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Langchain basetool. It is built on the Runnable protocol.

  • Langchain basetool. Here is a step-by-step guide: Define the input schema using Pydantic 's BaseModel. Jun 19, 2024 · However, LangChain provides other ways to build custom tools that can handle more complex objects as inputs and outputs. See examples of tool attributes, schemas, decorators, and docstrings. This also makes the resultant tool accept a Nov 21, 2023 · Based on the structure of the LangChain framework, the validate_inputs function you've created should ideally be called within the _parse_input method of the BaseTool class. The BaseTool class serves as the foundation for all tools in LangChain. This package provides a LangChain BaseTool implementation based on the sequential thinking pattern, inspired by the Model Context Protocol (MCP) server implementation. Aug 14, 2024 · """**Tools** are classes that an Agent uses to interact with the world. format_scratchpad. This Aug 1, 2023 · 公式ドキュメントを参考に最もシンプルなカスタムツールを作成しました。これはBaseToolを継承し、ツール名（name）とツールの説明（description）を定義しています。run関数への引数の受け渡しは、descriptionで指定します。 tool (Union[dict[str, Any], type[BaseModel], Callable, BaseTool]) – Either a dictionary, a pydantic. LLM based applications often involve a lot of I/O-bound operations, such as making API calls to language models, databases, or other services. Base class for all LangChain tools. Migration guide: For migrating legacy chain abstractions to LCEL. Deprecated. Examples using InjectedToolArg How to pass run time values to tools Aug 27, 2024 · 创建工具，继承BaseTool并且传递了BaseTool中不包含的参数To create a tool by inheriting from BaseTool and passing parameters not included in BaseTool, you can follow the example provided in the LangChain documentation. Mar 26, 2025 · LangChain提供了三种创建工具的方式： 使用@tool装饰器 ——定义自定义工具的最简单方式 使用StructuredTool. Checked other resources I added a very descriptive title to this question. Initialize tool. Each tool has a **description**. In this part, we’ll look at giving our agent access to the entire internet. _parse_input discards any parameter that I pass to the tool. agents import AgentType, Tool, initialize_agent, tool from langchain. as_tool will instantiate a BaseTool with a name, description, and args_schema from a Runnable. Subclassing the BaseTool class provides more control over the tool’s behaviour and defines custom instance variables or propagates callbacks. Tool(name: str, func: Callable, description: str, *, args_schema: Optional[Type[BaseModel]] = None, return Aug 14, 2024 · class langchain_core. tools import BaseTool class My Aug 14, 2024 · class langchain_core. Oct 16, 2024 · LangChainでは、 @tool デコレーターなどで定義した関数を一度 BaseTool に変換し、その後、OpenAIやAnthropicなど各LLMモデル用のパラメータへと変換しています。 (@toolデコレーター => BaseTool => モデルのパラメタ) 関数名 -> name 関数の説明 -> description langchain_core. No default will be assigned until the API is stabilized. Create a new model by parsing and validating input data from keyword arguments. BaseToolkit ¶ class langchain_core. tool. I used the GitHub search to find a similar question and Tools are runnables, and you can treat them the same way as any other runnable at the interface level - you can call invoke(), batch(), and stream() on them as normal. Raises [ValidationError] [pydantic_core tools # Tools are classes that an Agent uses to interact with the world. A toolkit is a collection of related tools that can be used together to accomplish a specific task or work with a particular system. c Sep 9, 2024 · langchain-core: contains the essential LangChain abstractions and the code base for using the new LangChain Expression Language. Tool [source] # Bases: BaseTool Tool that takes in function or coroutine directly. BaseTool 源码分析BaseTool 是 LangChain 框架中定义 tools 的模板类 核心属性name：表示 tool 唯一名称的字符串（用于识别） description：对如何 / 何时 / 为何使用该 tool 的描述，帮助模型决定什么时候调用该 … *args – Extra positional arguments. prompts import Dec 9, 2024 · from typing import Optional, Sequence from langchain_core. Creating tools from functions may be sufficient for most use cases, and can be done via a simple @tool decorator. tools 初始化用于代理程序的LLM。 