Langchain react agent prompt. Includes an LLM, tools, and prompt.
- Langchain react agent prompt. Change the content in PREFIX, SUFFIX, and FORMAT_INSTRUCTION according to your need after tying and testing few times. AgentExecutor for create_react_agent, even though langchain. Sep 16, 2023 · At its core, ReAct Prompting is a groundbreaking approach that leverages LLMs to generate both reasoning traces and task-specific actions in a dynamic and interleaved manner. The goal is to enable the agent to process user queries, interact with an SQL database, and return coherent, context-aware How to add a custom system prompt to the prebuilt ReAct agent This tutorial will show how to add a custom system prompt to the prebuilt ReAct agent. Install dependencies If you haven't already, install LangGraph and LangChain: Feb 18, 2025 · To review and edit a tool message in the create_react_agent function, you can customize the prompt or use the tools_renderer parameter to modify how tool messages are presented to the language model. Prompt Templates output Langchain v0. ReAct agents extend the capabilities of LLMs to respond to queries by mimicking human reactions to problems using external tools. prompts import PromptTemplate from langchain_community. . We will be using OpenAI for the LLM and LangChain as it already has built-in functionality that leverages the ReAct framework to build agents that perform tasks by combining the power of LLMs and different tools. hope this helps! A ReAct prompt might include examples of actions, the observations resulting from those actions, and the transcribed thoughts of a human during the process. Sep 11, 2024 · from langchain import hub from langchain. 3 React Agent Error: Missing Required Prompt Variables The post content has been automatically edited by the Moderator Agent for consistency and clarity. as_retriever() Step 2: Augment Next, to augment the prompt with the additional context, you need to prepare a prompt template. With the LangChain ReAct agents, you can enable Nov 20, 2024 · this actually allows passing more state variables into your prompt as well, for example if you have some state keys like user_info etc, you can pass that information to the prompt as well. 0. The ReAct agent is a great prototypical design for this, as it prompts the language model using a repeated thought, act, observation loop: Thought: I should call Search() to see the current score of the game. I want to initialize an CONVERSATIONAL_REACT_DESCRIPTION agent. Jul 18, 2024 · Why no use of langchain. 03629) May 16, 2025 · System prompts are a critical component in the ReAct Agent architecture that define the agent's behavior, context understanding, and response patterns. from langch Prompt Template比較 LangSmithのPrompt Templateの比較です。 openai-functions-template シンプルなPromptです。 Toolsの情報はPromptと別に渡します。 {instruction} は、 Using OpenAI Functions Agent の例だと以下を使用。 You are an agent designed to write and execute python code to answer questions. Use of Prompt Hub is subject to our Terms of Service. agents import AgentExecutor from langchain. Jun 26, 2024 · In this post, we’ve created a responsive AI agent using Langchain and OpenAI. prompts import PromptTemplate search_tool = DuckDuckGoSearchRun () tools = [search_tool] react_openai_tools = """ Answer the following questions as best you can. LangChain helps you compose ReAct framework. tools. Below we assemble a minimal SQL agent. 3 自定义提示模板（Prompt） 你可以完全控制 Agent 的提示词，以指导其行为风格、语言偏好、思考策略。 示例：定制 Agent 提示模板 from langchain. Answer the following questions as best you can. base import BaseTool # Define your tools tools = [BaseTool (name="tool1", description="description1"), BaseTool (name="tool2", description Jan 30, 2024 · It seems like the issue you're encountering is related to the way the create_react_agent function in the LangChain framework handles the ReAct prompting style. Based on paper “ReAct: Synergizing Reasoning and Acting in Language Models” (https://arxiv. The thing is there is a lot of wasted effort because the agent want to call tools which are not even present. base. This guide shows how to implement ReAct agent from scratch using LangGraph. [Github] The Jupiter Notebook of this implementation Common Tools of LangChain Prompt Templates Cyclic graphs (LangGraphs 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. react. from_template(""" 你是一个高效的个人助手。请 Nov 22, 2024 · Learning Objectives We will understand ReAct prompting and its role in building more capable AI agents that can reason, act, and think through complex tasks. 