Langchain agents tools

Langchain agents tools. - get_content: Given a list of document CSV. Agents let the model use tools in a loop, so that it can decide how many times to use tools. The key to using models with tools is correctly prompting a model and parsing its This notebook shows how to use an agent to compare two documents. JSON schema of what the inputs to the tool are. Tool-calling is extremely useful for building tool-using chains and agents, and for getting structured outputs from models more generally. tools = [TavilySearchResults(max_results=1)] # Choose the LLM that will drive the agent. Memory in Agent. agents import load_tools llm = OpenAI(temperature=0) tools = load_tools(["pal-math"], llm=llm) agent = initialize_agent(tools, llm, agent=AgentType. See this section for general instructions on installing integration packages. 📄️ Apify. Observe: react to the response of the tool call by either calling another function or responding to When using custom tools, you can run the assistant and tool execution loop using the built-in AgentExecutor or write your own executor. Heat index: None. Agents let us do just this. Agents. LangChain is a framework for developing applications powered by language models. For example, Let say my custom tool takes 3 input parameters: [input1, input2,input3] :-> bool, str, int. Note 2: There are almost certainly other ways to do this, this is just a first pass. It returns as output either an AgentAction or AgentFinish. base import PALChain from Introduction. There are two main ways to use tools: chains and agents. The Github toolkit contains tools that enable an LLM agent to interact. OpenAI assistants currently have access to two tools hosted by OpenAI: code interpreter, and knowledge retrieval. Then, the Agent is called again with 3 blocks as input: SystemPrompt, HumanPrompt and the AIPrompt. 0: Use create_json_chat_agent instead. The tool returns the accuracy score for a pre-trained model saved at a given path. from langchain import hub. Conversational. A description of what the tool is. This notebook goes over adding memory to an Agent. chat_models import ChatOpenAI from langchain. Bases: Agent. Google Calendar Tool. It can be useful to run the agent as an iterator, to add human-in-the-loop checks as needed. While other tools (like the Requests tools) are fine for static sites, PlayWright Browser toolkits let your agent navigate the web and interact with dynamically rendered sites. By supplying the model with a schema that matches up with a LangChain tool’s signature, along with a name and description of what the tool does, we May 14, 2023 · from langchain. For more information on LangChain agents and their types, see this. ZERO_SHOT_REACT_DESCRIPTION, verbose=True) Let’s test it out on the same example as above: Apr 9, 2024 · class langchain. agents import AgentType from langchain. - find_similar: Given a URL, retrieve a list of search results corresponding to webpages which are similar to the document at the provided URL. Using tools allows the model to request that more than one function will be called upon when appropriate. 57 m/s, direction 240°, humidity of 56%, temperature of 20. In this example, we will use OpenAI Function Calling to create this agent. "Action", 2 days ago · A Runnable sequence representing an agent. We will first create it WITHOUT memory, but we will then show how to add memory in. Chains lets you create a pre-defined sequence of tool usage(s). Using the Exa SDK as LangChain Agent Tools . To use the Google Calendar Tools you need to install the following official peer dependency: Apr 28, 2023 · Colab: https://colab. This covers basics like initializing an agent, creating tools, and adding memory. It takes the name of the category (such as text-classification, depth-estimation, etc), and returns the name of the Jan 22, 2024 · The 'create_retriever_tool' function in the LangChain codebase is used to create a tool for retrieving documents. llm = ChatOpenAI(temperature=0. llm = OpenAI(temperature=0) tools = load_tools(. For an in depth explanation, please check out this conceptual guide. tool_names = [] tools = load_tools(tool_names) Sep 7, 2023 · The langchain framework makes it easy to use LLMs as agents capable of making decisions. We’ll focus on Chains since Agents can route between multiple tools by default. ToolsAgentOutputParser [source] ¶. 1. Deprecated since version 0. Bases: AgentActionMessageLog. Change the content in PREFIX, SUFFIX, and FORMAT_INSTRUCTION according to your need after tying and testing few times. This walkthrough demonstrates how to use an agent optimized for conversation. In this example, we will use OpenAI Tool Calling to create this agent. llms import OpenAI # LLM ラッパーを初期化 llm = OpenAI (temperature = 0. In agents, a language model is used as a reasoning… 6 min read · Apr 17, 2024 This categorizes all the available agents along a few dimensions. Parses a message into agent actions/finish. llm = ChatOpenAI(temperature=0, model_name="gpt-3. Next, we will use the high level constructor for this type of agent. Some tools bundled within the PlayWright Browser toolkit include: NavigateTool (navigate_browser Tools. api. `"generate"` calls