agent prompt must have an agent_scratchpad key that is a MessagesPlaceholder. Memory is needed to enable conversation. It incorporates the React framework to determine which tool to use and utilizes memory to remember previous conversation interactions. llm (BaseLanguageModel) – Language model to use as the agent. We recommend that you use LangGraph for building agents. Setup: LangSmith By definition, agents take a self-determined, input-dependent Oct 29, 2024 · Build dynamic conversational agents with custom tools to enhance user interactions, delivering personalized, context-driven responses. memory import ConversationBufferMemory from langchain_community. Here’s how you can too. chains import LLMChain from langchain. In Chains, a sequence of actions is hardcoded. running from langchain. pydantic_v1 import BaseModel, Field from langchain_core. llms import ChatOpenAI template = """You are a customer service representative working for Amazon. chains import LLMMathChain from langchain_core. What Are LangChain Tools? [docs] def initialize_agent( tools: Sequence[BaseTool], llm: BaseLLM, agent: Optional[str] = None, callback_manager: Optional[BaseCallbackManager] = None, agent_path: Optional[str] = None, agent_kwargs: Optional[dict] = None, **kwargs: Any, ) -> AgentExecutor: """Load an agent executor given tools and LLM. They allow a LLM to access Google search, perform complex calculations with Python, and even make SQL queries. agents import initialize_agent, AgentType from langchain. It takes the agent class, the language model, and an optional list of tools as input. AgentOutputParser [source] # Bases: BaseOutputParser[Union[AgentAction, AgentFinish]] Base class for parsing agent output into agent action/finish. agents import AgentExecutor, AgentType, initialize_agent, load_tools from langchain. In this notebook we'll explore agents and how to use them in LangChain. agent_types 03プロンプトエンジニアの必須スキル5選04プロンプトデザイン入門【質問テクニック10選】05LangChainの概要と使い方06LangChainのインストール方法【Python】07LangChainのインストール方法【JavaScript・TypeScript】08LCEL（LangChain Expression Language）の概要と使い方09LangSmithの import os from langchain. Issue Content Currently there's a bunch of tools and other integrations that use initialize_agent in their docs page ( Agents LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. When you use all LangChain products, you'll build better, get to production quicker, and grow visibility -- all with less set up and friction. 1. note Jun 4, 2025 · Using a Langchain agent with a local LLM offers a compelling way to build autonomous, private, and cost-effective AI workflows. 7, openai_api 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. Understand how LangChain agents enhance LLM applications by dynamically integrating external tools, APIs, and real-time data access. . Initializing the Agent We'll use an OpenAI chat model and an "openai-tools" agent, which will use OpenAI's function-calling API to drive the agent's tool selection and invocations. Nov 30, 2023 · The initialize_agent function is a convenience function provided by LangChain that simplifies creating an agent. runnables import Config… Apr 28, 2025 · When I first started working with LangChain Agents, I realized pretty quickly: theory will only take you so far. Deprecated since version 0. Interested in discussing a Data or AI project? Feel free to reach 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. langchain. Agents select and use Tools and Toolkits for actions. Nov 9, 2023 · How to correctly load a local model LLM and use it in the initialize_agent function of the langchain library? I have a LLM google/flan-t5-large (downloaded from HuggingFaces) stored in my computer langchain. Args: tools: List of tools this agent has access to. Deprecated since version 0. LLMs are large deep-learning models pre-trained on large amounts of data that can generate responses to user queries—for example, answering questions or creating images from text-based prompts. agents ¶ Agent is a class that uses an LLM to choose a sequence of actions to take. Mar 22, 2024 · Output parser of langchain React AgentDescription I am initializing a langchain agent as seen in the code. agent. initialize_agent(tools: Sequence[BaseTool], llm: BaseLanguageModel, agent: Optional[AgentType] = None, callback_manager: Optional[BaseCallbackManager] = None, agent_path: Optional[str] = None, agent_kwargs: Optional[dict] = None, *, tags: Optional[Sequence[str]] = None, **kwargs: Any) → AgentExecutor [source] ¶ Load 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. Contribute to langchain-ai/langchain development by creating an account on GitHub. Continuously improve your application with LangSmith's tools for LLM observability, evaluation, and prompt engineering. 用create_tool_calling_agent报错构建agent，这个方法是过时了吗？官方文档也没更新，官方示例也运行错误 from langchain_core. It can recover from errors by running a generated query, catching the traceback and regenerating it Aug 22, 2023 · 2. 0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. agents import initialize_agent from langchain. memory import ConversationBufferMemory llm = OpenAI(openai_api_key Documentation for LangChain. As we can see, the agent will first choose which tables are relevant and then add the schema for those tables and a few sample rows to the prompt. 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. Mar 20, 2024 · ただ、上記のサイトで紹介されている"initialize_agent"を実行すると非推奨と出るように、Langchain0. Dec 9, 2024 · Deprecated since version 0. Aug 25, 2024 · In LangChain, an “Agent” is an AI entity that interacts with various “Tools” to perform tasks or answer queries. Agent # class langchain. Concepts There are several key concepts to understand when building agents: Agents, AgentExecutor, Tools, Toolkits. language_models import BaseLanguageModel from langchain_core. Change the content in PREFIX, SUFFIX, and FORMAT_INSTRUCTION according to your need after tying and testing few times. There were multiple solutions provided by the community, including using sys_message to change the prompt and using agent_kwargs to set a custom prompt via initialize_agent(). Dec 9, 2024 · An agent that breaks down a complex question into a series of simpler questions. This is driven by a LLMChain. 有路过的大佬指点一二么？ 2. In this example, we will use OpenAI Tool Calling to create this agent. zxhlftj cczvdzy ezypx roomzk aochdxml yjxiqt ztltw gmyxvj psumy wncc