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). tools import DuckDuckGoSearchRun from langchain_openai import ChatOpenAI from langchain. org/abs/2210. name: tool for tool in tools} # this is similar to customizing the create_react_agent with 'prompt' parameter, but is more flexible # system_prompt = SystemMessage( # "You are a helpful assistant Agents LangChain has a SQL Agent which provides a more flexible way of interacting with SQL Databases than a chain. # Initialize a ChatOpenAI model Apr 12, 2025 · Introduction In this blog post, we delve deeper into the integration of AI Agents using LangGraph tools, building upon the foundation established in Simple ReAct Agent from Scratch. memory import ConversationBufferMemory, ReadOnlySharedMemory from langchain. Apr 25, 2024 · The ReAct agent repeatedly calls tools and receives results until a query is resolved. In this style, the agent's action is followed by an observation of the result of the action. Mar 25, 2024 · Hey @PasinduUd, great to see you back here! 🛸 To initialize a CONVERSATIONAL_REACT_DESCRIPTION agent using the create_react_agent method in LangChain, you can follow these steps: Import the necessary modules and classes from langchain and other libraries as shown in the example. agents import initialize_agent from langchain. ReActDocstoreAgent [source] # Bases: Agent Deprecated since version 0. Imagine it as a conductor orchestrating a symphony of information and tasks. 5-sonnet, gpt-4o, o1, and o3-mini across two domains of tasks. These applications use LangChain components such as prompts, LLMs, chains and agents as building blocks to create unique workflows. This page explains how system prompts are defined, configured, and used within the ReAct Agent Tool Server. from langchain. We explore new tools and techniques that enable more sophisticated AI agent implementations. Disclaimer: Prompts are user-generated and unverified. Documentation for LangChain. LlamaIndex，在 ReAct 模式、Tool use / function call 上的異同與特性又是什麼？這是一系列的比較，讓你更了解該選擇 LangChain 還是 LlamaIndex Feb 15, 2024 · Useful when answering complex queries on internal documents in a step-by-step manner with ReAct and Open AI Tools agents. 1に合わせつつ、エージェントの概念を Feb 2, 2024 · 概要 前回のLangChainを用いてReActフレームワークの理解からバージョンの更新が進み、 LangChain Expression Languageという記法が導入されました。 記法の導入に伴い前回（v0. The agents use a zero shot react prompt as I would like the agents to show their thought process while trying to answer the user's question. 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. Dec 9, 2024 · The prompt must have input keys: tools: contains descriptions and arguments for each tool. agents import AgentExecutor, create_react_agent from LangChain Hub Explore and contribute prompts to the community hub Feb 13, 2024 · from langchain_community. The agent is integrated with a set of tools, such as an SQL tool, and utilizes a memory buffer to maintain conversation history across sessions. agents. utils import validate_tools_single_input from langchain. 7, openai_api LangGraph quickstart This guide shows you how to set up and use LangGraph's prebuilt, reusable components, which are designed to help you construct agentic systems quickly and reliably. create_openai_tools_agent? Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. We wanted to make it easy to share and discover these workflows by creating a hub where users can share the components they’ve created. In those cases, you can create a custom ReAct agent. Aug 25, 2024 · Pull Prompt Template: This pulls a prompt template named “react” from the LangChain hub, which is designed to help the agent reason and take actions. In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. Includes an LLM, tools, and prompt. py. Further implement ReAct Agents within the LlamaIndex framework, which provides the Agent with feedback capabilities. Due to this the agent reaches max iteration without calling the tool which are present. Based on paper "ReAct: Synergizing Reasoning and Acting in Language Nov 29, 2024 · Implementation 1: Using Langchain Langchain OpenAI Tavily Search import os from langchain. LangChain does not review or endorse public prompts, use these at your own risk. Aug 29, 2024 · LangChain ReAct Framework is a prompting technique that combines reasoning and action elements in large language models (LLMs). import os from langchain. Prerequisites Before you start this tutorial, ensure you have the following: An Anthropic API key 1. This project showcases the creation of a ReAct (Reasoning and Acting) agent using the LangChain library. utilities import GoogleSearchAPIWrapper from This notebook goes through how to create your own custom agent. An Agent can use one or multiple specific "tools". The prompt must have input keys: tools: contains descriptions and arguments for each tool. For details, refer to the LangGraph documentation as well as guides for Apr 21, 2024 · agent = create_react_agent(model, tools, prompt) The ReAct agent within LangChain is a component that embodies the “Reasoning, Acting, and Learning” framework. Jan 24, 2025 · It's the code from the documentation, which clearly states that create_react_agent has a response_format option, but it returns an error of: TypeError: create_react_agent() got an unexpected keyword argument 'response_format' Nov 22, 2024 · React agents represent an exciting frontier in AI development, offering developers the ability to create sophisticated, interactive agents… May 25, 2023 · Here is how you can do it. This can be used to guide a model's response, helping it understand the context and generate relevant and coherent language-based output. Mar 25, 2024 · But in LangChain v1. 