the agent's LLM Chain one final time to generate a final answer based on the previous steps. This toolkit is used to interact with the browser. Today, we're announcing agent toolkits, a new abstraction that allows developers to create agents designed for a particular use-case (for example, interacting with a relational database or interacting with an OpenAPI spec). It simplifies the process of programming and integration with external data sources and software workflows. Web Browser Tool. Get started. It is mostly optimized for question answering. openai_tools. Whether the result of a tool should be returned directly to the user. First, you need to install the arxiv python package. This notebook goes through how to create your own custom agent. Multiply these together. These integrations allow developers to create versatile applications that combine the power from langchain. You can use an agent with a different type of model than it is intended Apr 13, 2023 · Langchain Agents and Tools offer a simple, high-level API that allows users to tap into the power of advanced Language Models. By definition, agents take a self-determined, input-dependent sequence of steps before returning a user-facing output. invoke(tool_args 2 days ago · Either 'force' or 'generate'. This notebook shows how to use the [Apify. These tools can be generic utilities (e. get_all_tool_names¶ langchain. Available in both Python- and Javascript-based libraries, LangChain’s tools and APIs simplify the process of building LLM-driven applications like chatbots and virtual agents . Aug 7, 2023 · Creating an agent is one of the few use cases where I believe it is more convenient to use the most powerful Model possible. Memory is needed to enable conversation. description: a short instruction manual that explains when and why the agent should use the tool. info. The 'retriever' argument is an instance of the BaseRetriever class, which is used for the retrieval of documents. agents import load_tools tool_names = [] tools = load_tools(tool_names) # flake8: noqa """Load tools. If you're creating agents using OpenAI models, you should be using this OpenAI Tools agent rather than the OpenAI functions agent. For this example, we’ll create a couple of custom tools as well as LangChain’s provided DuckDuckGo search tool to create a research agent. com/drive/1FYsa3x3PzziL57EHEIuIqa5rkCAxCbin?usp=sharing In this video I look at how you can make your own custom tools t A large collection of built-in Tools. This log can be used in a few ways. Tools 📄️ Alpha Vantage. LangChain provides a standard interface for agents, a selection of agents to choose from, and examples of end-to-end agents. In our Quickstart we went over how to build a Chain that calls a single multiply tool. base. First, let’s initialize Tavily and an OpenAI chat model capable of tool calling: from langchain_community. You switched accounts on another tab or window. Nov 30, 2023 · The Tool. The simplest way to more gracefully handle errors is to try/except the tool-calling step and return a helpful message on errors: from typing import Any. To start, we will set up the retriever we want to use, and then turn it into a retriever tool. chat_models import ChatOpenAI from langchain. The Webbrowser Tool gives your agent the ability to visit a website and extract information. Before going through this notebook, please walkthrough the following notebooks, as this will build on top of both of them: 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. base import LLMMathChain from langchain. chat_models import ChatOpenAI. Is meant to be used with OpenAI models, as it relies on the specific tool_calls parameter from OpenAI to convey what tools to use. langchain. 68°C, and a heat index of None. ) Reason: rely on a language model to reason (about how to answer based on You signed in with another tab or window. Tools are interfaces that an agent, chain, or LLM can use to interact with the world. The Exa SDK creates a client that can use the Exa API to perform three functions: - search: Given a natural language search query, retrieve a list of search results. 📄️ ArXiv. Wikipedia is the largest and most-read reference work in history. Tool calling is only available with supported models. Apr 11, 2024 · By definition, agents take a self-determined, input-dependent sequence of steps before returning a user-facing output. agents import AgentExecutor, create_react_agent, load_tools. We construct these agents using Langchain, an essential open-source library that streamlines the development of adaptable AI agents. agents import load_tools. g. tavily_search import TavilySearchResults. conversational_chat. It should be Jan 12, 2024 · 1. Reload to refresh your session. If a tool_calls parameter is passed, then that is used to get the tool names and tool inputs. The function to call. agents import Tool, AgentExecutor, (agent=agent, tools=tools, verbose=True) agent_executor. See name (str), is required and must be unique within a set of tools provided to an agent description (str), is optional but recommended, as it is used by an agent to determine tool use args_schema (Pydantic BaseModel), is optional but recommended, can be used to