text: The agent is able to iteratively explore the blob to find what it needs to answer the user's question.ğŸ“„ï¸� Multion ToolkitThis notebook walks you through connecting LangChain to the MultiOn Client in your browserğŸ“„ï¸� Office365 ToolkitThis notebook walks through connecting LangChain to Office365 email and calendar.ğŸ“„ï¸� OpenAPI agentsWe can construct agents to consume arbitrary APIs, here APIs conformant to the OpenAPI/Swagger specification.ğŸ“„ï¸� Natural Language APIsNatural Language API Toolkits (NLAToolkits) permit LangChain Agents to efficiently plan and combine calls across endpoints. This notebook demonstrates a sample composition of the Speak, Klarna, and Spoonacluar APIs.ğŸ“„ï¸� Pandas Dataframe AgentThis notebook shows how to use agents to interact with a pandas dataframe. It is mostly optimized for question answering.ğŸ“„ï¸� PlayWright Browser ToolkitThis toolkit is used to interact with the browser. While other tools (like the Requests tools) are fine for static sites, Browser toolkits let your agent navigate the web and interact with dynamically rendered sites. Some tools bundled within the Browser toolkit include:ğŸ“„ï¸� PowerBI Dataset AgentThis notebook showcases an agent designed to interact with a Power BI Dataset. The agent is designed to answer more general questions about a dataset, as well as recover from errors.ğŸ“„ï¸� Python AgentThis notebook showcases an agent designed to write and execute python code to answer a question.ğŸ“„ï¸� Spark Dataframe AgentThis notebook shows how to use agents to interact with a Spark dataframe and Spark Connect. It is mostly optimized for question answering.ğŸ“„ï¸� Spark SQL AgentThis notebook shows how to use agents to interact