Langchain Tools Import Tool. types import Command from typing_extensions import NotRequi

types import Command from typing_extensions import NotRequired # 1. 0正式开源。记得收藏哦 目录1 16 hours ago · from langgraph. tools. memory import ConversationBufferMemory from langchain_core. tools import tool, ToolRuntime from langchain. tool_node import ToolCallRequest from langgraph. 6 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. messages import HumanMessage basic_model = ChatDeepSeek(model=「deepseek-chat」) reasoner_model = ChatDeepSeek(model=「deepseek-reasoner」) 1 day ago · from typing import Literal from langchain. tools import BaseTool, tool from langchain. How to Create a Custom Tool There are two ways to create a tool: using @tool Sep 24, 2025 · In this article, we’ll walk through two categories of tools in LangChain — built-in tools and custom tools, and then dive into how to create structured tools using Pydantic. 5B-WEBUI镜像的完整流程，结合LangChain框架构建智能代理，实现LeetCode风格编程题的自动解答。 该方案适用于模型微调与AI应用开发，展现小参数模型在特定任务中的高效推理能力。 1 day ago · from typing import Literal from langchain. context 能访问到哪些字段 Flowise is an open source no-code UI visual tool to build 🦜🔗LangChain applications from langchain_deepseek import ChatDeepSeek from langchain. types import Command import time @wrap_tool_call def monitor_tools( from langchain_core. tools import tool # 定义工具 @tool def search (query: str): 5 days ago · LangChain components turn LLMs from “chatbots” into structured, scalable, and production-ready AI systems by separating concerns like reasoning, retrieval, memory, and tool usage. Tools can depend on runtime context and also interact with agent memory. Notice below how the get_user_location tool uses runtime context: Inside tools You can access the runtime information inside tools to: Access the context Read or write long-term memory Write to the custom stream (ex, tool progress / updates) Use the ToolRuntime parameter to access the Runtime object inside a tool. agents import AgentExecutor, create_react_agent from langchain. from langchain. tools import tool from langchain. Tools # Tools are functions that agents can use to interact with the world. Jan 13, 2026 · This page documents the file and directory organization of the langchain-aiplugin repository. com/). bind_tools(tools) memory = MemorySaver() 2 days ago · This blog demonstrated how the OCI OpenAI package makes it easy to build agentic applications on OCI Generative AI using multiple frameworks. agents import create_agent import os from pydantic import BaseModel # 初始化存储后端 (生产环境通常连接 Redis 或 PostgreSQL) store = InMemoryStore() # 这决定了工具中 runtime. That’s where custom tools come in. Functions can have any signature - the tool will automatically infer input schemas unless disabled. memory import MemorySaver model = ChatOpenAI(model="gpt-4o", api_key=openai_api_key) bound_model = model. memory import InMemoryStore from langchain. 文章浏览阅读544次，点赞13次，收藏13次。本文详解LangChain 1. Learn tool calling, memory, workflows, and LLM integration using simple Python examples. get_tools () 26 print (tools) 27 28 # 导入与聊天模型相关的包 29 from langchain. The docstring becomes the tool's description that the agent sees. from_template("Tell me about {topic}") model = ChatOpenAI() chain = prompt | model # Invoke with config result = chain Nov 29, 2025 · Build powerful AI agents with LangChain 2. graph import StateGraph, START, END from langgraph. 1 day ago · LangChain recently introduced Deep Agents: a new way to build structured, multi-agent systems that can plan, delegate, and reason across multiple steps. agents import create_react_agent, AgentExecutor from pydantic import BaseModel, Field from typing import Type, Any 16 hours ago · 文章浏览阅读13次。摘要： LangChain框架通过分层记忆治理机制提升智能体交互能力。短期记忆基于Thread和Checkpointer维持单次会话连贯性，将对话状态持久化存储；长期记忆通过Store接口实现跨会话用户偏好沉淀，使用Namespace隔离数据。文章通过代码示例展示了两种记忆实现方式：短期记忆示例使用 Tool（道具）の定義方法 Pythonの関数に @tool デコレータを付けるだけで、簡単にAI用のツールを作成できます。 from langchain_core. 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 from langchain_aws. These tools can be generic utilities (e. May 2, 2023 · This notebook takes you through how to use LangChain to augment an OpenAI model with access to external tools. 16 hours ago · from langchain. I think in terms of three layers: 1 day ago · The @tool decorator converts any function into a LangChain tool. mcp-use is the easiest way to interact with mcp servers with custom agents - mcp-use/mcp-use 2 days ago · 在之前的学习中，我们眼中的大模型（LLM）更像是一个博学但封闭的“大脑”。它能陪你聊天、写诗、解释复杂的概念，但它有一个致命的弱点：它无法触及外部世界。 它不知道此时此刻北京的天气（因为它只有历史数据 25 tools = toolkit. agents. These Learn how to integrate Reddit with LangChain using the Model Context Protocol (MCP). messages import HumanMessage basic_model = ChatDeepSeek(model=「deepseek-chat」) reasoner_model = ChatDeepSeek(model=「deepseek-reasoner」) from langchain. middleware import wrap_model_call, ModelRequest, ModelResponse from langchain_core. python. It describes the purpose of each directory and key file, showing how the codebase is organized to separate from langchain. The model decides when to invoke a tool based on the conversation context, and what input arguments to provide. Can be used as a decorator with or without arguments to create tools from functions. For questions, please use the LangChain Forum (https://forum. In this post, we’ll explore what custom tools are, how to create them in LangChain, and when you should consider building your own. It comes with built-in planning, a filesystem for context, and subagent spawning. A quick mental model for LangChain in 2026 LangChain in 2026 is more modular than its early versions. By implementing a simple weather agent across the OpenAI SDK, OpenAI Agents SDK, LangChain, LangGraph, and the Microsoft Agent Framework. Under the hood, tools are callable functions with well-defined inputs and outputs that get passed to a chat model. agents import create_agent from langchain. chat_models import init_chat_model model = init_chat_model( "claude-sonnet-4-5-20250929", temperature=0 ) # Define tools @tool def multiply(a: int, b: int) -> int: """Multiply `a` and `b`. 