provide more information (e. You can use an agent with a different type of model than it is intended Apr 4, 2023 · The agent’s tools — Here, we will equip the agent with a Search Ticketmaster tool for discovering events and a “Bad Bunny rap” tool that allows users to request a rap in Bad Bunny’s style on any topic. LangSmith is especially useful for such cases. To demonstrate the AgentExecutorIterator functionality, we will set up a problem where an Agent must: Retrieve three prime numbers from a Tool. By understanding the core concepts and following the steps outlined Apr 29, 2024 · Let's dive into the core of LangChain Agents, highlighting their unique features and capabilities through examples. Whether this agent is intended for Chat Models (takes in messages, outputs message) or LLMs (takes in string, outputs string). base import APIChain from langchain. LangChain serves as a generic interface for May 25, 2023 · Here is how you can do it. Bases: MultiActionAgentOutputParser. agents import initialize_agent from langchain. from langchain_openai import OpenAI. The examples in LangChain documentation ( JSON agent , HuggingFace example) use tools with a single string input. agents import AgentExecutor, create_openai_tools_agent prompt = hub LangChain Redirecting Mar 19, 2024 · This is different from LangChain chains where the sequence of actions are hardcoded in code. """handle_parsing_errors:Union[bool,str,Callable[ [OutputParserException],str]]=False"""How to handle errors Using agents. agents import AgentExecutor, create_tool_calling_agent, tool from langchain_anthropic import ChatAnthropic from langchain_core. param log: str [Required] ¶. prompts import PromptTemplate llm = OpenAI(model_name='text-davinci-003', temperature = 0. In this simple problem we can demonstrate adding some logic to verify intermediate May 1, 2024 · langchain. This agent is May 2, 2023 · Knowledge Base: Create a knowledge base of "Stuff You Should Know" podcast episodes, to be accessed through a tool. , few-shot examples) or validation for expected parameters. Building an agent from a runnable usually involves a few things: Data processing for the intermediate steps ( agent_scratchpad ). They combine a few things: The name of the tool. 📄️ Shell (bash) Giving agents access to the shell is powerful (though risky outside a. Now, LangChain is the most advanced library for creating Agents, but Hugging Face has also joined the party with their Transformers Agents & tools, and even the ChatGPT plugins could fit into this category. This notebook shows how to use agents to interact with data in CSV format. from langchain_openai import ChatOpenAI. llm_math. input should be a comma separated list of "valid URL including protocol","what you want to find on the page or empty string for a Quickstart. Since the tools in the semantic layer use slightly more complex inputs, I had to dig a little deeper. OpenAIToolsAgentOutputParser [source] ¶. LLM Agent with Tools: Extend the agent with access to multiple tools and test that it uses them to answer questions. Here is an example input for a recommender tool. prompts import Feb 13, 2024 · LLM agents typically have the following main steps: Propose action: the LLM generates text to respond directly to a user or to pass to a function. The Agent is called with a SystemPrompt and a HumanPrompt and the tools & functions are available. ConversationalChatAgent [source] ¶. Read about all the agent types here. Notes. It enables applications that: Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc. Cloud cover: 75%u001b[0m. from_function() method lets you quickly create a tool from a simple function. Aug 15, 2023 · Agents use a combination of an LLM (or an LLM Chain) as well as a Toolkit in order to perform a predefined series of steps to accomplish a goal. The score_tool is a tool I define for the LLM that uses a function named llm Feb 20, 2024 · Tools in the semantic layer. get_all_tool_names ( ) → List [ str ] [source] ¶ Get a list of all possible tool names. %pip install --upgrade --quiet arxiv. It takes three arguments: a retriever, a name, and a description. In some situations, this can help signficantly reduce the time that it takes an agent to achieve its goal. It's generating a markdown content and then call the tool. 📄️ Jira May 2, 2023 · A Structured Tool object is defined by its: name: a label telling the agent which tool to pick. import os from langchain. Choosing between multiple tools. You signed out in another tab or window. It is described to the agent as. Thought:u001b[32;1mu001b[1;3m I now know the current weather in London. It also highlights the challenges and limitations of using LLMs in agent systems. Initialising and running a LangChain agent with access to the LlamaIndex tool: from langchain. First, you'll want to import the relevant modules: tip. These need to represented in a way that the language model can recognize them. 