May 7, 2024 · This tells your tool to expect and validate userinfo according to the schema defined. tools import BaseTool from pydantic import SecretStr from langchain_tests. Asynchronous programming (or async programming) is a paradigm that allows a program to perform multiple tasks concurrently without blocking the execution of other tasks, improving efficiency and responsiveness, particularly in I/O-bound operations. This class allows you to define local variables that can be used within the tool. Defaults to False. Class hierarchy: May 20, 2024 · from langchain. Subclasses must implement the tools property to provide the specific tools for the toolkit. agents. tools import BaseTool from typing import AsyncIterator, Tuple, Any, Optional from langchain. chat import ChatPromptTemplate from langchain_core. base import BaseStandardTests class ToolsTests(BaseStandardTests): """:private: Base class for testing tools. # Construct the agent. openai_tools Apr 16, 2024 · Checked other resources I added a very descriptive title to this question. This issue is created at langchain v0. , if the Runnable takes a dict as input and the specific dict keys are not typed), the schema can be specified directly with args_schema. Agent uses the description to choose the righttool for the job WikipediaQueryRun # class langchain_community. config (Optional[RunnableConfig]) – The config to use for the runnable. Mar 8, 2024 · 文章浏览阅读2. How to: chain runnables How to: stream runnables How to: invoke runnables in parallel How to: add default invocation args to runnables How Example Code I'm encountering an issue where the tool_call_id parameter is consistently None in tool responses, which is failing to return artifact from langchain_core. Jun 26, 2024 · Langchain Tools: TypeError: BaseTool. tools import Tool, BaseTool from langchain_core. These updates require langchain-core>=0. from langchain_core. chat_models import ChatOpenAI from langchain. Installation The python version should be 3. It allows language models to structure their problem-solving process into explicit, potentially revisable thought steps. Aug 5, 2024 · LangChain入門 (6) – Tool/Agent - 外部世界への橋渡し 16 例えば、検索結果を処理する場合、検索した内容が意図したものでない場合は繰り返し処理が必要になりことがあります。 Dec 17, 2024 · That's working to send information, in that example the ID, but also to send some information who I need from the state. load_tools. Secondly, the model needs to return tool arguments that are valid. wikipedia. The universal invocation protocol (Runnables) along with a syntax for combining components (LangChain Expression Language) are also defined here. This abstract class defines the interface that all LangChain tools must implement. I searched the LangChain documentation with the integrated search. While that option provides excellent flexibility, the solution could be brittle and not consistently generating precise Cypher statements. Create the agent: Use the defined tools and a language model to create an agent. pydantic_v1 import BaseModel, Field from langchain_core Apr 2, 2025 · Conversion to LangChain Tools It leverages a utility function convert_mcp_to_langchain_tools(). load_tools(tool_names: List[str], llm: BaseLanguageModel | None = None, callbacks: List[BaseCallbackHandler] | BaseCallbackManager | None = None, allow_dangerous_tools: bool = False, **kwargs: Any) → List[BaseTool] [source] # Load tools based on their name. version (Literal['v1']) – The version of the schema to use. manager import ( AsyncCallbackManagerForToolRun, CallbackManagerForToolRun, ) langchain_core. abc import Sequence from typing import Callable from langchain_core. Toolkits are collections of tools that agents can use. The model may try to call a tool that doesn't exist or fail to return arguments that match the requested schema. BaseTool ¶ Note BaseTool implements the standard Runnable Interface. This can enhance type safety, improve code readability, and simplify the integration of tools and chat models. Alternatively (e. Calling tools with an LLM is generally more reliable than pure prompting, but it isn't perfect. abstract get_tools() → List[BaseTool] [source] # Get the tools in the toolkit. tools import BaseTool class GetIncidentsByUserTool (BaseTool): args_schema = UserInfoSchema # Use the Pydantic model def _run (self, userinfo, *args, **kwargs): # Implementation using userinfo pass Nov 9, 2023 · In the LangChain framework, tools are defined as Python functions that return an instance of a class derived from BaseTool. from_function () method lets you quickly create a tool from a simple function. Most of the time, such values should not be controlled by the LLM. tools import BaseTool, StructuredTool, tool # Define the input arguments' schema using Pydantic class MultiplySchema(BaseModel): langchain. BaseTool [source] ¶ 基类： RunnableSerializable [Union [str, Dict, ToolCall], Any] LangChain 工具必须实现的接口。 