tools import tool from langchain. 4，2. Let's see how this works in practice with a real-world example. Model Context Protocol (MCP) is an open protocol that standardizes how applications provide tools and context to LLMs. To add a tool to your prompt, click the + Tool button at the bottom of the prompt editor. Flowise is an open source no-code UI visual tool to build 🦜🔗LangChain applications - YouTube 5 days ago · 今晚20:30，想看真实效果的，晚上准点来，下方预约，开播有提醒哦！！！目前版本是1. 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. agents instead, which is the new standard for building tool-calling agents in LangChain v1. Under the hood, tools are callable functions with well-defined inputs and outputs that get passed to a chat model. 5 days ago · Skills take a lighter approach—progressive disclosure for agent capabilities. agents in recent version. I added a very descriptive Jan 13, 2026 · LangChain has moved its LangSmith Agent Builder from public beta to general availability, roughly six weeks after launching the no-code AI agent platform in early December 2025. This emits an event after every agent step. LangChain agents can use tools defined on MCP servers using the langchain-mcp-adapters library. Tools extend what agents can do—letting them fetch real-time data, execute code, query external databases, and take actions in the world. Apr 11, 2024 · LangChain is a popular framework for creating LLM-powered apps. Functions can have any signature - the tool will automatically infer input schemas unless disabled. for example: from langchain. Convert Python functions and Runnables to LangChain tools. That is exactly where LangChain fits. LangChain is the platform for agent engineering. It involves linking multiple prompts in a logical sequence, where the output of one prompt serves as the input for the next. You’ll only see the tools that are compatible with the provider and model you’ve chosen. LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. AI Agents and Applications is your hands-on guide to developing cutting-edge language model solutions for real business needs. This project creates an intelligent chatbot that can interact with Workato's MCP server to query customer data, retrieve 4 days ago · You have to manage prompts, memory, tools, retrieval, structured outputs, retries, streaming, observability, and cost or latency controls. Aug 22, 2025 · LangChain prompt templates are a tool that allows developers to create reusable, dynamic prompts for language models. It runs on LangGraph under the hood and supports the ReAct loop for tool calling. 2+ and is not available in langchain. This book will help you earn your seat at the table. 4 days ago · LangChain is the easiest way to start building agents and applications powered by LLMs. After years of rapid iteration and community feedback, these frameworks have evolved from experimental tools into production-ready platforms powering mission-critical AI applications at companies like Uber, LinkedIn, Klarna, and JP Morgan. com/). The tool system provides the assistant with concrete capabilities to interact with emails, calen 22 hours ago · Easy chaining of prompts, tools, retrievers Strong community momentum Where it struggles: Hidden control flow Debugging is painful at scale Abstractions leak under complex logic Performance tuning is hard When to use LangChain MVPs Hackathons POCs Teams new to LLMs When to avoid Complex, stateful workflows Systems needing precise control or 1 day ago · Today, both LangChain and LangGraph rely on ad‑hoc PyTest patterns, manual mocks, and custom assertions. Compare features, prices, and use cases to find the best alternative to LangChain for your needs. For questions, please use the LangChain Forum (https://forum. . graph import StateGraph, START, END from langgraph. Jan 9, 2026 · Learn about the best LangChain alternatives in 2026. But when I run the code I got the following error. Quickly get started building agents, with any model provider of your choice. runnables import RunnableConfig # Create config with callbacks config = RunnableConfig(callbacks=[handler]) # Use with LCEL chains from langchain_core. Jan 13, 2026 · Checked other resources This is a bug, not a usage question. " Works well for coding agents where context accumulates but capabilities stay fluid. Contribute to patterns-ai-core/langchainrb development by creating an account on GitHub. tools import tool, ToolRuntime from langgraph. They support continuous improvement, pre-deployment testing, structured experiments, flexible evaluation, and seamless integration with frameworks like LangChain and LlamaIndex. Your community starts here. 22 hours ago · from typing import Literal from langchain. Deep Agents is an agent harness built on langchain and langgraph. Build LLM-powered applications in Ruby. could you help me to 3 days ago · What began as simple prompt–response interactions has grown into multi-step workflows involving retrieval systems, tool usage, autonomous agents, and long-running processes. Define state with active LlamaIndex brings together VLM-powered and an enterprise‑grade framework for building, serving, and deploying agents. In particular, you’ll be able to create LLM agents that use custom tools to answer user queries. May 2, 2023 · This notebook takes you through how to use LangChain to augment an OpenAI model with access to external tools. What is Langchain? LangChain is a framework for developing applications powered by language models. What are we building? Elastic’s AI security assistant, built with LangSmith and LangGraph, cut alert response times for 20,000+ customers. LangChain provides the engineering platform and open source frameworks developers use to build, test, and deploy reliable AI agents. Its modular design allowed the team to integrate multiple model providers and build on a standard interface instead of rolling out their own. For example, if you have an agent that calls a tool once, you should see the following updates: LLM node: AIMessage with tool call requests Tool node: ToolMessage with execution result LLM node: Final AI response A practical guide to structured outputs in LangChain v1 If your prompts still include “Please return your answer as JSON”, it’s time to stop. Can be used as a decorator with or without arguments to create tools from functions. Jan 13, 2026 · This document details the tool system architecture used throughout the email assistant implementations. prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI prompt = ChatPromptTemplate. It helps you chain together interoperable components and third-party integrations to simplify AI application development – all while future-proofing decisions as the underlying technology evolves. It provides standardized interfaces for models, embeddings, vector stores, tools, and memory. 