text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsAmadeus ToolkitAzure Cognitive Services ToolkitCSV AgentDocument ComparisonGitHubGmail ToolkitJiraJSON AgentMultion ToolkitOffice365 ToolkitOpenAPI agentsNatural Language APIsPandas Dataframe AgentPlayWright Browser ToolkitPowerBI Dataset AgentPython AgentSpark Dataframe AgentSpark SQL AgentSQL Database AgentVectorstore AgentXorbits AgentToolsVector storesGrouped by providerIntegrationsAgent toolkitsMultion ToolkitOn this pageMultion ToolkitThis notebook walks you through connecting LangChain to the MultiOn Client in your browserTo use this toolkit, you will need to add MultiOn Extension to your browser as explained in the MultiOn for Chrome.pip install --upgrade multion > /dev/nullMultiOn Setupâ€‹Login to establish connection with your extension.# Authorize connection to your Browser extentionimport multion multion.login()Use Multion Toolkit within an Agentâ€‹from langchain.agents.agent_toolkits import create_multion_agentfrom langchain.tools.multion.tool import MultionClientToolfrom langchain.agents.agent_types import AgentTypefrom langchain.chat_models import ChatOpenAIagent_executor = create_multion_agent(    llm=ChatOpenAI(temperature=0),    tool=MultionClientTool(),    agent_type=AgentType.OPENAI_FUNCTIONS,    verbose=True)agent.run("show me the weather today")agent.run(    "Tweet about Elon Musk")PreviousJSON AgentNextOffice365 ToolkitMultiOn SetupUse Multion Toolkit within an AgentCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.