初始化工具。 param args_schema: Optional[Type[BaseModel]] = None ¶ Pydantic 模型类，用于验证和解析工具的输入参数。 Args schema 应该是 pydantic. simple. Using a model to invoke a tool has some obvious potential failure modes. tools import BaseTool, StructuredTool, tool: BaseTool: This is a base class for tools in LangChain, which provides foundational functionalities for creating custom tools. callbacks import ( AsyncCallbackManagerForToolRun, CallbackManagerForToolRun, ) from langchain_core. 在这里，我们使用 LangChain 的 BaseTool 对象初始化了自定义的 CircumferenceTool 类。 我们可以将 BaseTool 视为 LangChain 工具的必要模板。 LangChain 要求工具具有两个属性，即 name 和 description 参数。 description 是工具的 自然语言 描述，LLM 根据它来决定是否需要使用该工具。 LangChain 支持从以下内容创建工具： 函数; LangChain 运行接口; 通过从 BaseTool 子类化 -- 这是最灵活的方法，它提供了最大的控制程度，但需要更多的努力和代码。 从函数创建工具可能足以满足大多数用例，可以通过简单的 @tool 装饰器 来完成。如果需要更多配置，例如同时指定同步和异步实现，也可以 LangChain 工具—— BaseTool 的实例——是具有额外约束的 可运行对象，使其能够被语言模型有效调用： 它们的输入被限制为可序列化，特别是字符串和 Python dict 对象； 它们包含名称和描述，指示如何以及何时使用； 它们可能包含详细的 args_schema 以定义其参数。 LangChain Expression Language is a way to create arbitrary custom chains. include_names (Optional[Sequence[str]]) – Only include events from runnables with matching names. Instead of generating Cypher statements, we can implement Cypher templates as LangChain 还有其他几种创建工具的方式；例如，通过子类化 BaseTool 类或使用 StructuredTool。 这些方法在 如何创建自定义工具指南 中有所展示，但我们通常建议在大多数情况下使用 @tool 装饰器。 Apr 22, 2024 · langchain_community. current dir. LangChain 支持从以下方式创建工具： 函数； LangChain Runnables； 通过子类化 BaseTool -- 这是最灵活的方法，它提供了最大程度的控制，但需要付出更多精力和代码。 从函数创建工具可能足以满足大多数用例，并且可以通过简单的 @tool 装饰器 完成。如果需要更多配置——例如，同步和异步实现的指定 load_tools # langchain_community. abstract get_tools() → List[BaseTool] [source] # BaseToolkit # class langchain_core. InjectedToolArg [source] # Annotation for tool arguments that are injected at runtime. The tool schema. 🏃. Aug 3, 2024 · from langchain. pydantic_v1 import BaseModel, Field from typing import List, Optional, Type from langchain_core. BaseToolkit [source] # Bases: BaseModel, ABC Base class for toolkits containing related tools. Interface LangChain tools must implement. Tools allow agents to interact with various resources and services like APIs Sep 5, 2024 · Hello, @SAIL-Fang! To create a custom Agent that reviews git commits and checks their names using LangChain, you can follow these steps: Define the tools: Create a tool that can interact with the git repository to fetch commit names. agents import AgentAction from langchain_core. Agent uses the description to choose the right tool for the job. tools Tool 来自 langchain. tools import BaseTool from langchain_core. BaseModel class, Python function, or BaseTool. Must be empty. Edit: consider response some langchain_core. Class hierarchy: ToolMetaclass --> BaseTool --> <name>Tool # Examples: AIPluginTool, BaseGraphQLTool <name> # Examples: BraveSearch, HumanInputRun Main helpers: CallbackManagerForToolRun, AsyncCallbackManagerForToolRun Classes Tool # class langchain_core. However, when writing custom tools, you may want to invoke other runnables like chat models or retrievers. tools StructuredTool 来自 langchain. Note BaseTool implements the standard Runnable Interface. It is built on the Runnable protocol. messages import BaseMessage from langchain_core. strict (Optional[bool]) – If True, model output is from collections. Return type: List [BaseTool] 3 days ago · This utility function initializes all specified MCP servers in parallel, and returns LangChain Tools (tools: list[BaseTool]) by gathering available MCP tools from the servers, and by wrapping them into LangChain tools. v1. Completely New Tools - String Input and Output The simplest tools accept a single query string and return a string output. Its json-schema suggests no parame Jun 14, 2024 · To