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 16 LangChain Model I/Oとは？ 【Prompts・Language Models・Output Parsers】 17 LangChain Retrievalとは？ 【Document Loaders・Vector Stores・Indexing etc. Jun 14, 2024 · ReAct 本次演示展示了如何使用一个agent来实现 ReAct 的逻辑。 [docs] def create_react_agent( llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: BasePromptTemplate, output_parser: Optional[AgentOutputParser] = None, tools_renderer: ToolsRenderer = render_text_description, *, stop_sequence: Union[bool, List[str]] = True, ) -> Runnable: """Create an agent that uses ReAct prompting. AgentExecutor is used for other agents, such as langchain. Sep 7, 2023 · The langchain framework makes it easy to use LLMs as agents capable of making decisions. from langchain import hub from langchain. To create this agent2-supervisor architecture I use the supervisor as a router that decides which agent should go next when handling the user's question. By prompting the LLM to alternate between thinking and acting, ReAct transforms it into an active agent in its environment, capable of solving tasks in a human-aligned manner. Sep 17, 2023 · from libs. Please see this tutorial for how to get started with the prebuilt ReAct agent You can add a custom system prompt by passing a string to the stateModifier param. This walkthrough showcases using an agent to implement the ReAct logic. It provides structured output, binds multiple tools, and allows the model to choose which tool to call. The Jun 2, 2024 · LangChain vs. 前言 这是对langchain源码剖析的系列文章，也有对应的本站 视频 和 b站视频，建议读者可以结合视频和文章一起看。 agent中的prompt介绍 agent模块中整个过程没有显示的给出prompt，但是仔细分析agent的源码，发现也是有prompt词的，并且设计也是比较巧妙，下面分享一下agent模块中的prompt。 prompt介绍 agent For more examples on using prompts in code, see Managing prompts programatically. 】 18 LangChain Chainsとは？ 【Simple・Sequential・Custom】 19 LangChain Memoryとは？ 【Chat Message History・Conversation Buffer Memory】 20 LangChain Agentsとは？ Mar 31, 2025 · import json from langchain_core. We’ve set up the environment, pulled a React prompt, initialized the language model, and added the capability Customize the prompt: We provide a default system prompt in prompts. Create an agent that uses ReAct prompting. langchain. agents import create_react_agent from langchain. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. runnables import RunnableConfig tools_by_name = {tool. Dec 9, 2024 · [docs] def create_react_agent( llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: BasePromptTemplate, output_parser: Optional[AgentOutputParser] = None, tools_renderer: ToolsRenderer = render_text_description, *, stop_sequence: Union[bool, List[str]] = True, ) -> Runnable: """Create an agent that uses ReAct prompting. jsParams required to create the agent. Is there any better way to build these agents? or is there any research on better type of agents for this? LangSmith provides tools for executing and managing LangChain applications remotely. tools=tools, . You have access to the following tools: {tools} Use the following format: Question: the input question you must answer Thought: you should always think about what to do Action: the action to take, should be one of [{tool_names}] Action Input: the input to the action Observation: the result of the action (this Thought/Action/Action Input Jun 27, 2024 · Create a Comprehensive Prompt: Use the create_prompt method to construct a detailed prompt that includes system messages, human messages, and placeholders for chat history and agent scratchpad. Based on paper "ReAct: Synergizing Reasoning and Acting in Language Feb 28, 2025 · Adding Thread-Level Memory Adding a Custom System Prompt Returning Structured Output Adding Semantic Search to Your Agent’s Memory Running a Graph Asynchronously Forcing a Tool-Calling Agent to Structure Output The key packages used throughout include: langgraph langchain-openai langchain-anthropic langchain-core langchain pydantic Using the prebuilt ReAct agent create_react_agent is a great way to get started, but sometimes you might want more control and customization. Prompt Templates take as input a dictionary, where each key represents a variable in the prompt template to fill in. base import ConversationalChatAgent from libs. Here’s an example: Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. agents import load_tools from langchain. Using LangGraph's pre-built ReAct agent