📄️ Gitlab. ["graphql"], Structured Tools | ️ Langchain - python. OpenAIToolAgentAction [source] ¶. You can pass a Runnable into an agent. When building with LangChain, all steps will automatically be traced in LangSmith. from langchain import hub from langchain_community. Try/except tool call. Additional information to log about the action. agents import load_tools from langchain. Importing Necessary Libraries 🤖 Agents: Agents allow an LLM autonomy over how a task is accomplished. llms import OpenAI from langchain. LangChain provides integrations for over 25 different embedding methods, as well as for over 50 different vector storesLangChain is a tool for building applications using large language models (LLMs) like chatbots and virtual agents. This should be pretty tightly coupled to the instructions in the prompt. The article provides case studies and proof-of-concept examples of LLM-powered agents in various domains, such as scientific discovery and generative agents simulation. This notebook goes over how to use the arxiv tool with an agent. This notebook walks through connecting a LangChain email to the. chains. 📄️ Gmail. 📄️ AWS Lambda. The autoreload extension is already loaded. load_tools. Load the LLM Jun 15, 2023 · Initialise LangChain Agent. These tools include, and are not limited to, online search tools, API-based tools, chain-based tools etc. Provides a lot of flexibility in how you call these tools. "Tool calling" in this case refers to a specific type of model API Tool calling agent. 3 days ago · A Runnable sequence representing an agent. Now, let’s create a BaseGraphQLTool instance with the specified Star Wars API endpoint and initialize an Agent with the tool. pal. 75°C, low of 18. Once defined, custom tools can be added to the LangChain agent using the initialize_agent() method. We'll use the tool calling agent, which is generally the most reliable kind and the recommended one for most use cases. LangChain has a large ecosystem of integrations with various external resources like local and remote file systems, APIs and databases. Override init to support instantiation by position for backward compat. useful for when you need to find something on or summarize a webpage. First, you need to install wikipedia python package. The main advantages of using SQL Agents are: It can answer questions based on the databases schema as well as on the databases content (like describing a specific table). runnables import Runnable, RunnableConfig. Apr 21, 2023 · from langchain. LangChain is an open source orchestration framework for the development of applications using large language models (LLMs). Custom tools in LangChain provide task-specific functionality and flexibility, allowing users to define Wikipedia. NOTE: this agent calls the Pandas DataFrame agent under the hood, which in turn calls the Python agent, which executes LLM generated Python code - this can be bad if the LLM generated Python code is harmful. We hope to continue developing different toolkits that can enable agents to do amazing feats. At the end, we have a AI output which is a JSON with the key "tool_calls". LangChain Agents #1: OpenAI Tools Agent. Currently, tools can be loaded with the following snippet: from langchain. Final Answer: The current weather in London is broken clouds, with a wind speed of 2. tools. Tools are functions that agents can use to interact with the world. 📄 Mar 26, 2023 · Agents in LangChain are systems that use a language model to interact with other tools. from langchain_core. agents import initialize_agent. The Gitlab toolkit contains tools that enable an LLM agent to interact. """ from typing import Any, List, Optional from langchain. Tool calling allows a model to respond to a given prompt by generating output that matches a user-defined schema. agents import initialize_agent from langchain. [ Deprecated] An agent designed to hold a conversation in addition to using tools. Note 1: This currently only works for plugins with no auth. Furthermore, these agents can be equipped with a variety of tools which implement different functionalities Huggingface Tools that supporting text I/O can be loaded directly using the load_huggingface_tool function. 📄️ Github. Execute action: your code invokes other software to do things like query a database or call an API. #. search), other chains, or even other agents. u001b[0m. This is a more generalized version of the OpenAI tools agent, which was designed for OpenAI's specific style of tool calling. # Only certain models support this. Setup ChatGPT Plugins. agents import AgentType, initialize_agent, load_tools. Once it has a plan, it uses an embedded traditional Action Agent to solve each step. Concepts There are several key concepts to understand when building agents: Agents, AgentExecutor, Tools, Toolkits. llm = OpenAI (temperature = 0) Google Serper API Wrapper Custom agent. The Google Calendar Tools allow your agent to create and view Google Calendar events from a linked calendar. base import BaseCallbackManager from langchain. run("generate a short blog post to review the plot of the movie Avatar 2. LangChain offers a number of tools and functions that allow you to create SQL Agents which can provide a more flexible way of interacting with SQL databases. How to feed these inputs to the agent who is using thes tool? PlayWright Browser. research. Now let’s take a look at how we might augment this chain so that it can pick from a number of tools to call. from