properly provide the input schema to the model in LangChain, you can use the get_input_schema method from the BaseTool class. If a dictionary is passed in, it is assumed to already be a valid OpenAI function, a JSON schema with top-level ‘title’ key specified, an Anthropic format tool, or an Amazon Bedrock Converse Dec 21, 2023 · In LangChain, you can pass a DataFrame as a parameter to a user-defined function within a custom tool by using the PythonAstREPLTool class. g. Add any additional Jan 3, 2025 · Image by author using Chatgpt L angChain has emerged as one of the most powerful frameworks for building AI-driven applications, providing modular and extensible components to streamline complex workflows. Tool dataclass The 'Tool' dataclass wraps functions Creating from BaseTool class If you want to create a BaseTool object directly, instead of decorating a function with @tool, you can do so like this: API参考： AgentType 来自 langchain. Tools tool # langchain_core. BaseTool. pydantic_v1 import BaseModel, Field from langchain. Parameters input (Any) – The input to the runnable. BaseTool [source] # Bases: RunnableSerializable [Union [str, Dict, ToolCall], Any] Interface LangChain tools must implement. 39 # langchain-core defines the base abstractions for the LangChain ecosystem. tools tool 来自 langchain. First, we show how to create completely new tools from scratch. Args schema should be either: A subclass of pydantic. messages import ToolCall from langchain_core. In order to properly trace and configure those sub-invocations, you’ll need to manually access and pass in the tool’s Dec 9, 2024 · Create a BaseTool from a Runnable. These tools provide access to various resources and services like APIs, databases, file systems, etc. However, when these default tools cannot satisfy our requirements, we now know how to build our own. 5k次，点赞10次，收藏20次。本文介绍了如何使用装饰器定义工具、继承BaseTool类以及StructuredTool类在构建智能体时提供功能，包括设置工具名称、描述和参数验证。通过谷歌搜索工具实例展示了这些方法的应用。 Apr 8, 2024 · For more information on how to create and use tools in LangChain, you can refer to the LangChain Tools documentation and the source code for the BaseTool class. tools import BaseTool, StructuredTool, tool # Import things that are needed generically from langchain import LLMMathChain, SerpAPIWrapper from langchain. Run the agent: Execute the agent to review git commits. agents initialize_agent 来自 langchain. BaseToolkit [source] ¶ Bases: BaseModel, ABC Base Toolkit representing a collection of related tools. You can also pass arg_types to just Oct 28, 2023 · Python LangChain Course Part 0/6: Overview Part 1/6: Summarizing Long Texts Using LangChain Part 2/6: Chatting with Large Document s Part 3/6: Agents and Tools Part 4/6: Custom Tools Part 5/6: Understanding Agents and Building Your Own Part 6/6: RCI and LangChain Expression Language Welcome back to part 4. This guide 在LangChain中构建自定义工具时，如果您想要更细致地掌控工具的行为，并定义一些特殊的属性或者处理函数，可以考虑从BaseTool类进行派生。 Parameters: tool (Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]) – Either a dictionary, a pydantic. messages. tools import BaseTool Tool # class langchain_core. No third-party integrations are Bases: BaseModel, ABC Base Toolkit representing a collection of related tools. llms import OllamaLLM from langchain_ollama. return_direct – Whether to return directly from the tool rather than continuing the agent loop. runnables import Runnable, RunnablePassthrough from langchain_core. get_input_schema. BaseModel. This method helps define and communicate input schemas to the model, similar to how get_format_instructions works for output schemas. agents ChatOpenAI 来自 langchain. BaseModel 的子类（如果 Semantic layer over graph database You can use database queries to retrieve information from a graph database like Neo4j. base. param callback_manager: Optional[BaseCallbackManager] = None ¶ Documentation for LangChain. Class hierarchy: BaseTool # class langchain_core. tools. If a dictionary is passed in, it is assumed to already be a valid OpenAI tool, OpenAI function, or a JSON schema with top-level ‘title’ and ‘description’ keys specified. Create a custom tool class by subclassing BaseTool. 