constructor, we can do this in one line. !pip install langchain !pip install Apr 15, 2025 · 6. # Create an agent executor by passing in the agent and tools . pull("hwchase17/react") agent = create_react_agent(llm, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) 使用Agent Dec 5, 2023 · Master LangChain Agents and React Framework with our ultimate guide! Transform your AI skills, unleash intelligent automation. Define or pull a prompt that matches the requirements for a ReAct agent. You can also quickly extend this template by: Modifying the agent's reasoning process in graph. You have access to a python REPL, which you can use to execute This guide will walk you through how we stream agent data to the client using React Server Components inside this directory. prompts import ChatPromptTemplate template = """You are an assistant for question-answering tasks. 0, it says that it will be deprecated and to use the create_react_agent method. Start learning now! Documentation for LangChain. This internal monologue will be a collection of all observations, thoughts, and actions (read this post, as it ReActDocstoreAgent # class langchain. Based on paper "ReAct: Synergizing Reasoning and Acting in Language Jan 31, 2024 · In this blog, we will delve into the implementation of the ReAct framework within Langchain and provide a detailed, step-by-step guide on the functioning of a simple agent. agents import AgentExecutor, create_openai_tools_agent from langchain. tool_names: contains all tool names. agents import AgentExecutor, Tool, ZeroShotAgent, create_react_agent from langchain. agent_scratchpad: contains previous agent actions and tool outputs as a string. agents import AgentExecutor # 这里获取一个内置prompt，为了方便 prompt = hub. The prompt can be easily customized from a prompt template, as shown below. 写在前面本文翻译自 LangChain 的官方文档 “Build an Agent”， 基于： LangGraph 封装好的 ReAct agent：from langgraph. Depending on what the user input (prompt) is, the agent may or may not call any of these tools, or even multiple tools in a row, until it can reason its way to the answer. llms import OpenAI from langchain. You have access to the following tools: {tools} Use the following format: Question: the input question you must answer Thought: you should always think about what to do Action: the action to take, should be one of [ {tool_names}] Action Input: the input to the action Observation: the Feb 14, 2024 · Description I am trying to create a 2-agents team with a supervisor using the code attached. prompts import PromptTemplate llm = OpenAI(model_name='text-davinci-003', temperature = 0. prebuilt import create_react_agent封装好的 Memory Savor本人加入一些补充说明什么是 A… Nov 9, 2023 · I tried to create a custom prompt template for a langchain agent. 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. LangGraph 快速入门 本指南将向您展示如何设置和使用 LangGraph 的 预构建 、 可复用 组件，这些组件旨在帮助您快速可靠地构建代理系统。 先决条件 在开始本教程之前，请确保您具备以下条件： 一个 Anthropic API 密钥 1. prompts import PromptTemplate template = PromptTemplate. NOTE: if you need to add extra state keys to create_react_agent, you'd need to also pass state_schema parameter. 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. Prompt Templates Prompt templates help to translate user input and parameters into instructions for a language model. Unfortunately, the LangChain docs are so high-level that they are almost useless. Here’s an example: [docs] def create_react_agent( llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: BasePromptTemplate, output_parser: Optional[AgentOutputParser] = None, tools_renderer: ToolsRenderer = render_text_description, *, stop_sequence: Union[bool, list[str]] = True, ) -> Runnable: """Create an agent that uses ReAct prompting. 使用预置的 ReAct 代理 create_react_agent 是一个很好的入门方式，但有时您可能需要更多的控制和定制。 在这种情况下，您可以创建自定义的 ReAct 代理。 本指南展示了如何使用 LangGraph 从头开始实现 ReAct 代理。 设置 首先，让我们安装所需的软件包并设置我们的 API This walkthrough showcases using an agent to implement the ReAct logic. The prompt must include input keys for Mar 7, 2023 · ReAct (Reasoning + Acting) is a flexible LLM chain framework and essential for today's advanced LLM reasoning. prompts import PromptTemplate template = '''Answer the following questions as best you can. Feb 13, 2024 · Observe: react to the response of the tool call by either calling another function or responding to the user. Feb 10, 2025 · We explore how increasing the number of instructions and tools available to a single ReAct agent affects its performance, benchmarking models like claude-3. In the agent execution the tutorial use the tools name to tell the agent what tools it must us Taking inspiration from Hugging Face Hub, LangChainHub is collection of all artifacts useful for working with LangChain primitives such as prompts, chains and agents. May 22, 2024 · This tutorial explores how three powerful technologies — LangChain’s ReAct Agents, the Qdrant Vector Database, and Llama3 Language Model. 