0 in 2025. I added a very descriptive Jan 13, 2026 · Multi-agent当单个智能体无法满足过多工具以及更多的领域和广泛的上下文；或者需要执行顺序约束或者满足条件才能往下执行功能；会引入Multi-agent 模式（Pattern）中文名称工作原理（整理后）核心特点典型适用场景… 3 days ago · # 传统LangChain Agent示例 from langchain. store. We would like to show you a description here but the site won’t allow us. tools import tool, ToolRuntime from langgraph. prompts import PromptTemplate import os from dotenv import load_dotenv # 加载 . prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI prompt = ChatPromptTemplate. checkpoint. invoke ("Hello!") See the full LangChain Integration Guide for memory, retrievers, agents, and more. agents import AgentState, create_agent from langchain. types import Command import time @wrap_tool_call def monitor_tools( LangChain 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. g. Define state with active LangChain 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. 看一下 runtime 下面有啥""" print (f"====> runtime type: {type (runtime Dec 15, 2024 · from langchain_openai import ChatOpenAI from headroom. To improve your LLM application development, pair LangChain with: 1 day ago · Cons: usage costs, network latency, data residency constraints In both cases, you’ll wrap the Hugging Face pipeline in LangChain so the rest of your code can call a single interface. Convert Python functions and Runnables to LangChain tools. tools import create_code_interpreter_toolkit # Create toolkit and get tools (async) toolkit, code_tools = await create_code_interpreter_toolkit(region="us-west-2") from langchain_openai import ChatOpenAI from langgraph. What is Langchain? LangChain is a framework for developing applications powered by language models. env 文件 3 days ago · 本文介绍了基于星图GPU平台自动化部署VibeThinker-1. Tools extend what agents can do—letting them fetch real-time data, execute code, query external databases, and take actions in the world. com Redirecting. tools import tool, ToolRuntime from model_glm import model @tool def test_runtime (runtime: ToolRuntime) -> str: """Test runtime. from langchain_aws. To stream agent progress, use the stream or astream methods with stream_mode="updates". 4 days ago · Build powerful AI agents with Strands using tools, memory, and chains for real-world intelligent automation. middleware import wrap_tool_call from langchain. tools import tool @tool def search_database(query: str, limit: int = 10) -> str: """Search the customer database for records matching the query. 0框架下MCP调用流程，包括官方示例、百度地图MCP对接、DeepSeek模型JSON反序列化报错解决方案，以及异步MCP工具与同步人机交互中间件的兼容实现。提供完整代码示例，帮助开发者快速上手并解决常见问题。_代码中调用mcp 2 days ago · from langchain. integrations import HeadroomChatModel # Wrap your model - that's it! llm = HeadroomChatModel (ChatOpenAI (model="gpt-4o")) # Use exactly like before response = llm. langchain. messages import AIMessage, ToolMessage from langchain. environ["DEEPSEEK_API_KEY"] = "sk-" 16 hours ago · from typing import Any from langgraph. Args: 4 days ago · from langchain. tools import tool from langchain_openai import ChatOpenAI from langchain. But connecting that agent to a real frontend is still surprisingly hard. Step-by-step guide with Python and TypeScript code examples. but sometimes, you need something specific to your use case. agents import create_react_agent, AgentExecutor from langchain import hub from langchain. agents import create_agent agent = create_agent( model="claude-sonnet-4-5-20250929", tools=[check_weather], system_prompt="You are a helpful assistant" ) 2 Create tools Tools let a model interact with external systems by calling functions you define. The tool decorator is an easy way to create tools. chat_models import ChatOpenAI 30 from [Link] import initialize_agent, AgentType 31 32 # 初始化聊天模型 33 llm = ChatOpenAI (temperature=0, model='gpt-4') 34 35 # 通过指定的工具和聊天模型初始化agent 36 agent 2 days ago · Learn how to orchestrate LangChain agents for production using Orkes Conductor with retries, human approval, and full observability. List documents in a folder from box_ai_agents_toolkit import box_folder_items_list @tool(parse_docstring=True) def list_loan_documents(folder_id: str) -> str: """List all documents in a loan application folder. Today, we will build a Deep Agents powered job search assistant and connect it to a live Jan 13, 2026 · Checked other resources This is a bug, not a usage question. structured_output import ToolStrategy from langchain_core. tools import tool @tool def get_weather(city: str) -> str: """都市名を受け取り、現在の天気を返します。 """ # 実際はここで外部APIを叩く Jul 7, 2025 · Understand how to trace, monitor, and debug LangChain and LangGraph apps using OpenTelemetry, down to chains, tools, tokens, and state flows. This emits an event after every agent step. tools import tool import os # 设置 API 密钥 os. May 14, 2025 · LangChain offers a wide variety of built-in tools for search, math, web APIs, and more. runnables import RunnableConfig # Create config with callbacks config = RunnableConfig(callbacks=[handler]) # Use with LCEL chains from langchain_core. 4，2. In particular, you’ll be able to create LLM agents that use custom tools to answer user queries. tools import create_browser_toolkit # Create toolkit and get tools toolkit, browser_tools = create_browser_toolkit(region="us-west-2") 1 day ago · from typing import Literal from langchain. Currently, tools can be loaded with the following snippet: Oct 24, 2024 · How to build Custom Tools in LangChain 1: Using @tool decorator: There are several ways to build custom tools. search), other chains, or even other agents.

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