🏃 The Runnable Interface has additional methods that are available on runnables, such as with_types, with_retry, assign, bind, get_graph, and more. agents import AgentExecutor, create_tool_calling_agent from langchain_openai import ChatOpenAI from langchain. infer_schema – Whether to infer the schema of the arguments from the function’s signature. One option is to use LLMs to generate Cypher statements. For example, the tool logic may require using the ID of the user who made the request. Initialize the tool. Tool [source] ¶ Bases: BaseTool Tool that takes in function or coroutine directly. Raises ValidationError if the input data cannot be parsed to form a valid model. How can I change this code so that it doesn't throw an error? Code: from langchain. Here's a step-by-step Jun 12, 2024 · from langchain_core. Tools are interfaces that an agent can use to interact with the world. function_calling import convert_to_openai_tool from langchain. Pydantic model class to validate and parse the tool’s input arguments. langchain-core: 0. The interfaces for core components like chat models, LLMs, vector stores, retrievers, and more are defined here. param args_schema: Optional[Type[BaseModel]] = None ¶ Pydantic model class to validate and parse the tool’s input arguments. There are two ways to do this: either by using the Tool dataclass, or by subclassing the BaseTool class. Firstly, the model needs to return a output that can be parsed at all. Nov 2, 2024 · The tool is expecting an argument, but I haven't provided one. Jun 14, 2024 · 您还可以通过将自定义工具子类化为BaseTool类来明确定义自定义工具。 这提供了对工具定义的最大控制，但需要更多的工作。 You may need to bind values to a tool that are only known at runtime. Tool arguments annotated with this class are not included in the tool schema sent to language models and are instead injected during execution. jsAbstract base class for toolkits in LangChain. Please use callbacks instead. If your tool function requires multiple arguments, you might want to skip down to the StructuredTool section below. A number of chat models also support accepting Pydantic v2 models in bind_tools and with_structured_output (including Anthropic, OpenAI, Fireworks, and Mistral). We will use the default agent type here. Once class langchain_core. , specification Nov 21, 2023 · Using Subclass BaseTool Another approach for creating the structured tools is subclassing the BaseTool after importing the class CallBack and AsyncCallBack managers from LangChain: from typing import Optional, Type from langchain. 202 Consider the ListDirectoryTool Its only parameter has a default value as the . callbacks import CallbackManagerForToolRun class UpdateDataInput (BaseModel): [docs] classBaseTool(RunnableSerializable[Union[str,dict,ToolCall],Any]):"""Base class for all LangChain tools. Each tool has a description. WikipediaQueryRun [source] # Bases: BaseTool Tool that searches the Wikipedia API. We can often use LangChain’s default tools for running SQL queries, performing calculations, or doing vector search. LangChain has a few other ways to create tools; e. I used the GitHub search to find a similar question and Jun 17, 2023 · Issue you'd like to raise. Not just Apr 28, 2025 · 在LangChain项目中，开发者经常需要创建自定义工具类来扩展功能。当继承BaseTool类时，可能会遇到类型检查器对args_schema属性的警告问题。本文将深入分析这一问题，并提供专业解决方案。 ## 问题背景 在LangChain框架中，BaseTool是所有工具类的基类。开发者通过继 New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications. Where possible, schemas are inferred from runnable. In fact, allowing the LLM to control the user ID may lead to a security risk. Tool ¶ class langchain. AIMessage who have tool_call. BaseTool implements the standard Runnable Interface. How should I do it? class langchain_core. chat_models BaseTool 来自 langchain. Q: Can I use previously defined string BaseTool 's with new agents built for StructuredTool ’s A: Yes! Structured tools don’t require new agent executors, and older tools are forwards compatible. If more configuration is needed-- e. BaseToolkit ¶ class langchain_community. Why is that? from langchain_core. Jul 30, 2024 · LangChain APIs now allow using Pydantic v2 models for BaseTool and StructuredTool. Strategies like keeping schemas simple, reducing the number of tools you pass at once, and having good names and descriptions can help mitigate this risk, but aren't foolproof. 