langchain. LangChain offers a wide set of tools that can be integrated with an agent. model_download_counter: This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub. The idea is that the planning step keeps the LLM more "on track" by May 5, 2023 · Still there is an issue. Setup . output_parsers. Alpha Vantage Alpha Vantage provides. This makes debugging these systems particularly tricky, and observability particularly important. . This example shows how to use ChatGPT Plugins within LangChain abstractions. Apr 11, 2024 · One of the most powerful and obvious uses for LLM tool-calling abilities is to build agents. This is an agent specifically optimized for doing retrieval when necessary and also holding a conversation. `"force"` returns a string saying that it stopped because it met a time or iteration limit. 0) It explores the components of such agents, including planning, memory, and tool use. The main thing this affects is the prompting strategy used. Wikipedia is a multilingual free online encyclopedia written and maintained by a community of volunteers, known as Wikipedians, through open collaboration and using a wiki-based editing system called MediaWiki. There are two different ways of doing this - you can either let the agent use the vector stores as normal tools, or you can set returnDirect: true to just use the agent as a router. Other agents are often optimized for using tools to figure out the best response, which is not ideal in a conversational setting where you may want the agent to be able to chat with the user as well. I have the python 3 langchain code below that I'm using to create a conversational agent and define a tool for it to use. agents. Amazon AWS Lambda is a. Providers adopt different conventions for formatting tool schemas and tool calls. Subclassing the BaseTool class provides more control over the tool’s behaviour and defines custom instance variables or propagates callbacks. Mar 1, 2023 · 3 min read Mar 1, 2023. LangChain provides a wide set of toolkits to get started. The model is scored on data that is saved at another path. 5-turbo", streaming=True) agent = initialize_agent(. Agent Types There are many different types of agents to use. It takes as input all the same input variables as the prompt passed in does. google. 2 days ago · class langchain. In this guide, we will go over the basic ways to create Chains and Agents that call Tools. LangChain includes a suite of built-in tools and supports several methods for defining your own custom tools . 7) # ツールの一覧を作成します # `llm-math` ツールを使うのに LLM が必要であることに注意してください tools = load_tools Setup: LangSmith. tools import Tool from langchain. Finally, we will walk through how to construct a Tools. For example, a tool named "GetCurrentWeather" tells the agent that it's for finding the current weather. Tools allow us to extend the capabilities of a model beyond just outputting text/messages. com Redirecting This categorizes all the available agents along a few dimensions. If one is not passed, then the AIMessage is assumed to be the final output. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete done. If you have better ideas, please open a PR! Custom agent. This agent uses a two step process: First, the agent uses an LLM to create a plan to answer the query with clear steps. # flake8: noqa """Tools provide access to various resources and services. agents import AgentType, initialize_agent, load_tools from langchain_openai import OpenAI. 3 days ago · class langchain. all_genres = [. . %load_ext autoreload %autoreload 2. Intended Model Type. It uses LangChain's ToolCall interface to support a wider range of provider implementations, such as Anthropic, Google Gemini, and Mistral in addition to OpenAI. 1. api import news_docs, open_meteo_docs, tmdb_docs from langchain. The OpenAI Tools agent is designed to work seamlessly with the most recent OpenAI models, facilitating the execution of multiple functions or "tools" simultaneously. For this LangChain provides the concept of toolkits - groups of around 3-5 tools needed to accomplish specific objectives. May 26, 2016 · This notebook goes over how to use the arxiv tool with an agent. def try_except_tool(tool_args: dict, config: RunnableConfig) -> Runnable: try: complex_tool. LangChain already has a create_openai_tools_agent() constructor that makes it easy to build an agent with tool-calling models that adhere to the OpenAI tool-calling API, but this won’t work for models like Anthropic and Gemini. Tools can be just about anything — APIs, functions, databases, etc. For example, the GitHub toolkit has a tool for searching through GitHub issues, a tool for reading a file, a tool for commenting, etc. callbacks. 11°C, high of 21. May 1, 2024 · Source code for langchain. Sep 24, 2023 · Custom tools are a critical component when creating an agent using the LangChain framework. LangChain comes with a number of built-in agents that are optimized for different use cases. We've implemented the assistant API in LangChain with some helpful abstractions. 7, openai_api The execution is usually done by a separate agent (equipped with tools). This is generally the most reliable way to create agents. fg an pq ex uw gr uq jl dh pp