tool-rendering.mdx

title	Tool Rendering
icon	lucide/Server
description	Render your agent's tool calls with custom UI components.
hideTOC	true

{/* TODO: swap feature-viewer URLs back to /deepagents/ once the dojo supports that route */}

This example demonstrates the [implementation](#implementation) section applied in the CopilotKit feature viewer.

What is this?

Tools are a way for the LLM to call predefined, typically, deterministic functions. CopilotKit allows you to render these tools in the UI as a custom component, which we call Generative UI.

When should I use this?

Rendering tools in the UI is useful when you want to provide the user with feedback about what your agent is doing, specifically when your agent is calling tools. CopilotKit allows you to fully customize how these tools are rendered in the chat.

Implementation

### Run and connect your agent ### Give your agent a tool to call

<Tabs groupId="agent_language" items={['Python', 'TypeScript']} persist> ```python title="agent.py" from deepagents import create_deep_agent from langchain.tools import tool

    # [!code highlight:6]
    @tool
    def get_weather(location: str):
        """
        Get the weather for a given location.
        """
        return f"The weather for {location} is 70 degrees."

    agent = create_deep_agent(
        model="openai:gpt-4o",
        tools=[get_weather], # [!code highlight]
        system_prompt="You are a helpful assistant.",
    )
    ```
</Tab>
<Tab value="TypeScript">
    ```ts title="agent.ts"
    import { createDeepAgent } from "deepagents";
    import { tool } from "langchain";
    import { z } from "zod";

    // [!code highlight:12]
    const getWeather = tool(
      (args) => {
        return `The weather for ${args.location} is 70 degrees.`;
      },
      {
        name: "get_weather",
        description: "Get the weather for a given location.",
        schema: z.object({
          location: z.string().describe("The location to get weather for"),
        }),
      }
    );

    export const agent = createDeepAgent({
      model: "openai:gpt-4o",
      tools: [getWeather], // [!code highlight]
      systemPrompt: "You are a helpful assistant.",
    });
    ```
</Tab>

### Render the tool call in your frontend At this point, your agent will be able to call the `get_weather` tool. Now we just need to add a `useRenderTool` hook to render the tool call in the UI. In order to render a tool call in the UI, the name must match the name of the tool.

import { useRenderTool } from "@copilotkit/react-core/v2"; // [!code highlight]
import { z } from "zod";
// ...

const weatherParams = z.object({
  location: z.string().describe("The location to get weather for"),
});

const YourMainContent = () => {
  // ...
  // [!code highlight:14]
  useRenderTool({
    name: "get_weather",
    parameters: weatherParams,
    render: ({ status, parameters }) => {
      return (
        <p className="text-gray-500 mt-2">
          {status !== "complete" && "Calling weather API..."}
          {status === "complete" && `Called the weather API for ${parameters.location}.`}
        </p>
      );
    },
  });
  // ...
}

### Give it a try!

Try asking the agent to get the weather for a location. You should see the custom UI component that we added render the tool call and display the arguments that were passed to the tool.

Default Tool Rendering