198）からLangChainの中身が大きく変わっていましたので、中身について改めて確認したものとなります。 Agentを改造する際にどの Oct 14, 2024 · To pass values to the variables {question} and {ai_response} in the create_react_agent langgraph, you need to provide the question, user_id, and session_id as part of the input to the chain. Dec 19, 2024 · Hi, I open a discussion following this ticket #2835 Issue with current documentation: In the nodes and edge definition from How to create a ReAct agent from scratch, we declare a system_prompt vari I am using langchain ReAct agent with tools. messages import ToolMessage, SystemMessage from langchain_core. prompt=template. max_iterations=3, handle_parsing_errors=True, verbose=True . This helps in maintaining the context and avoiding repeated action cycles. You can easily update this via configuration in the studio. I am trying to understand how ReAct agents are implemented on a high level to understand the concepts behind this approach. Aug 27, 2023 · The initial prompt is fed into an “internal monologue” for the LLM-based agent. chains import LLMChain from langchain. This architecture will use tool calling to select the correct tools to call, and loop until done. An example prompt on how ReAct prompt is written. Nov 14, 2023 · retriever = vectorstore. Sep 19, 2024 · ReAct Agent The ReAct agent architecture is the most generic agent architecture out there. Feb 27, 2025 · I am trying to build a simple react agent using langchain which uses a tool to get the weather condition of a location I tried making my custom react prompt template and used 'create_react_agent' a They can answer questions based on the databases' schema as well as on the databases' content (like describing a specific table). The ReAct agent: Takes a user query as input Reasons about the query and decides on an action Executes the chosen action using available tools Observes the result of the action Repeats steps 2-4 until it can provide a final answer By default, it's set up with a basic set of tools, but can be easily extended with custom tools to suit various use cases. It enables LLMs to reason and act according to the situation in a simulation environment. The structured chat agent is capable of using multi-input tools. conversational_chat. For more examples on using prompts in code, see Managing prompts programatically. agents. Jun 12, 2024 · Defining tools Model, Prompt and Tools are the main components of creating an Agent. 1. Data Enrichment Agent This is a slightly more specific agent that is aimed at conducting research to fill out a specific form. It can recover from errors by running a generated query, catching the traceback and regenerating it Deprecated since version 0. Apr 12, 2025 · Langchain hub is one of the centralized to store templatized prompt Here is an example of a ReAct prompt that we used in part 1: React System Prompt As you can see, we can pass tools, tool names and input as parameters The main advantage of using prompts from the centralized data store is that we can adapt the prompt on the fly without having to make a new software deployment just to update This project is designed to create and configure a ReAct (Reasoning and Acting) agent using LangChain and OpenAI's GPT-4o model. We will equip it with a set of tools using LangChain's SQLDatabaseToolkit. LangChainのAgentをカスタムできると自由度が上がりますが、LangChainのAgentがいまいちブラックボックスだった感があったので、デフォルトのプロンプトを解剖してみました。最近のLangChainだとChatGPT対応されており、これをカスタムすることで安価にAPIが使えそうです。 Documentation for LangChain. 安装依赖 如果您尚未安装，请安装 LangGraph 和 LangChain Apr 11, 2023 · I'm building my own agent with some custom tools. This post will give you the answer for the questions: "What is ReAct?", "How ReAct works?", and "How to build ReAct?". prompts import PromptTemplate from langchain. 0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. The goal of this repository is to be a central resource for sharing and discovering high quality prompts, chains and agents that combine together to form complex LLM applications. Jan 6, 2024 · LangChain also has another concept called Agent, that we can use to interpret the input from the user and determine which tool or tools to use to complete the task. Here, we will be creating few tools which will be binded to the agent. May 3, 2023 · 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(). Adjusting the ReAct loop or adding additional steps to the agent's decision-making process. I followed this langchain tutorial . 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. This project uses a ReAct type of agent, which uses the ReAct framework or model for prompting. This walkthrough showcases the self-ask with search agent. Furthermore, these agents can be equipped with a variety of tools which implement different functionalities Nov 10, 2024 · from langchain_core. wvrphn vsizonxp aqghte wmawvdy koafpl srji ecf nkxfpm qeib jej