22 hours ago · Subagent middleware - adds the task tool, allowing the main agent to delegate work to subagents with isolated context and their own prompts/tools. With under 10 lines of code, you can connect to OpenAI, Anthropic, Google, and more. tl;dr LangChain v1 refines and standardizes with_structured_output so it works consistently across providers that support it and falls back to tool calling elsewhere. After… In AI terms, LangChain lets you connect prompts, models, and tools in a straight line — ideal for quick chatbots, RAG (retrieval-augmented generation), and simple workflows. 4 days ago · A Chain in LangChain is a sequence (or pipeline) of components — like LLMs, prompts, retrievers, and tools — that work together to complete a task. In the tool section, select the built-in tool you want to use. By replacing static prompts with templates that use placeholders, developers can generate more consistent and efficient outputs. See the docs for conceptual guides, tutorials, and examples on using Tools. May 29, 2024 · Tool calling agents in langchian can be defined with the function: It takes as input a LLM and the tools you defined combined with a prompt template, there’s an example in the langchain Jun 29, 2025 · Every core component in LangChain – from your prompts to your LLMs and output parsers – implements the Runnable protocol, making them perfectly compatible with this chaining mechanism. It was built with these and other factors in mind, and provides a wide range of integrations with closed-source model providers (like OpenAI, Anthropic, and Google), open source models, and other third-party components like vectorstores. Instead of calling a model directly, you can Powerful tools including open source LLMs, the Langchain tools ecosystem, and standardized protocols like MCP are driving this new gold rush. You can use create_agent from langchain. Share solutions, influence AWS product development, and access useful content that accelerates your growth. 0 and LangGraph 1. Jan 13, 2026 · create_tool_calling_agent was removed in LangChain v0. agents import AgentState, create_agent from langchain. " A conversational AI chatbot that integrates Workato's Model Context Protocol (MCP) server with LangChain, enabling natural language interactions with Workato data and tools. messages import HumanMessage from langchain_google_genai import ChatGoogleGenerativeAI # Define the tool @tool(description="Get the current weather in a given location") def get_weather(location: str) -> str: return "It's sunny. 0正式开源。记得收藏哦目录1 The LangChain ecosystem has reached a pivotal milestone in 2025 with both LangChain 1. Deep Agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped 22 hours ago · Subagent middleware - adds the task tool, allowing the main agent to delegate work to subagents with isolated context and their own prompts/tools. LangChain controversially calls this a "quasi-multi-agent architecture. 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. 1 day ago · Why LangChain and LangGraph Remote chose LangChain because its ecosystem offers mature abstractions for prompt handling and tool invocation. There is no unified, first‑class testing framework that supports deterministic LLM mocking, chain/graph assertions, snapshot testing, or workflow‑level validation. The LangChain ecosystem has reached a pivotal milestone in 2025 with both LangChain 1. LangChain is an open source orchestration framework for application development using large language models (LLMs). 22 hours ago · I’m trying AI Agent in LangChain and build a very basic agent with HuggingFace free model. Prompt chaining is a foundational concept in building advanced workflows using large language models (LLMs). The agent loads specialized prompts and knowledge on-demand rather than managing multiple agent instances. LLM Playground is a tool for testing and iterating on your prompts and model configurations, shortening the feedback loop and accelerating development. from_template("Tell me about {topic}") model = ChatOpenAI() chain = prompt | model # Invoke with config result = chain Jan 6, 2026 · AI Framework Integration LangChain Integration LangChain provides MCP tool integration through the langchain-mcp package: Framework: rectalogic/langchain-mcp (Python) This integration enables: Automatic conversion of MCP tools to LangChain tools Use of MCP servers within LangChain agents Seamless integration with LangChain's agent frameworks To stream agent progress, use the stream or astream methods with stream_mode="updates". langchain. This is what makes Deep Agents feel “pre-wired” without introducing a new runtime. Jul 6, 2025 · LangChain is a modular, open-source Python framework to simplify the building of advanced LLM applications. LangChain is a framework for building agents and LLM-powered applications. It provides a standard interface for integrating with other tools and end-to-end chains for common applications. 1 day ago · Integrating Oracle Cloud Infrastructure (OCI) Generative AI with LangChain unlocks powerful Tagged with langchain, ocigenai, oracledatabase23ai, rag. The tool lets users create autonomous AI agents through natural language prompts rather than traditional programming. 0 achieving stable releases. AI teams at Replit, Clay, Rippling, Cloudflare, Workday, and more trust LangChain’s products to engineer reliable agents. Personal AI Assistant with Tools -LangChain agents, tool calling (calculator, search, file readers) -Tech Stack: LangChain Agents, OpenAI, SerpAPI, Python -Skills: Multi-step reasoning, agent actions, chaining 4. types import Command from typing_extensions import NotRequired # 1. from langchain_core. messages import AIMessage, ToolMessage from langchain. This comprehensive Connect with builders who understand your journey. Dec 12, 2025 · LangChain is an open-source framework designed to simplify the creation of applications using large language models (LLMs). If you want to go deeper, the linked middleware docs show the exact implementation details.

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Langchain Tools Prompt. tools import tool from langchain. 4，2. Let's see how this wo