0. utils. callbacks. A key feature of LangChain is the ability to create custom tools that integrate seamlessly with your AI models, enabling enhanced capabilities tailored to your specific use case. May 17, 2025 · BaseTool 是 LangChain 框架中的抽象基类，用于创建语言 模型 （尤其在基于代理的系统中）可调用的工具。 它提供标准接口，支持输入验证、错误处理、工件输出及与 LangChain 可运行对象的集成。 Learn how to create custom tools for LangChain agents using functions, runnables, or subclassing BaseTool. Tools are components that can be called by agents to perform specific actions. Defaults to None. from_function () method or subclass the BaseTool class. 2. agent_toolkits. invoke () takes from 2 to 3 positional arguments but 4 were given #23533 InjectedToolArg # class langchain_core. tool(*args: str | Callable | Runnable, return_direct: bool = False, args_schema: Type | None = None, infer_schema: bool = True, response_format: Literal['content', 'content_and_artifact'] = 'content', parse_docstring: bool = False, error_on_invalid_docstring: bool = True) → Callable [source] # Make tools out of functions, can be used with or without Apr 15, 2024 · 文章浏览阅读6. It implements the RunnableSerializable interface, making tools composable with other LangChain components through the Runnable protocol. import os from abc import abstractmethod from typing import Union from unittest import mock import pytest from langchain_core. StructuredTool [source] ¶ Bases: BaseTool Tool that can operate on any number of inputs. BaseModel 的子类。 或 - pydantic. ai. param args_schema: Type[BaseModel] [Required] ¶ The input arguments’ schema. These methods are shown in the how to create custom tools guide, but we generally recommend using the @tool decorator for most cases. The Tool. This function handles parallel initialization of specified multiple MCP servers and converts their available tools into a list of LangChain-compatible tools (List [BaseTool]). May 2, 2023 · Tools that inherit from the BaseTool class and accept a single string argument will still be treated as string tools. 1k次，点赞19次，收藏29次。本文介绍了如何通过LangChain框架构建自定义工具，如CustomSearchTool，以连接和管理大型语言模型（LLMs），如GPT，用于解决特定问题。BaseTool的构造方法和自定义工具的参数定义是关键内容。 Dec 9, 2024 · from __future__ import annotations import textwrap from inspect import signature from typing import Any, Awaitable, Callable, Dict, List, Literal, Optional, Type, Union from langchain_core. args_schema – optional argument schema for user to specify. Currently only version 1 is available. One way is to use the StructuredTool class, which allows you to define a tool that takes structured arguments. Nov 30, 2023 · Creating a custom tool in LangChain To define a custom tool in LangChain, you can use the Tool. tools import BaseTool from Each tool has a description. prompts. convert. Class hierarchy: # Import things that are needed generically from langchain. BaseToolkit [source] # Bases: BaseModel, ABC Base Toolkit representing a collection of related tools. prompts import ChatPromptTemplate from langchain_ollama. include Apr 10, 2024 · The bottom up way to create a Tool in LangChain would be to extend the BaseTool class, set the name and description fields on the class, and implement the _run method. LCEL cheatsheet: For a quick overview of how to use the main LCEL primitives. langchain: this package includes all advanced feature of an LLM invocation that can be used to implement a LLM app: memory, document retrieval, and agents. language_models import BaseLanguageModel from langchain_core. Instead, the LLM should only control the parameters of the tool that are meant to be Aug 22, 2023 · I want to create a custom tool class with an additional property, let's say number. , by sub-classing the BaseTool class or by using StructuredTool. 11 or higher. tools # Tools are classes that an Agent uses to interact with the world. from_function 类方法 —— 这类似于 @tool 装饰器，但允许更多配置和同步和异步实现的规范。 通过子类BaseTool —— 这是最灵活的方法，它提供了最大程度的控制，但需要更多的工作量和代码。 @tool . Feb 8, 2024 · However if I don't include it in the input model, the method langchain_core. LangChain supports the creation of tools from: Functions; LangChain Runnables; By sub-classing from BaseTool -- This is the most flexible method, it provides the largest degree of control, at the expense of more effort and code. yktcwy gconyr gghiop vffoq ujqz emez jmrmpg vjupym jft qjph