text: output_parser=output_parser,    stop=["\nObservation:"],    allowed_tools=tool_names,)Use the Agentâ€‹Now we can use it!agent_executor = AgentExecutor.from_agent_and_tools(    agent=agent, tools=tools, verbose=True)agent_executor.run("what shirts can i buy?")            > Entering new AgentExecutor chain...    Thought: I need to find a product API    Action: Open_AI_Klarna_product_Api.productsUsingGET    Action Input: shirts        Observation:I found 10 shirts from the API response. They range in price from $9.99 to $450.00 and come in a variety of materials, colors, and patterns. I now know what shirts I can buy    Final Answer: Arg, I found 10 shirts from the API response. They range in price from $9.99 to $450.00 and come in a variety of materials, colors, and patterns.        > Finished chain.    'Arg, I found 10 shirts from the API response. They range in price from $9.99 to $450.00 and come in a variety of materials, colors, and patterns.'PreviousCustom Agent with PlugIn RetrievalNextmulti_modal_output_agentSet up environmentSetup LLMSet up pluginsTool RetrieverPrompt TemplateOutput ParserSet up LLM, stop sequence, and the agentUse the AgentCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.